The Robustness of Pre-School Children's Tendency to Count Discrete Physical Objects

ERIC Educational Resources Information Center

Fletcher, Ben; Pine, Karen J.

2009-01-01

When pre-school children count an array of objects containing one that is broken in half, most count the halves as two separate objects. Two studies explore this predisposition to count discrete physical objects (DPOs) and investigate its robustness in the face of various manipulations. In Experiment 1, 32 children aged three-four years counted…

Robust Spectral Unmixing of Sparse Multispectral Lidar Waveforms using Gamma Markov Random Fields

DOE PAGES

Altmann, Yoann; Maccarone, Aurora; McCarthy, Aongus; ...

2017-05-10

Here, this paper presents a new Bayesian spectral un-mixing algorithm to analyse remote scenes sensed via sparse multispectral Lidar measurements. To a first approximation, in the presence of a target, each Lidar waveform consists of a main peak, whose position depends on the target distance and whose amplitude depends on the wavelength of the laser source considered (i.e, on the target reflectivity). Besides, these temporal responses are usually assumed to be corrupted by Poisson noise in the low photon count regime. When considering multiple wavelengths, it becomes possible to use spectral information in order to identify and quantify the mainmore » materials in the scene, in addition to estimation of the Lidar-based range profiles. Due to its anomaly detection capability, the proposed hierarchical Bayesian model, coupled with an efficient Markov chain Monte Carlo algorithm, allows robust estimation of depth images together with abundance and outlier maps associated with the observed 3D scene. The proposed methodology is illustrated via experiments conducted with real multispectral Lidar data acquired in a controlled environment. The results demonstrate the possibility to unmix spectral responses constructed from extremely sparse photon counts (less than 10 photons per pixel and band).« less

Real-time yield estimation based on deep learning

NASA Astrophysics Data System (ADS)

Rahnemoonfar, Maryam; Sheppard, Clay

2017-05-01

Crop yield estimation is an important task in product management and marketing. Accurate yield prediction helps farmers to make better decision on cultivation practices, plant disease prevention, and the size of harvest labor force. The current practice of yield estimation based on the manual counting of fruits is very time consuming and expensive process and it is not practical for big fields. Robotic systems including Unmanned Aerial Vehicles (UAV) and Unmanned Ground Vehicles (UGV), provide an efficient, cost-effective, flexible, and scalable solution for product management and yield prediction. Recently huge data has been gathered from agricultural field, however efficient analysis of those data is still a challenging task. Computer vision approaches currently face diffident challenges in automatic counting of fruits or flowers including occlusion caused by leaves, branches or other fruits, variance in natural illumination, and scale. In this paper a novel deep convolutional network algorithm was developed to facilitate the accurate yield prediction and automatic counting of fruits and vegetables on the images. Our method is robust to occlusion, shadow, uneven illumination and scale. Experimental results in comparison to the state-of-the art show the effectiveness of our algorithm.

Automated inference procedure for the determination of cell growth parameters

NASA Astrophysics Data System (ADS)

Harris, Edouard A.; Koh, Eun Jee; Moffat, Jason; McMillen, David R.

2016-01-01

The growth rate and carrying capacity of a cell population are key to the characterization of the population's viability and to the quantification of its responses to perturbations such as drug treatments. Accurate estimation of these parameters necessitates careful analysis. Here, we present a rigorous mathematical approach for the robust analysis of cell count data, in which all the experimental stages of the cell counting process are investigated in detail with the machinery of Bayesian probability theory. We advance a flexible theoretical framework that permits accurate estimates of the growth parameters of cell populations and of the logical correlations between them. Moreover, our approach naturally produces an objective metric of avoidable experimental error, which may be tracked over time in a laboratory to detect instrumentation failures or lapses in protocol. We apply our method to the analysis of cell count data in the context of a logistic growth model by means of a user-friendly computer program that automates this analysis, and present some samples of its output. Finally, we note that a traditional least squares fit can provide misleading estimates of parameter values, because it ignores available information with regard to the way in which the data have actually been collected.

Platelet count and total and cause-specific mortality in the Women's Health Initiative.

PubMed

Kabat, Geoffrey C; Kim, Mimi Y; Verma, Amit K; Manson, JoAnn E; Lin, Juan; Lessin, Lawrence; Wassertheil-Smoller, Sylvia; Rohan, Thomas E

2017-04-01

We used data from the Women's Health Initiative to examine the association of platelet count with total mortality, coronary heart disease (CHD) mortality, cancer mortality, and non-CHD/noncancer mortality. Platelet count was measured at baseline in 159,746 postmenopausal women and again in year 3 in 75,339 participants. Participants were followed for a median of 15.9 years. Cox proportional hazards models were used to estimate the relative mortality hazards associated with deciles of baseline platelet count and of the mean of baseline + year 3 platelet count. Low and high deciles of both baseline and mean platelet count were positively associated with total mortality, CHD mortality, cancer mortality, and non-CHD/noncancer mortality. The association was robust and was not affected by adjustment for a number of potential confounding factors, exclusion of women with comorbidity, or allowance for reverse causality. Low- and high-platelet counts were associated with all four outcomes in never smokers, former smokers, and current smokers. In this large study of postmenopausal women, both low- and high-platelet counts were associated with total and cause-specific mortality. Copyright © 2017 Elsevier Inc. All rights reserved.

A New Method for Estimating Bacterial Abundances in Natural Samples using Sublimation

NASA Technical Reports Server (NTRS)

Glavin, Daniel P.; Cleaves, H. James; Schubert, Michael; Aubrey, Andrew; Bada, Jeffrey L.

2004-01-01

We have developed a new method based on the sublimation of adenine from Escherichia coli to estimate bacterial cell counts in natural samples. To demonstrate this technique, several types of natural samples including beach sand, seawater, deep-sea sediment, and two soil samples from the Atacama Desert were heated to a temperature of 500 C for several seconds under reduced pressure. The sublimate was collected on a cold finger and the amount of adenine released from the samples then determined by high performance liquid chromatography (HPLC) with UV absorbance detection. Based on the total amount of adenine recovered from DNA and RNA in these samples, we estimated bacterial cell counts ranging from approx. l0(exp 5) to l0(exp 9) E. coli cell equivalents per gram. For most of these samples, the sublimation based cell counts were in agreement with total bacterial counts obtained by traditional DAPI staining. The simplicity and robustness of the sublimation technique compared to the DAPI staining method makes this approach particularly attractive for use by spacecraft instrumentation. NASA is currently planning to send a lander to Mars in 2009 in order to assess whether or not organic compounds, especially those that might be associated with life, are present in Martian surface samples. Based on our analyses of the Atacama Desert soil samples, several million bacterial cells per gam of Martian soil should be detectable using this sublimation technique.

Assessing the composition of fragmented agglutinated foraminiferal assemblages in ancient sediments: comparison of counting and area-based methods in Famennian samples (Late Devonian)

NASA Astrophysics Data System (ADS)

Girard, Catherine; Dufour, Anne-Béatrice; Charruault, Anne-Lise; Renaud, Sabrina

2018-01-01

Benthic foraminifera have been used as proxies for various paleoenvironmental variables such as food availability, carbon flux from surface waters, microhabitats, and indirectly water depth. Estimating assemblage composition based on morphotypes, as opposed to genus- or species-level identification, potentially loses important ecological information but opens the way to the study of ancient time periods. However, the ability to accurately constrain benthic foraminiferal assemblages has been questioned when the most abundant foraminifera are fragile agglutinated forms, particularly prone to fragmentation. Here we test an alternate method for accurately estimating the composition of fragmented assemblages. The cumulated area per morphotype method is assessed, i.e., the sum of the area of all tests or fragments of a given morphotype in a sample. The percentage of each morphotype is calculated as a portion of the total cumulated area. Percentages of different morphotypes based on counting and cumulated area methods are compared one by one and analyzed using principal component analyses, a co-inertia analysis, and Shannon diversity indices. Morphotype percentages are further compared to an estimate of water depth based on microfacies description. Percentages of the morphotypes are not related to water depth. In all cases, counting and cumulated area methods deliver highly similar results, suggesting that the less time-consuming traditional counting method may provide robust estimates of assemblages. The size of each morphotype may deliver paleobiological information, for instance regarding biomass, but should be considered carefully due to the pervasive issue of fragmentation.

Robust Bayesian Fluorescence Lifetime Estimation, Decay Model Selection and Instrument Response Determination for Low-Intensity FLIM Imaging

PubMed Central

Rowley, Mark I.; Coolen, Anthonius C. C.; Vojnovic, Borivoj; Barber, Paul R.

2016-01-01

We present novel Bayesian methods for the analysis of exponential decay data that exploit the evidence carried by every detected decay event and enables robust extension to advanced processing. Our algorithms are presented in the context of fluorescence lifetime imaging microscopy (FLIM) and particular attention has been paid to model the time-domain system (based on time-correlated single photon counting) with unprecedented accuracy. We present estimates of decay parameters for mono- and bi-exponential systems, offering up to a factor of two improvement in accuracy compared to previous popular techniques. Results of the analysis of synthetic and experimental data are presented, and areas where the superior precision of our techniques can be exploited in Förster Resonance Energy Transfer (FRET) experiments are described. Furthermore, we demonstrate two advanced processing methods: decay model selection to choose between differing models such as mono- and bi-exponential, and the simultaneous estimation of instrument and decay parameters. PMID:27355322

HIV Diversity as a Biomarker for HIV Incidence Estimation: Including a High-Resolution Melting Diversity Assay in a Multiassay Algorithm

PubMed Central

Cousins, Matthew M.; Konikoff, Jacob; Laeyendecker, Oliver; Celum, Connie; Buchbinder, Susan P.; Seage, George R.; Kirk, Gregory D.; Moore, Richard D.; Mehta, Shruti H.; Margolick, Joseph B.; Brown, Joelle; Mayer, Kenneth H.; Koblin, Beryl A.; Wheeler, Darrell; Justman, Jessica E.; Hodder, Sally L.; Quinn, Thomas C.; Brookmeyer, Ron

2014-01-01

Multiassay algorithms (MAAs) can be used to estimate cross-sectional HIV incidence. We previously identified a robust MAA that includes the BED capture enzyme immunoassay (BED-CEIA), the Bio-Rad Avidity assay, viral load, and CD4 cell count. In this report, we evaluated MAAs that include a high-resolution melting (HRM) diversity assay that does not require sequencing. HRM scores were determined for eight regions of the HIV genome (2 in gag, 1 in pol, and 5 in env). The MAAs that were evaluated included the BED-CEIA, the Bio-Rad Avidity assay, viral load, and the HRM diversity assay, using HRM scores from different regions and a range of region-specific HRM diversity assay cutoffs. The performance characteristics based on the proportion of samples that were classified as MAA positive by duration of infection were determined for each MAA, including the mean window period. The cross-sectional incidence estimates obtained using optimized MAAs were compared to longitudinal incidence estimates for three cohorts in the United States. The performance of the HRM-based MAA was nearly identical to that of the MAA that included CD4 cell count. The HRM-based MAA had a mean window period of 154 days and provided cross-sectional incidence estimates that were similar to those based on cohort follow-up. HIV diversity is a useful biomarker for estimating HIV incidence. MAAs that include the HRM diversity assay can provide accurate HIV incidence estimates using stored blood plasma or serum samples without a requirement for CD4 cell count data. PMID:24153134

A unified genetic association test robust to latent population structure for a count phenotype.

PubMed

Song, Minsun

2018-06-04

Confounding caused by latent population structure in genome-wide association studies has been a big concern despite the success of genome-wide association studies at identifying genetic variants associated with complex diseases. In particular, because of the growing interest in association mapping using count phenotype data, it would be interesting to develop a testing framework for genetic associations that is immune to population structure when phenotype data consist of count measurements. Here, I propose a solution for testing associations between single nucleotide polymorphisms and a count phenotype in the presence of an arbitrary population structure. I consider a classical range of models for count phenotype data. Under these models, a unified test for genetic associations that protects against confounding was derived. An algorithm was developed to efficiently estimate the parameters that are required to fit the proposed model. I illustrate the proposed approach using simulation studies and an empirical study. Both simulated and real-data examples suggest that the proposed method successfully corrects population structure. Copyright © 2018 John Wiley & Sons, Ltd.

A full-spectral Bayesian reconstruction approach based on the material decomposition model applied in dual-energy computed tomography.

PubMed

Cai, C; Rodet, T; Legoupil, S; Mohammad-Djafari, A

2013-11-01

Dual-energy computed tomography (DECT) makes it possible to get two fractions of basis materials without segmentation. One is the soft-tissue equivalent water fraction and the other is the hard-matter equivalent bone fraction. Practical DECT measurements are usually obtained with polychromatic x-ray beams. Existing reconstruction approaches based on linear forward models without counting the beam polychromaticity fail to estimate the correct decomposition fractions and result in beam-hardening artifacts (BHA). The existing BHA correction approaches either need to refer to calibration measurements or suffer from the noise amplification caused by the negative-log preprocessing and the ill-conditioned water and bone separation problem. To overcome these problems, statistical DECT reconstruction approaches based on nonlinear forward models counting the beam polychromaticity show great potential for giving accurate fraction images. This work proposes a full-spectral Bayesian reconstruction approach which allows the reconstruction of high quality fraction images from ordinary polychromatic measurements. This approach is based on a Gaussian noise model with unknown variance assigned directly to the projections without taking negative-log. Referring to Bayesian inferences, the decomposition fractions and observation variance are estimated by using the joint maximum a posteriori (MAP) estimation method. Subject to an adaptive prior model assigned to the variance, the joint estimation problem is then simplified into a single estimation problem. It transforms the joint MAP estimation problem into a minimization problem with a nonquadratic cost function. To solve it, the use of a monotone conjugate gradient algorithm with suboptimal descent steps is proposed. The performance of the proposed approach is analyzed with both simulated and experimental data. The results show that the proposed Bayesian approach is robust to noise and materials. It is also necessary to have the accurate spectrum information about the source-detector system. When dealing with experimental data, the spectrum can be predicted by a Monte Carlo simulator. For the materials between water and bone, less than 5% separation errors are observed on the estimated decomposition fractions. The proposed approach is a statistical reconstruction approach based on a nonlinear forward model counting the full beam polychromaticity and applied directly to the projections without taking negative-log. Compared to the approaches based on linear forward models and the BHA correction approaches, it has advantages in noise robustness and reconstruction accuracy.

Evaluation of sliding baseline methods for spatial estimation for cluster detection in the biosurveillance system

PubMed Central

Xing, Jian; Burkom, Howard; Moniz, Linda; Edgerton, James; Leuze, Michael; Tokars, Jerome

2009-01-01

Background The Centers for Disease Control and Prevention's (CDC's) BioSense system provides near-real time situational awareness for public health monitoring through analysis of electronic health data. Determination of anomalous spatial and temporal disease clusters is a crucial part of the daily disease monitoring task. Our study focused on finding useful anomalies at manageable alert rates according to available BioSense data history. Methods The study dataset included more than 3 years of daily counts of military outpatient clinic visits for respiratory and rash syndrome groupings. We applied four spatial estimation methods in implementations of space-time scan statistics cross-checked in Matlab and C. We compared the utility of these methods according to the resultant background cluster rate (a false alarm surrogate) and sensitivity to injected cluster signals. The comparison runs used a spatial resolution based on the facility zip code in the patient record and a finer resolution based on the residence zip code. Results Simple estimation methods that account for day-of-week (DOW) data patterns yielded a clear advantage both in background cluster rate and in signal sensitivity. A 28-day baseline gave the most robust results for this estimation; the preferred baseline is long enough to remove daily fluctuations but short enough to reflect recent disease trends and data representation. Background cluster rates were lower for the rash syndrome counts than for the respiratory counts, likely because of seasonality and the large scale of the respiratory counts. Conclusion The spatial estimation method should be chosen according to characteristics of the selected data streams. In this dataset with strong day-of-week effects, the overall best detection performance was achieved using subregion averages over a 28-day baseline stratified by weekday or weekend/holiday behavior. Changing the estimation method for particular scenarios involving different spatial resolution or other syndromes can yield further improvement. PMID:19615075

Monitoring Oilfield Operations and GHG Emissions Sources Using Object-based Image Analysis of High Resolution Spatial Imagery

NASA Astrophysics Data System (ADS)

Englander, J. G.; Brodrick, P. G.; Brandt, A. R.

2015-12-01

Fugitive emissions from oil and gas extraction have become a greater concern with the recent increases in development of shale hydrocarbon resources. There are significant gaps in the tools and research used to estimate fugitive emissions from oil and gas extraction. Two approaches exist for quantifying these emissions: atmospheric (or 'top down') studies, which measure methane fluxes remotely, or inventory-based ('bottom up') studies, which aggregate leakage rates on an equipment-specific basis. Bottom-up studies require counting or estimating how many devices might be leaking (called an 'activity count'), as well as how much each device might leak on average (an 'emissions factor'). In a real-world inventory, there is uncertainty in both activity counts and emissions factors. Even at the well level there are significant disagreements in data reporting. For example, some prior studies noted a ~5x difference in the number of reported well completions in the United States between EPA and private data sources. The purpose of this work is to address activity count uncertainty by using machine learning algorithms to classify oilfield surface facilities using high-resolution spatial imagery. This method can help estimate venting and fugitive emissions sources from regions where reporting of oilfield equipment is incomplete or non-existent. This work will utilize high resolution satellite imagery to count well pads in the Bakken oil field of North Dakota. This initial study examines an area of ~2,000 km2 with ~1000 well pads. We compare different machine learning classification techniques, and explore the impact of training set size, input variables, and image segmentation settings to develop efficient and robust techniques identifying well pads. We discuss the tradeoffs inherent to different classification algorithms, and determine the optimal algorithms for oilfield feature detection. In the future, the results of this work will be leveraged to be provide activity counts of oilfield surface equipment including tanks, pumpjacks, and holding ponds.

Hematologic and serum biochemical reference intervals for free-ranging common bottlenose dolphins (Tursiops truncatus) and variation in the distributions of clinicopathologic values related to geographic sampling site.

PubMed

Schwacke, Lori H; Hall, Ailsa J; Townsend, Forrest I; Wells, Randall S; Hansen, Larry J; Hohn, Aleta A; Bossart, Gregory D; Fair, Patricia A; Rowles, Teresa K

2009-08-01

To develop robust reference intervals for hematologic and serum biochemical variables by use of data derived from free-ranging bottlenose dolphins (Tursiops truncatus) and examine potential variation in distributions of clinicopathologic values related to sampling sites' geographic locations. 255 free-ranging bottlenose dolphins. Data from samples collected during multiple bottlenose dolphin capture-release projects conducted at 4 southeastern US coastal locations in 2000 through 2006 were combined to determine reference intervals for 52 clinicopathologic variables. A nonparametric bootstrap approach was applied to estimate 95th percentiles and associated 90% confidence intervals; the need for partitioning by length and sex classes was determined by testing for differences in estimated thresholds with a bootstrap method. When appropriate, quantile regression was used to determine continuous functions for 95th percentiles dependent on length. The proportion of out-of-range samples for all clinicopathologic measurements was examined for each geographic site, and multivariate ANOVA was applied to further explore variation in leukocyte subgroups. A need for partitioning by length and sex classes was indicated for many clinicopathologic variables. For each geographic site, few significant deviations from expected number of out-of-range samples were detected. Although mean leukocyte counts did not vary among sites, differences in the mean counts for leukocyte subgroups were identified. Although differences in the centrality of distributions for some variables were detected, the 95th percentiles estimated from the pooled data were robust and applicable across geographic sites. The derived reference intervals provide critical information for conducting bottlenose dolphin population health studies.

An empirical likelihood ratio test robust to individual heterogeneity for differential expression analysis of RNA-seq.

PubMed

Xu, Maoqi; Chen, Liang

2018-01-01

The individual sample heterogeneity is one of the biggest obstacles in biomarker identification for complex diseases such as cancers. Current statistical models to identify differentially expressed genes between disease and control groups often overlook the substantial human sample heterogeneity. Meanwhile, traditional nonparametric tests lose detailed data information and sacrifice the analysis power, although they are distribution free and robust to heterogeneity. Here, we propose an empirical likelihood ratio test with a mean-variance relationship constraint (ELTSeq) for the differential expression analysis of RNA sequencing (RNA-seq). As a distribution-free nonparametric model, ELTSeq handles individual heterogeneity by estimating an empirical probability for each observation without making any assumption about read-count distribution. It also incorporates a constraint for the read-count overdispersion, which is widely observed in RNA-seq data. ELTSeq demonstrates a significant improvement over existing methods such as edgeR, DESeq, t-tests, Wilcoxon tests and the classic empirical likelihood-ratio test when handling heterogeneous groups. It will significantly advance the transcriptomics studies of cancers and other complex disease. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Modular method of detection, localization, and counting of multiple-taxon pollen apertures using bag-of-words

NASA Astrophysics Data System (ADS)

Lozano-Vega, Gildardo; Benezeth, Yannick; Marzani, Franck; Boochs, Frank

2014-09-01

Accurate recognition of airborne pollen taxa is crucial for understanding and treating allergic diseases which affect an important proportion of the world population. Modern computer vision techniques enable the detection of discriminant characteristics. Apertures are among the important characteristics which have not been adequately explored until now. A flexible method of detection, localization, and counting of apertures of different pollen taxa with varying appearances is proposed. Aperture description is based on primitive images following the bag-of-words strategy. A confidence map is estimated based on the classification of sampled regions. The method is designed to be extended modularly to new aperture types employing the same algorithm by building individual classifiers. The method was evaluated on the top five allergenic pollen taxa in Germany, and its robustness to unseen particles was verified.

MerCat: a versatile k-mer counter and diversity estimator for database-independent property analysis obtained from metagenomic and/or metatranscriptomic sequencing data

DOE Office of Scientific and Technical Information (OSTI.GOV)

White, Richard A.; Panyala, Ajay R.; Glass, Kevin A.

MerCat is a parallel, highly scalable and modular property software package for robust analysis of features in next-generation sequencing data. MerCat inputs include assembled contigs and raw sequence reads from any platform resulting in feature abundance counts tables. MerCat allows for direct analysis of data properties without reference sequence database dependency commonly used by search tools such as BLAST and/or DIAMOND for compositional analysis of whole community shotgun sequencing (e.g. metagenomes and metatranscriptomes).

Deep 3 GHz number counts from a P(D) fluctuation analysis

NASA Astrophysics Data System (ADS)

Vernstrom, T.; Scott, Douglas; Wall, J. V.; Condon, J. J.; Cotton, W. D.; Fomalont, E. B.; Kellermann, K. I.; Miller, N.; Perley, R. A.

2014-05-01

Radio source counts constrain galaxy populations and evolution, as well as the global star formation history. However, there is considerable disagreement among the published 1.4-GHz source counts below 100 μJy. Here, we present a statistical method for estimating the μJy and even sub-μJy source count using new deep wide-band 3-GHz data in the Lockman Hole from the Karl G. Jansky Very Large Array. We analysed the confusion amplitude distribution P(D), which provides a fresh approach in the form of a more robust model, with a comprehensive error analysis. We tested this method on a large-scale simulation, incorporating clustering and finite source sizes. We discuss in detail our statistical methods for fitting using Markov chain Monte Carlo, handling correlations, and systematic errors from the use of wide-band radio interferometric data. We demonstrated that the source count can be constrained down to 50 nJy, a factor of 20 below the rms confusion. We found the differential source count near 10 μJy to have a slope of -1.7, decreasing to about -1.4 at fainter flux densities. At 3 GHz, the rms confusion in an 8-arcsec full width at half-maximum beam is ˜ 1.2 μJy beam-1, and a radio background temperature ˜14 mK. Our counts are broadly consistent with published evolutionary models. With these results, we were also able to constrain the peak of the Euclidean normalized differential source count of any possible new radio populations that would contribute to the cosmic radio background down to 50 nJy.

A novel approach to estimation of the time to biomarker threshold: applications to HIV.

PubMed

Reddy, Tarylee; Molenberghs, Geert; Njagi, Edmund Njeru; Aerts, Marc

2016-11-01

In longitudinal studies of biomarkers, an outcome of interest is the time at which a biomarker reaches a particular threshold. The CD4 count is a widely used marker of human immunodeficiency virus progression. Because of the inherent variability of this marker, a single CD4 count below a relevant threshold should be interpreted with caution. Several studies have applied persistence criteria, designating the outcome as the time to the occurrence of two consecutive measurements less than the threshold. In this paper, we propose a method to estimate the time to attainment of two consecutive CD4 counts less than a meaningful threshold, which takes into account the patient-specific trajectory and measurement error. An expression for the expected time to threshold is presented, which is a function of the fixed effects, random effects and residual variance. We present an application to human immunodeficiency virus-positive individuals from a seroprevalent cohort in Durban, South Africa. Two thresholds are examined, and 95% bootstrap confidence intervals are presented for the estimated time to threshold. Sensitivity analysis revealed that results are robust to truncation of the series and variation in the number of visits considered for most patients. Caution should be exercised when interpreting the estimated times for patients who exhibit very slow rates of decline and patients who have less than three measurements. We also discuss the relevance of the methodology to the study of other diseases and present such applications. We demonstrate that the method proposed is computationally efficient and offers more flexibility than existing frameworks. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Temporal and spatial binning of TCSPC data to improve signal-to-noise ratio and imaging speed

NASA Astrophysics Data System (ADS)

Walsh, Alex J.; Beier, Hope T.

2016-03-01

Time-correlated single photon counting (TCSPC) is the most robust method for fluorescence lifetime imaging using laser scanning microscopes. However, TCSPC is inherently slow making it ineffective to capture rapid events due to the single photon product per laser pulse causing extensive acquisition time limitations and the requirement of low fluorescence emission efficiency to avoid bias of measurement towards short lifetimes. Furthermore, thousands of photons per pixel are required for traditional instrument response deconvolution and fluorescence lifetime exponential decay estimation. Instrument response deconvolution and fluorescence exponential decay estimation can be performed in several ways including iterative least squares minimization and Laguerre deconvolution. This paper compares the limitations and accuracy of these fluorescence decay analysis techniques to accurately estimate double exponential decays across many data characteristics including various lifetime values, lifetime component weights, signal-to-noise ratios, and number of photons detected. Furthermore, techniques to improve data fitting, including binning data temporally and spatially, are evaluated as methods to improve decay fits and reduce image acquisition time. Simulation results demonstrate that binning temporally to 36 or 42 time bins, improves accuracy of fits for low photon count data. Such a technique reduces the required number of photons for accurate component estimation if lifetime values are known, such as for commercial fluorescent dyes and FRET experiments, and improve imaging speed 10-fold.

A comparison of charcoal measurements for reconstruction of Mediterranean paleo-fire frequency in the mountains of Corsica

NASA Astrophysics Data System (ADS)

Leys, Bérangère; Carcaillet, Christopher; Dezileau, Laurent; Ali, Adam A.; Bradshaw, Richard H. W.

2013-05-01

Fire-history reconstructions inferred from sedimentary charcoal records are based on measuring sieved charcoal fragment area, estimating fragment volume, or counting fragments. Similar fire histories are reconstructed from these three approaches for boreal lake sediment cores, using locally defined thresholds. Here, we test the same approach for a montane Mediterranean lake in which taphonomical processes might differ from boreal lakes through fragmentation of charcoal particles. The Mediterranean charcoal series are characterized by highly variable charcoal accumulation rates. Results there indicate that the three proxies do not provide comparable fire histories. The differences are attributable to charcoal fragmentation. This could be linked to fire type (crown or surface fires) or taphonomical processes, including charcoal transportation in the catchment area or in the sediment. The lack of correlation between the concentration of charcoal and of mineral matter suggests that fragmentation is not linked to erosion. Reconstructions based on charcoal area are more robust and stable than those based on fragment counts. Area-based reconstructions should therefore be used instead of the particle-counting method when fragmentation may influence the fragment abundance.

Robust x-ray based material identification using multi-energy sinogram decomposition

NASA Astrophysics Data System (ADS)

Yuan, Yaoshen; Tracey, Brian; Miller, Eric

2016-05-01

There is growing interest in developing X-ray computed tomography (CT) imaging systems with improved ability to discriminate material types, going beyond the attenuation imaging provided by most current systems. Dual- energy CT (DECT) systems can partially address this problem by estimating Compton and photoelectric (PE) coefficients of the materials being imaged, but DECT is greatly degraded by the presence of metal or other materials with high attenuation. Here we explore the advantages of multi-energy CT (MECT) systems based on photon-counting detectors. The utility of MECT has been demonstrated in medical applications where photon- counting detectors allow for the resolution of absorption K-edges. Our primary concern is aviation security applications where K-edges are rare. We simulate phantoms with differing amounts of metal (high, medium and low attenuation), both for switched-source DECT and for MECT systems, and include a realistic model of detector energy 0 resolution. We extend the DECT sinogram decomposition method of Ying et al. to MECT, allowing estimation of separate Compton and photoelectric sinograms. We furthermore introduce a weighting based on a quadratic approximation to the Poisson likelihood function that deemphasizes energy bins with low signal. Simulation results show that the proposed approach succeeds in estimating material properties even in high-attenuation scenarios where the DECT method fails, improving the signal to noise ratio of reconstructions by over 20 dB for the high-attenuation phantom. Our work demonstrates the potential of using photon counting detectors for stably recovering material properties even when high attenuation is present, thus enabling the development of improved scanning systems.

An evaluation of the Bayesian approach to fitting the N-mixture model for use with pseudo-replicated count data

USGS Publications Warehouse

Toribo, S.G.; Gray, B.R.; Liang, S.

2011-01-01

The N-mixture model proposed by Royle in 2004 may be used to approximate the abundance and detection probability of animal species in a given region. In 2006, Royle and Dorazio discussed the advantages of using a Bayesian approach in modelling animal abundance and occurrence using a hierarchical N-mixture model. N-mixture models assume replication on sampling sites, an assumption that may be violated when the site is not closed to changes in abundance during the survey period or when nominal replicates are defined spatially. In this paper, we studied the robustness of a Bayesian approach to fitting the N-mixture model for pseudo-replicated count data. Our simulation results showed that the Bayesian estimates for abundance and detection probability are slightly biased when the actual detection probability is small and are sensitive to the presence of extra variability within local sites.

HYPOTHESIS SETTING AND ORDER STATISTIC FOR ROBUST GENOMIC META-ANALYSIS.

PubMed

Song, Chi; Tseng, George C

2014-01-01

Meta-analysis techniques have been widely developed and applied in genomic applications, especially for combining multiple transcriptomic studies. In this paper, we propose an order statistic of p-values ( r th ordered p-value, rOP) across combined studies as the test statistic. We illustrate different hypothesis settings that detect gene markers differentially expressed (DE) "in all studies", "in the majority of studies", or "in one or more studies", and specify rOP as a suitable method for detecting DE genes "in the majority of studies". We develop methods to estimate the parameter r in rOP for real applications. Statistical properties such as its asymptotic behavior and a one-sided testing correction for detecting markers of concordant expression changes are explored. Power calculation and simulation show better performance of rOP compared to classical Fisher's method, Stouffer's method, minimum p-value method and maximum p-value method under the focused hypothesis setting. Theoretically, rOP is found connected to the naïve vote counting method and can be viewed as a generalized form of vote counting with better statistical properties. The method is applied to three microarray meta-analysis examples including major depressive disorder, brain cancer and diabetes. The results demonstrate rOP as a more generalizable, robust and sensitive statistical framework to detect disease-related markers.

The XMM Cluster Survey: X-ray analysis methodology

NASA Astrophysics Data System (ADS)

Lloyd-Davies, E. J.; Romer, A. Kathy; Mehrtens, Nicola; Hosmer, Mark; Davidson, Michael; Sabirli, Kivanc; Mann, Robert G.; Hilton, Matt; Liddle, Andrew R.; Viana, Pedro T. P.; Campbell, Heather C.; Collins, Chris A.; Dubois, E. Naomi; Freeman, Peter; Harrison, Craig D.; Hoyle, Ben; Kay, Scott T.; Kuwertz, Emma; Miller, Christopher J.; Nichol, Robert C.; Sahlén, Martin; Stanford, S. A.; Stott, John P.

2011-11-01

The XMM Cluster Survey (XCS) is a serendipitous search for galaxy clusters using all publicly available data in the XMM-Newton Science Archive. Its main aims are to measure cosmological parameters and trace the evolution of X-ray scaling relations. In this paper we describe the data processing methodology applied to the 5776 XMM observations used to construct the current XCS source catalogue. A total of 3675 > 4σ cluster candidates with >50 background-subtracted X-ray counts are extracted from a total non-overlapping area suitable for cluster searching of 410 deg2. Of these, 993 candidates are detected with >300 background-subtracted X-ray photon counts, and we demonstrate that robust temperature measurements can be obtained down to this count limit. We describe in detail the automated pipelines used to perform the spectral and surface brightness fitting for these candidates, as well as to estimate redshifts from the X-ray data alone. A total of 587 (122) X-ray temperatures to a typical accuracy of <40 (<10) per cent have been measured to date. We also present the methodology adopted for determining the selection function of the survey, and show that the extended source detection algorithm is robust to a range of cluster morphologies by inserting mock clusters derived from hydrodynamical simulations into real XMMimages. These tests show that the simple isothermal β-profiles is sufficient to capture the essential details of the cluster population detected in the archival XMM observations. The redshift follow-up of the XCS cluster sample is presented in a companion paper, together with a first data release of 503 optically confirmed clusters.

Estimating population diversity with CatchAll

PubMed Central

Bunge, John; Woodard, Linda; Böhning, Dankmar; Foster, James A.; Connolly, Sean; Allen, Heather K.

2012-01-01

Motivation: The massive data produced by next-generation sequencing require advanced statistical tools. We address estimating the total diversity or species richness in a population. To date, only relatively simple methods have been implemented in available software. There is a need for software employing modern, computationally intensive statistical analyses including error, goodness-of-fit and robustness assessments. Results: We present CatchAll, a fast, easy-to-use, platform-independent program that computes maximum likelihood estimates for finite-mixture models, weighted linear regression-based analyses and coverage-based non-parametric methods, along with outlier diagnostics. Given sample ‘frequency count’ data, CatchAll computes 12 different diversity estimates and applies a model-selection algorithm. CatchAll also derives discounted diversity estimates to adjust for possibly uncertain low-frequency counts. It is accompanied by an Excel-based graphics program. Availability: Free executable downloads for Linux, Windows and Mac OS, with manual and source code, at www.northeastern.edu/catchall. Contact: jab18@cornell.edu PMID:22333246

Aerial Surveys Give New Estimates for Orangutans in Sabah, Malaysia

PubMed Central

Gimenez, Olivier; Ambu, Laurentius; Ancrenaz, Karine; Andau, Patrick; Goossens, Benoît; Payne, John; Sawang, Azri; Tuuga, Augustine; Lackman-Ancrenaz, Isabelle

2005-01-01

Great apes are threatened with extinction, but precise information about the distribution and size of most populations is currently lacking. We conducted orangutan nest counts in the Malaysian state of Sabah (North Borneo), using a combination of ground and helicopter surveys, and provided a way to estimate the current distribution and size of the populations living throughout the entire state. We show that the number of nests detected during aerial surveys is directly related to the estimated true animal density and that a helicopter is an efficient tool to provide robust estimates of orangutan numbers. Our results reveal that with a total estimated population size of about 11,000 individuals, Sabah is one of the main strongholds for orangutans in North Borneo. More than 60% of orangutans living in the state occur outside protected areas, in production forests that have been through several rounds of logging extraction and are still exploited for timber. The role of exploited forests clearly merits further investigation for orangutan conservation in Sabah. PMID:15630475

Long-term exposure to ambient particulate matter (PM2.5) is associated with platelet counts in adults.

PubMed

Zhang, Zilong; Chan, Ta-Chien; Guo, Cui; Chang, Ly-Yun; Lin, Changqing; Chuang, Yuan Chieh; Jiang, Wun Kai; Ho, Kin Fai; Tam, Tony; Woo, Kam S; Lau, Alexis K H; Lao, Xiang Qian

2018-05-09

The prothrombotic effects of particulate matter (PM) may underlie the association of air pollution with increased risks of cardiovascular disease. This study aimed to investigate the association between long-term exposure to PM with an aerodynamic diameter ≤2.5 μm (PM 2.5 ) and platelet counts, a marker of coagulation profiles. The study participants were from a cohort consisting of 362,396 Taiwanese adults who participated in a standard medical examination program between 2001 and 2014. Platelet counts were measured through Complete Blood Count tests. A satellite-based spatio-temporal model was used to estimate 2-year average ambient PM 2.5 concentration at each participant's address. Mixed-effects linear regression models were used to investigate the association between PM 2.5 exposure and platelet counts. This analysis included 175,959 men with 396,248 observations and 186,437 women with 397,877 observations. Every 10-μg/m 3 increment in the 2-year average PM 2.5 was associated with increases of 0.42% (95% CI: 0.38%, 0.47%) and 0.49% (95% CI: 0.44%, 0.54%) in platelet counts in men and women, respectively. A series of sensitivity analyses, including an analysis in participants free of cardiometabolic disorders, confirmed the robustness of the observed associations. Baseline data analyses showed that every 10-μg/m 3 increment in PM 2.5 was associated with higher risk of 17% and 14% of having elevated platelet counts (≥90th percentile) in men and women, respectively. Long-term exposure to PM 2.5 appears to be associated with increased platelet counts, indicating potential adverse effects on blood coagulability. Copyright © 2018 Elsevier Ltd. All rights reserved.

Use of portable antennas to estimate abundance of PIT-tagged fish in small streams: Factors affecting detection probability

USGS Publications Warehouse

O'Donnell, Matthew J.; Horton, Gregg E.; Letcher, Benjamin H.

2010-01-01

Portable passive integrated transponder (PIT) tag antenna systems can be valuable in providing reliable estimates of the abundance of tagged Atlantic salmon Salmo salar in small streams under a wide range of conditions. We developed and employed PIT tag antenna wand techniques in two controlled experiments and an additional case study to examine the factors that influenced our ability to estimate population size. We used Pollock's robust-design capture–mark–recapture model to obtain estimates of the probability of first detection (p), the probability of redetection (c), and abundance (N) in the two controlled experiments. First, we conducted an experiment in which tags were hidden in fixed locations. Although p and c varied among the three observers and among the three passes that each observer conducted, the estimates of N were identical to the true values and did not vary among observers. In the second experiment using free-swimming tagged fish, p and c varied among passes and time of day. Additionally, estimates of N varied between day and night and among age-classes but were within 10% of the true population size. In the case study, we used the Cormack–Jolly–Seber model to examine the variation in p, and we compared counts of tagged fish found with the antenna wand with counts collected via electrofishing. In that study, we found that although p varied for age-classes, sample dates, and time of day, antenna and electrofishing estimates of N were similar, indicating that population size can be reliably estimated via PIT tag antenna wands. However, factors such as the observer, time of day, age of fish, and stream discharge can influence the initial and subsequent detection probabilities.

A video-based real-time adaptive vehicle-counting system for urban roads.

PubMed

Liu, Fei; Zeng, Zhiyuan; Jiang, Rong

2017-01-01

In developing nations, many expanding cities are facing challenges that result from the overwhelming numbers of people and vehicles. Collecting real-time, reliable and precise traffic flow information is crucial for urban traffic management. The main purpose of this paper is to develop an adaptive model that can assess the real-time vehicle counts on urban roads using computer vision technologies. This paper proposes an automatic real-time background update algorithm for vehicle detection and an adaptive pattern for vehicle counting based on the virtual loop and detection line methods. In addition, a new robust detection method is introduced to monitor the real-time traffic congestion state of road section. A prototype system has been developed and installed on an urban road for testing. The results show that the system is robust, with a real-time counting accuracy exceeding 99% in most field scenarios.

A video-based real-time adaptive vehicle-counting system for urban roads

PubMed Central

2017-01-01

In developing nations, many expanding cities are facing challenges that result from the overwhelming numbers of people and vehicles. Collecting real-time, reliable and precise traffic flow information is crucial for urban traffic management. The main purpose of this paper is to develop an adaptive model that can assess the real-time vehicle counts on urban roads using computer vision technologies. This paper proposes an automatic real-time background update algorithm for vehicle detection and an adaptive pattern for vehicle counting based on the virtual loop and detection line methods. In addition, a new robust detection method is introduced to monitor the real-time traffic congestion state of road section. A prototype system has been developed and installed on an urban road for testing. The results show that the system is robust, with a real-time counting accuracy exceeding 99% in most field scenarios. PMID:29135984

DOE Office of Scientific and Technical Information (OSTI.GOV)

Altmann, Yoann; Maccarone, Aurora; McCarthy, Aongus

Here, this paper presents a new Bayesian spectral un-mixing algorithm to analyse remote scenes sensed via sparse multispectral Lidar measurements. To a first approximation, in the presence of a target, each Lidar waveform consists of a main peak, whose position depends on the target distance and whose amplitude depends on the wavelength of the laser source considered (i.e, on the target reflectivity). Besides, these temporal responses are usually assumed to be corrupted by Poisson noise in the low photon count regime. When considering multiple wavelengths, it becomes possible to use spectral information in order to identify and quantify the mainmore » materials in the scene, in addition to estimation of the Lidar-based range profiles. Due to its anomaly detection capability, the proposed hierarchical Bayesian model, coupled with an efficient Markov chain Monte Carlo algorithm, allows robust estimation of depth images together with abundance and outlier maps associated with the observed 3D scene. The proposed methodology is illustrated via experiments conducted with real multispectral Lidar data acquired in a controlled environment. The results demonstrate the possibility to unmix spectral responses constructed from extremely sparse photon counts (less than 10 photons per pixel and band).« less

Direct reconstruction of parametric images for brain PET with event-by-event motion correction: evaluation in two tracers across count levels

NASA Astrophysics Data System (ADS)

Germino, Mary; Gallezot, Jean-Dominque; Yan, Jianhua; Carson, Richard E.

2017-07-01

Parametric images for dynamic positron emission tomography (PET) are typically generated by an indirect method, i.e. reconstructing a time series of emission images, then fitting a kinetic model to each voxel time activity curve. Alternatively, ‘direct reconstruction’, incorporates the kinetic model into the reconstruction algorithm itself, directly producing parametric images from projection data. Direct reconstruction has been shown to achieve parametric images with lower standard error than the indirect method. Here, we present direct reconstruction for brain PET using event-by-event motion correction of list-mode data, applied to two tracers. Event-by-event motion correction was implemented for direct reconstruction in the Parametric Motion-compensation OSEM List-mode Algorithm for Resolution-recovery reconstruction. The direct implementation was tested on simulated and human datasets with tracers [11C]AFM (serotonin transporter) and [11C]UCB-J (synaptic density), which follow the 1-tissue compartment model. Rigid head motion was tracked with the Vicra system. Parametric images of K 1 and distribution volume (V T  =  K 1/k 2) were compared to those generated by the indirect method by regional coefficient of variation (CoV). Performance across count levels was assessed using sub-sampled datasets. For simulated and real datasets at high counts, the two methods estimated K 1 and V T with comparable accuracy. At lower count levels, the direct method was substantially more robust to outliers than the indirect method. Compared to the indirect method, direct reconstruction reduced regional K 1 CoV by 35-48% (simulated dataset), 39-43% ([11C]AFM dataset) and 30-36% ([11C]UCB-J dataset) across count levels (averaged over regions at matched iteration); V T CoV was reduced by 51-58%, 54-60% and 30-46%, respectively. Motion correction played an important role in the dataset with larger motion: correction increased regional V T by 51% on average in the [11C]UCB-J dataset. Direct reconstruction of dynamic brain PET with event-by-event motion correction is achievable and dramatically more robust to noise in V T images than the indirect method.

Bike-Ped Portal : development of an online nonmotorized traffic count archive.

DOT National Transportation Integrated Search

2017-05-01

Robust bicycle and pedestrian data on a national scale would serve numerous purposes. Access to a centralized nonmotorized traffic count : archive can open the door for innovation through research, design and planning; provide safety researchers with...

QNB: differential RNA methylation analysis for count-based small-sample sequencing data with a quad-negative binomial model.

PubMed

Liu, Lian; Zhang, Shao-Wu; Huang, Yufei; Meng, Jia

2017-08-31

As a newly emerged research area, RNA epigenetics has drawn increasing attention recently for the participation of RNA methylation and other modifications in a number of crucial biological processes. Thanks to high throughput sequencing techniques, such as, MeRIP-Seq, transcriptome-wide RNA methylation profile is now available in the form of count-based data, with which it is often of interests to study the dynamics at epitranscriptomic layer. However, the sample size of RNA methylation experiment is usually very small due to its costs; and additionally, there usually exist a large number of genes whose methylation level cannot be accurately estimated due to their low expression level, making differential RNA methylation analysis a difficult task. We present QNB, a statistical approach for differential RNA methylation analysis with count-based small-sample sequencing data. Compared with previous approaches such as DRME model based on a statistical test covering the IP samples only with 2 negative binomial distributions, QNB is based on 4 independent negative binomial distributions with their variances and means linked by local regressions, and in the way, the input control samples are also properly taken care of. In addition, different from DRME approach, which relies only the input control sample only for estimating the background, QNB uses a more robust estimator for gene expression by combining information from both input and IP samples, which could largely improve the testing performance for very lowly expressed genes. QNB showed improved performance on both simulated and real MeRIP-Seq datasets when compared with competing algorithms. And the QNB model is also applicable to other datasets related RNA modifications, including but not limited to RNA bisulfite sequencing, m 1 A-Seq, Par-CLIP, RIP-Seq, etc.

A burst-mode photon counting receiver with automatic channel estimation and bit rate detection

NASA Astrophysics Data System (ADS)

Rao, Hemonth G.; DeVoe, Catherine E.; Fletcher, Andrew S.; Gaschits, Igor D.; Hakimi, Farhad; Hamilton, Scott A.; Hardy, Nicholas D.; Ingwersen, John G.; Kaminsky, Richard D.; Moores, John D.; Scheinbart, Marvin S.; Yarnall, Timothy M.

2016-04-01

We demonstrate a multi-rate burst-mode photon-counting receiver for undersea communication at data rates up to 10.416 Mb/s over a 30-foot water channel. To the best of our knowledge, this is the first demonstration of burst-mode photon-counting communication. With added attenuation, the maximum link loss is 97.1 dB at λ=517 nm. In clear ocean water, this equates to link distances up to 148 meters. For λ=470 nm, the achievable link distance in clear ocean water is 450 meters. The receiver incorporates soft-decision forward error correction (FEC) based on a product code of an inner LDPC code and an outer BCH code. The FEC supports multiple code rates to achieve error-free performance. We have selected a burst-mode receiver architecture to provide robust performance with respect to unpredictable channel obstructions. The receiver is capable of on-the-fly data rate detection and adapts to changing levels of signal and background light. The receiver updates its phase alignment and channel estimates every 1.6 ms, allowing for rapid changes in water quality as well as motion between transmitter and receiver. We demonstrate on-the-fly rate detection, channel BER within 0.2 dB of theory across all data rates, and error-free performance within 1.82 dB of soft-decision capacity across all tested code rates. All signal processing is done in FPGAs and runs continuously in real time.

Increased robustness of single-molecule counting with microfluidics, digital isothermal amplification, and a mobile phone versus real-time kinetic measurements.

PubMed

Selck, David A; Karymov, Mikhail A; Sun, Bing; Ismagilov, Rustem F

2013-11-19

Quantitative bioanalytical measurements are commonly performed in a kinetic format and are known to not be robust to perturbation that affects the kinetics itself or the measurement of kinetics. We hypothesized that the same measurements performed in a "digital" (single-molecule) format would show increased robustness to such perturbations. Here, we investigated the robustness of an amplification reaction (reverse-transcription loop-mediated amplification, RT-LAMP) in the context of fluctuations in temperature and time when this reaction is used for quantitative measurements of HIV-1 RNA molecules under limited-resource settings (LRS). The digital format that counts molecules using dRT-LAMP chemistry detected a 2-fold change in concentration of HIV-1 RNA despite a 6 °C temperature variation (p-value = 6.7 × 10(-7)), whereas the traditional kinetic (real-time) format did not (p-value = 0.25). Digital analysis was also robust to a 20 min change in reaction time, to poor imaging conditions obtained with a consumer cell-phone camera, and to automated cloud-based processing of these images (R(2) = 0.9997 vs true counts over a 100-fold dynamic range). Fluorescent output of multiplexed PCR amplification could also be imaged with the cell phone camera using flash as the excitation source. Many nonlinear amplification schemes based on organic, inorganic, and biochemical reactions have been developed, but their robustness is not well understood. This work implies that these chemistries may be significantly more robust in the digital, rather than kinetic, format. It also calls for theoretical studies to predict robustness of these chemistries and, more generally, to design robust reaction architectures. The SlipChip that we used here and other digital microfluidic technologies already exist to enable testing of these predictions. Such work may lead to identification or creation of robust amplification chemistries that enable rapid and precise quantitative molecular measurements under LRS. Furthermore, it may provide more general principles describing robustness of chemical and biological networks in digital formats.

Estimation of single-year-of-age counts of live births, fetal losses, abortions, and pregnant women for counties of Texas.

PubMed

Singh, Bismark; Meyers, Lauren Ancel

2017-05-08

We provide a methodology for estimating counts of single-year-of-age live-births, fetal-losses, abortions, and pregnant women from aggregated age-group counts. As a case study, we estimate counts for the 254 counties of Texas for the year 2010. We use interpolation to estimate counts of live-births, fetal-losses, and abortions by women of each single-year-of-age for all Texas counties. We then use these counts to estimate the numbers of pregnant women for each single-year-of-age, which were previously available only in aggregate. To support public health policy and planning, we provide single-year-of-age estimates of live-births, fetal-losses, abortions, and pregnant women for all Texas counties in the year 2010, as well as the estimation method source code.

Efficient Levenberg-Marquardt minimization of the maximum likelihood estimator for Poisson deviates

DOE Office of Scientific and Technical Information (OSTI.GOV)

Laurence, T; Chromy, B

2009-11-10

Histograms of counted events are Poisson distributed, but are typically fitted without justification using nonlinear least squares fitting. The more appropriate maximum likelihood estimator (MLE) for Poisson distributed data is seldom used. We extend the use of the Levenberg-Marquardt algorithm commonly used for nonlinear least squares minimization for use with the MLE for Poisson distributed data. In so doing, we remove any excuse for not using this more appropriate MLE. We demonstrate the use of the algorithm and the superior performance of the MLE using simulations and experiments in the context of fluorescence lifetime imaging. Scientists commonly form histograms ofmore » counted events from their data, and extract parameters by fitting to a specified model. Assuming that the probability of occurrence for each bin is small, event counts in the histogram bins will be distributed according to the Poisson distribution. We develop here an efficient algorithm for fitting event counting histograms using the maximum likelihood estimator (MLE) for Poisson distributed data, rather than the non-linear least squares measure. This algorithm is a simple extension of the common Levenberg-Marquardt (L-M) algorithm, is simple to implement, quick and robust. Fitting using a least squares measure is most common, but it is the maximum likelihood estimator only for Gaussian-distributed data. Non-linear least squares methods may be applied to event counting histograms in cases where the number of events is very large, so that the Poisson distribution is well approximated by a Gaussian. However, it is not easy to satisfy this criterion in practice - which requires a large number of events. It has been well-known for years that least squares procedures lead to biased results when applied to Poisson-distributed data; a recent paper providing extensive characterization of these biases in exponential fitting is given. The more appropriate measure based on the maximum likelihood estimator (MLE) for the Poisson distribution is also well known, but has not become generally used. This is primarily because, in contrast to non-linear least squares fitting, there has been no quick, robust, and general fitting method. In the field of fluorescence lifetime spectroscopy and imaging, there have been some efforts to use this estimator through minimization routines such as Nelder-Mead optimization, exhaustive line searches, and Gauss-Newton minimization. Minimization based on specific one- or multi-exponential models has been used to obtain quick results, but this procedure does not allow the incorporation of the instrument response, and is not generally applicable to models found in other fields. Methods for using the MLE for Poisson-distributed data have been published by the wider spectroscopic community, including iterative minimization schemes based on Gauss-Newton minimization. The slow acceptance of these procedures for fitting event counting histograms may also be explained by the use of the ubiquitous, fast Levenberg-Marquardt (L-M) fitting procedure for fitting non-linear models using least squares fitting (simple searches obtain {approx}10000 references - this doesn't include those who use it, but don't know they are using it). The benefits of L-M include a seamless transition between Gauss-Newton minimization and downward gradient minimization through the use of a regularization parameter. This transition is desirable because Gauss-Newton methods converge quickly, but only within a limited domain of convergence; on the other hand the downward gradient methods have a much wider domain of convergence, but converge extremely slowly nearer the minimum. L-M has the advantages of both procedures: relative insensitivity to initial parameters and rapid convergence. Scientists, when wanting an answer quickly, will fit data using L-M, get an answer, and move on. Only those that are aware of the bias issues will bother to fit using the more appropriate MLE for Poisson deviates. However, since there is a simple, analytical formula for the appropriate MLE measure for Poisson deviates, it is inexcusable that least squares estimators are used almost exclusively when fitting event counting histograms. There have been ways found to use successive non-linear least squares fitting to obtain similarly unbiased results, but this procedure is justified by simulation, must be re-tested when conditions change significantly, and requires two successive fits. There is a great need for a fitting routine for the MLE estimator for Poisson deviates that has convergence domains and rates comparable to the non-linear least squares L-M fitting. We show in this report that a simple way to achieve that goal is to use the L-M fitting procedure not to minimize the least squares measure, but the MLE for Poisson deviates.« less

Variable selection for distribution-free models for longitudinal zero-inflated count responses.

PubMed

Chen, Tian; Wu, Pan; Tang, Wan; Zhang, Hui; Feng, Changyong; Kowalski, Jeanne; Tu, Xin M

2016-07-20

Zero-inflated count outcomes arise quite often in research and practice. Parametric models such as the zero-inflated Poisson and zero-inflated negative binomial are widely used to model such responses. Like most parametric models, they are quite sensitive to departures from assumed distributions. Recently, new approaches have been proposed to provide distribution-free, or semi-parametric, alternatives. These methods extend the generalized estimating equations to provide robust inference for population mixtures defined by zero-inflated count outcomes. In this paper, we propose methods to extend smoothly clipped absolute deviation (SCAD)-based variable selection methods to these new models. Variable selection has been gaining popularity in modern clinical research studies, as determining differential treatment effects of interventions for different subgroups has become the norm, rather the exception, in the era of patent-centered outcome research. Such moderation analysis in general creates many explanatory variables in regression analysis, and the advantages of SCAD-based methods over their traditional counterparts render them a great choice for addressing this important and timely issues in clinical research. We illustrate the proposed approach with both simulated and real study data. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Validation of a Cytotechnologist Manual Counting Service for the Ki67 Index in Neuroendocrine Tumors of the Pancreas and Gastrointestinal Tract.

PubMed

Cottenden, Jennielee; Filter, Emily R; Cottreau, Jon; Moore, David; Bullock, Martin; Huang, Weei-Yuarn; Arnason, Thomas

2018-03-01

- Pathologists routinely assess Ki67 immunohistochemistry to grade gastrointestinal and pancreatic neuroendocrine tumors. Unfortunately, manual counts of the Ki67 index are very time consuming and eyeball estimation has been criticized as unreliable. Manual Ki67 counts performed by cytotechnologists could potentially save pathologist time and improve accuracy. - To assess the concordance between manual Ki67 index counts performed by cytotechnologists versus eyeball estimates and manual Ki67 counts by pathologists. - One Ki67 immunohistochemical stain was retrieved from each of 18 archived gastrointestinal or pancreatic neuroendocrine tumor resections. We compared pathologists' Ki67 eyeball estimates on glass slides and printed color images with manual counts performed by 3 cytotechnologists and gold standard manual Ki67 index counts by 3 pathologists. - Tumor grade agreement between pathologist image eyeball estimate and gold standard pathologist manual count was fair (κ = 0.31; 95% CI, 0.030-0.60). In 9 of 20 cases (45%), the mean pathologist eyeball estimate was 1 grade higher than the mean pathologist manual count. There was almost perfect agreement in classifying tumor grade between the mean cytotechnologist manual count and the mean pathologist manual count (κ = 0.910; 95% CI, 0.697-1.00). In 20 cases, there was only 1 grade disagreement between the 2 methods. Eyeball estimation by pathologists required less than 1 minute, whereas manual counts by pathologists required a mean of 17 minutes per case. - Eyeball estimation of the Ki67 index has a high rate of tumor grade misclassification compared with manual counting. Cytotechnologist manual counts are accurate and save pathologist time.

Effects of lek count protocols on greater sage-grouse population trend estimates

USGS Publications Warehouse

Monroe, Adrian; Edmunds, David; Aldridge, Cameron L.

2016-01-01

Annual counts of males displaying at lek sites are an important tool for monitoring greater sage-grouse populations (Centrocercus urophasianus), but seasonal and diurnal variation in lek attendance may increase variance and bias of trend analyses. Recommendations for protocols to reduce observation error have called for restricting lek counts to within 30 minutes of sunrise, but this may limit the number of lek counts available for analysis, particularly from years before monitoring was widely standardized. Reducing the temporal window for conducting lek counts also may constrain the ability of agencies to monitor leks efficiently. We used lek count data collected across Wyoming during 1995−2014 to investigate the effect of lek counts conducted between 30 minutes before and 30, 60, or 90 minutes after sunrise on population trend estimates. We also evaluated trends across scales relevant to management, including statewide, within Working Group Areas and Core Areas, and for individual leks. To further evaluate accuracy and precision of trend estimates from lek count protocols, we used simulations based on a lek attendance model and compared simulated and estimated values of annual rate of change in population size (λ) from scenarios of varying numbers of leks, lek count timing, and count frequency (counts/lek/year). We found that restricting analyses to counts conducted within 30 minutes of sunrise generally did not improve precision of population trend estimates, although differences among timings increased as the number of leks and count frequency decreased. Lek attendance declined >30 minutes after sunrise, but simulations indicated that including lek counts conducted up to 90 minutes after sunrise can increase the number of leks monitored compared to trend estimates based on counts conducted within 30 minutes of sunrise. This increase in leks monitored resulted in greater precision of estimates without reducing accuracy. Increasing count frequency also improved precision. These results suggest that the current distribution of count timings available in lek count databases such as that of Wyoming (conducted up to 90 minutes after sunrise) can be used to estimate sage-grouse population trends without reducing precision or accuracy relative to trends from counts conducted within 30 minutes of sunrise. However, only 10% of all Wyoming counts in our sample (1995−2014) were conducted 61−90 minutes after sunrise, and further increasing this percentage may still bias trend estimates because of declining lek attendance. 

Abundance models improve spatial and temporal prioritization of conservation resources.

PubMed

Johnston, Alison; Fink, Daniel; Reynolds, Mark D; Hochachka, Wesley M; Sullivan, Brian L; Bruns, Nicholas E; Hallstein, Eric; Merrifield, Matt S; Matsumoto, Sandi; Kelling, Steve

2015-10-01

Conservation prioritization requires knowledge about organism distribution and density. This information is often inferred from models that estimate the probability of species occurrence rather than from models that estimate species abundance, because abundance data are harder to obtain and model. However, occurrence and abundance may not display similar patterns and therefore development of robust, scalable, abundance models is critical to ensuring that scarce conservation resources are applied where they can have the greatest benefits. Motivated by a dynamic land conservation program, we develop and assess a general method for modeling relative abundance using citizen science monitoring data. Weekly estimates of relative abundance and occurrence were compared for prioritizing times and locations of conservation actions for migratory waterbird species in California, USA. We found that abundance estimates consistently provided better rankings of observed counts than occurrence estimates. Additionally, the relationship between abundance and occurrence was nonlinear and varied by species and season. Across species, locations prioritized by occurrence models had only 10-58% overlap with locations prioritized by abundance models, highlighting that occurrence models will not typically identify the locations of highest abundance that are vital for conservation of populations.

Key issues in the quality assurance of the One Number Census.

PubMed

Diamond, Ian; Abbott, Owen; Jackson, Neil

2003-01-01

As part of the 2001 Census, the One Number Census project estimated and adjusted the Census database for underenumeration. As a result of the highly innovative One Number Census and the Quality Assurance process it encompassed, it was also ensured that robust results could be obtained for each local authority area. This article examines some of the issues and analyses that were undertaken as part of that assessment of the 2001 Census population counts for England and Wales. The article firstly highlights the key issues surrounding the implementation of the 2001 Census fieldwork. The article then explores the 2001 Census results through a series of demographic analyses to illustrate the sorts of issues investigated during the One Number Census Quality Assurance process itself. These analyses look at the patterns contained within the results, and comparisons with key alternative sources of population counts. Overall, these in-depth analyses and investigations provide further credence to the plausibility of the One Number Census results.

Robust estimation of fractal measures for characterizing the structural complexity of the human brain: optimization and reproducibility

PubMed Central

Goñi, Joaquín; Sporns, Olaf; Cheng, Hu; Aznárez-Sanado, Maite; Wang, Yang; Josa, Santiago; Arrondo, Gonzalo; Mathews, Vincent P; Hummer, Tom A; Kronenberger, William G; Avena-Koenigsberger, Andrea; Saykin, Andrew J.; Pastor, María A.

2013-01-01

High-resolution isotropic three-dimensional reconstructions of human brain gray and white matter structures can be characterized to quantify aspects of their shape, volume and topological complexity. In particular, methods based on fractal analysis have been applied in neuroimaging studies to quantify the structural complexity of the brain in both healthy and impaired conditions. The usefulness of such measures for characterizing individual differences in brain structure critically depends on their within-subject reproducibility in order to allow the robust detection of between-subject differences. This study analyzes key analytic parameters of three fractal-based methods that rely on the box-counting algorithm with the aim to maximize within-subject reproducibility of the fractal characterizations of different brain objects, including the pial surface, the cortical ribbon volume, the white matter volume and the grey matter/white matter boundary. Two separate datasets originating from different imaging centers were analyzed, comprising, 50 subjects with three and 24 subjects with four successive scanning sessions per subject, respectively. The reproducibility of fractal measures was statistically assessed by computing their intra-class correlations. Results reveal differences between different fractal estimators and allow the identification of several parameters that are critical for high reproducibility. Highest reproducibility with intra-class correlations in the range of 0.9–0.95 is achieved with the correlation dimension. Further analyses of the fractal dimensions of parcellated cortical and subcortical gray matter regions suggest robustly estimated and region-specific patterns of individual variability. These results are valuable for defining appropriate parameter configurations when studying changes in fractal descriptors of human brain structure, for instance in studies of neurological diseases that do not allow repeated measurements or for disease-course longitudinal studies. PMID:23831414

Can cover data be used as a surrogate for seedling counts in regeneration stocking evaluations in northern hardwood forests?

Treesearch

Todd E. Ristau; Susan L. Stout

2014-01-01

Assessment of regeneration can be time-consuming and costly. Often, foresters look for ways to minimize the cost of doing inventories. One potential method to reduce time required on a plot is use of percent cover data rather than seedling count data to determine stocking. Robust linear regression analysis was used in this report to predict seedling count data from...

The Foraging Ecology of Royal and Sandwich Terns in North Carolina, USA

USGS Publications Warehouse

McGinnis, T.W.; Emslie, S.D.

2001-01-01

Population sizes of territorial male red-winged blackbirds (Agelaius phoeniceus) were determined with counts of territorial males (area count) and a Petersen-Lincoln Index method for roadsides (roadside estimate). Weather conditions and time of day did not influence either method. Combined roadside estimates had smaller error bounds than the individual transect estimates and were not hindered by the problem of zero recaptures. Roadside estimates were usually one-half as large as the area counts, presumably due to an observer bias for marked birds. The roadside estimate provides only an index of major changes in populations of territorial male redwings. When the roadside estimate is employed, the area count should be used to determine the amount and nature of observer bias. For small population surveys, the area count is probably more reliable and accurate than the roadside estimate.

Determining population size of territorial red-winged blackbirds

USGS Publications Warehouse

Albers, P.H.

1976-01-01

Population sizes of territorial male red-winged blackbirds (Agelaius phoeniceus) were determined with counts of territorial males (area count) and a Petersen-Lincoln Index method for roadsides (roadside estimate). Weather conditions and time of day did not influence either method. Combined roadside estimates had smaller error bounds than the individual transect estimates and were not hindered by the problem of zero recaptures. Roadside estimates were usually one-half as large as the area counts, presumably due to an observer bias for marked birds. The roadside estimate provides only an index of major changes in populations of territorial male redwings. When the roadside estimate is employed, the area count should be used to determine the amount and nature of observer bias. For small population surveys, the area count is probably more reliable and accurate than the roadside estimate.

A computerized recognition system for the home-based physiotherapy exercises using an RGBD camera.

PubMed

Ar, Ilktan; Akgul, Yusuf Sinan

2014-11-01

Computerized recognition of the home based physiotherapy exercises has many benefits and it has attracted considerable interest among the computer vision community. However, most methods in the literature view this task as a special case of motion recognition. In contrast, we propose to employ the three main components of a physiotherapy exercise (the motion patterns, the stance knowledge, and the exercise object) as different recognition tasks and embed them separately into the recognition system. The low level information about each component is gathered using machine learning methods. Then, we use a generative Bayesian network to recognize the exercise types by combining the information from these sources at an abstract level, which takes the advantage of domain knowledge for a more robust system. Finally, a novel postprocessing step is employed to estimate the exercise repetitions counts. The performance evaluation of the system is conducted with a new dataset which contains RGB (red, green, and blue) and depth videos of home-based exercise sessions for commonly applied shoulder and knee exercises. The proposed system works without any body-part segmentation, bodypart tracking, joint detection, and temporal segmentation methods. In the end, favorable exercise recognition rates and encouraging results on the estimation of repetition counts are obtained.

Short range shooting distance estimation using variable pressure SEM images of the surroundings of bullet holes in textiles.

PubMed

Hinrichs, Ruth; Frank, Paulo Ricardo Ost; Vasconcellos, M A Z

2017-03-01

Modifications of cotton and polyester textiles due to shots fired at short range were analyzed with a variable pressure scanning electron microscope (VP-SEM). Different mechanisms of fiber rupture as a function of fiber type and shooting distance were detected, namely fusing, melting, scorching, and mechanical breakage. To estimate the firing distance, the approximately exponential decay of GSR coverage as a function of radial distance from the entrance hole was determined from image analysis, instead of relying on chemical analysis with EDX, which is problematic in the VP-SEM. A set of backscattered electron images, with sufficient magnification to discriminate micrometer wide GSR particles, was acquired at different radial distances from the entrance hole. The atomic number contrast between the GSR particles and the organic fibers allowed to find a robust procedure to segment the micrographs into binary images, in which the white pixel count was attributed to GSR coverage. The decrease of the white pixel count followed an exponential decay, and it was found that the reciprocal of the decay constant, obtained from the least-square fitting of the coverage data, showed a linear dependence on the shooting distance. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Google Haul Out: Earth Observation Imagery and Digital Aerial Surveys in Coastal Wildlife Management and Abundance Estimation

PubMed Central

Moxley, Jerry H.; Bogomolni, Andrea; Hammill, Mike O.; Moore, Kathleen M. T.; Polito, Michael J.; Sette, Lisa; Sharp, W. Brian; Waring, Gordon T.; Gilbert, James R.; Halpin, Patrick N.; Johnston, David W.

2017-01-01

Abstract As the sampling frequency and resolution of Earth observation imagery increase, there are growing opportunities for novel applications in population monitoring. New methods are required to apply established analytical approaches to data collected from new observation platforms (e.g., satellites and unmanned aerial vehicles). Here, we present a method that estimates regional seasonal abundances for an understudied and growing population of gray seals (Halichoerus grypus) in southeastern Massachusetts, using opportunistic observations in Google Earth imagery. Abundance estimates are derived from digital aerial survey counts by adapting established correction-based analyses with telemetry behavioral observation to quantify survey biases. The result is a first regional understanding of gray seal abundance in the northeast US through opportunistic Earth observation imagery and repurposed animal telemetry data. As species observation data from Earth observation imagery become more ubiquitous, such methods provide a robust, adaptable, and cost-effective solution to monitoring animal colonies and understanding species abundances. PMID:29599542

Google Haul Out: Earth Observation Imagery and Digital Aerial Surveys in Coastal Wildlife Management and Abundance Estimation.

PubMed

Moxley, Jerry H; Bogomolni, Andrea; Hammill, Mike O; Moore, Kathleen M T; Polito, Michael J; Sette, Lisa; Sharp, W Brian; Waring, Gordon T; Gilbert, James R; Halpin, Patrick N; Johnston, David W

2017-08-01

As the sampling frequency and resolution of Earth observation imagery increase, there are growing opportunities for novel applications in population monitoring. New methods are required to apply established analytical approaches to data collected from new observation platforms (e.g., satellites and unmanned aerial vehicles). Here, we present a method that estimates regional seasonal abundances for an understudied and growing population of gray seals (Halichoerus grypus) in southeastern Massachusetts, using opportunistic observations in Google Earth imagery. Abundance estimates are derived from digital aerial survey counts by adapting established correction-based analyses with telemetry behavioral observation to quantify survey biases. The result is a first regional understanding of gray seal abundance in the northeast US through opportunistic Earth observation imagery and repurposed animal telemetry data. As species observation data from Earth observation imagery become more ubiquitous, such methods provide a robust, adaptable, and cost-effective solution to monitoring animal colonies and understanding species abundances.

Fresh Fuel Measurements With the Differential Die-Away Self-Interrogation Instrument

NASA Astrophysics Data System (ADS)

Trahan, Alexis C.; Belian, Anthony P.; Swinhoe, Martyn T.; Menlove, Howard O.; Flaska, Marek; Pozzi, Sara A.

2017-07-01

The purpose of the Next Generation Safeguards Initiative (NGSI)-Spent Fuel (SF) Project is to strengthen the technical toolkit of safeguards inspectors and/or other interested parties. The NGSI-SF team is working to achieve the following technical goals more easily and efficiently than in the past using nondestructive assay measurements of spent fuel assemblies: 1) verify the initial enrichment, burnup, and cooling time of facility declaration; 2) detect the diversion or replacement of pins; 3) estimate the plutonium mass; 4) estimate decay heat; and 5) determine the reactivity of spent fuel assemblies. The differential die-away self-interrogation (DDSI) instrument is one instrument that was assessed for years regarding its feasibility for robust, timely verification of spent fuel assemblies. The instrument was recently built and was tested using fresh fuel assemblies in a variety of configurations, including varying enrichment, neutron absorber content, and symmetry. The early die-away method, a multiplication determination method developed in simulation space, was successfully tested on the fresh fuel assembly data and determined multiplication with a root-mean-square (RMS) error of 2.9%. The experimental results were compared with MCNP simulations of the instrument as well. Low multiplication assemblies had agreement with an average RMS error of 0.2% in the singles count rate (i.e., total neutrons detected per second) and 3.4% in the doubles count rates (i.e., neutrons detected in coincidence per second). High-multiplication assemblies had agreement with an average RMS error of 4.1% in the singles and 13.3% in the doubles count rates.

Fresh Fuel Measurements With the Differential Die-Away Self-Interrogation Instrument

DOE Office of Scientific and Technical Information (OSTI.GOV)

Trahan, Alexis C.; Belian, Anthony P.; Swinhoe, Martyn T.

The purpose of the Next Generation Safeguards Initiative (NGSI)-Spent Fuel (SF) Project is to strengthen the technical toolkit of safeguards inspectors and/or other interested parties. Thus the NGSI-SF team is working to achieve the following technical goals more easily and efficiently than in the past using nondestructive assay measurements of spent fuel assemblies: 1) verify the initial enrichment, burnup, and cooling time of facility declaration; 2) detect the diversion or replacement of pins; 3) estimate the plutonium mass; 4) estimate decay heat; and 5) determine the reactivity of spent fuel assemblies. The differential die-away self-interrogation (DDSI) instrument is one instrumentmore » that was assessed for years regarding its feasibility for robust, timely verification of spent fuel assemblies. The instrument was recently built and was tested using fresh fuel assemblies in a variety of configurations, including varying enrichment, neutron absorber content, and symmetry. The early die-away method, a multiplication determination method developed in simulation space, was successfully tested on the fresh fuel assembly data and determined multiplication with a root-mean-square (RMS) error of 2.9%. The experimental results were compared with MCNP simulations of the instrument as well. Low multiplication assemblies had agreement with an average RMS error of 0.2% in the singles count rate (i.e., total neutrons detected per second) and 3.4% in the doubles count rates (i.e., neutrons detected in coincidence per second). High-multiplication assemblies had agreement with an average RMS error of 4.1% in the singles and 13.3% in the doubles count rates.« less

Fresh Fuel Measurements With the Differential Die-Away Self-Interrogation Instrument

DOE PAGES

Trahan, Alexis C.; Belian, Anthony P.; Swinhoe, Martyn T.; ...

2017-01-05

The purpose of the Next Generation Safeguards Initiative (NGSI)-Spent Fuel (SF) Project is to strengthen the technical toolkit of safeguards inspectors and/or other interested parties. Thus the NGSI-SF team is working to achieve the following technical goals more easily and efficiently than in the past using nondestructive assay measurements of spent fuel assemblies: 1) verify the initial enrichment, burnup, and cooling time of facility declaration; 2) detect the diversion or replacement of pins; 3) estimate the plutonium mass; 4) estimate decay heat; and 5) determine the reactivity of spent fuel assemblies. The differential die-away self-interrogation (DDSI) instrument is one instrumentmore » that was assessed for years regarding its feasibility for robust, timely verification of spent fuel assemblies. The instrument was recently built and was tested using fresh fuel assemblies in a variety of configurations, including varying enrichment, neutron absorber content, and symmetry. The early die-away method, a multiplication determination method developed in simulation space, was successfully tested on the fresh fuel assembly data and determined multiplication with a root-mean-square (RMS) error of 2.9%. The experimental results were compared with MCNP simulations of the instrument as well. Low multiplication assemblies had agreement with an average RMS error of 0.2% in the singles count rate (i.e., total neutrons detected per second) and 3.4% in the doubles count rates (i.e., neutrons detected in coincidence per second). High-multiplication assemblies had agreement with an average RMS error of 4.1% in the singles and 13.3% in the doubles count rates.« less

An emperor penguin population estimate: the first global, synoptic survey of a species from space.

PubMed

Fretwell, Peter T; Larue, Michelle A; Morin, Paul; Kooyman, Gerald L; Wienecke, Barbara; Ratcliffe, Norman; Fox, Adrian J; Fleming, Andrew H; Porter, Claire; Trathan, Phil N

2012-01-01

Our aim was to estimate the population of emperor penguins (Aptenodytes fosteri) using a single synoptic survey. We examined the whole continental coastline of Antarctica using a combination of medium resolution and Very High Resolution (VHR) satellite imagery to identify emperor penguin colony locations. Where colonies were identified, VHR imagery was obtained in the 2009 breeding season. The remotely-sensed images were then analysed using a supervised classification method to separate penguins from snow, shadow and guano. Actual counts of penguins from eleven ground truthing sites were used to convert these classified areas into numbers of penguins using a robust regression algorithm.We found four new colonies and confirmed the location of three previously suspected sites giving a total number of emperor penguin breeding colonies of 46. We estimated the breeding population of emperor penguins at each colony during 2009 and provide a population estimate of ~238,000 breeding pairs (compared with the last previously published count of 135,000-175,000 pairs). Based on published values of the relationship between breeders and non-breeders, this translates to a total population of ~595,000 adult birds.There is a growing consensus in the literature that global and regional emperor penguin populations will be affected by changing climate, a driver thought to be critical to their future survival. However, a complete understanding is severely limited by the lack of detailed knowledge about much of their ecology, and importantly a poor understanding of their total breeding population. To address the second of these issues, our work now provides a comprehensive estimate of the total breeding population that can be used in future population models and will provide a baseline for long-term research.

An Emperor Penguin Population Estimate: The First Global, Synoptic Survey of a Species from Space

PubMed Central

Fretwell, Peter T.; LaRue, Michelle A.; Morin, Paul; Kooyman, Gerald L.; Wienecke, Barbara; Ratcliffe, Norman; Fox, Adrian J.; Fleming, Andrew H.; Porter, Claire; Trathan, Phil N.

2012-01-01

Our aim was to estimate the population of emperor penguins (Aptenodytes fosteri) using a single synoptic survey. We examined the whole continental coastline of Antarctica using a combination of medium resolution and Very High Resolution (VHR) satellite imagery to identify emperor penguin colony locations. Where colonies were identified, VHR imagery was obtained in the 2009 breeding season. The remotely-sensed images were then analysed using a supervised classification method to separate penguins from snow, shadow and guano. Actual counts of penguins from eleven ground truthing sites were used to convert these classified areas into numbers of penguins using a robust regression algorithm. We found four new colonies and confirmed the location of three previously suspected sites giving a total number of emperor penguin breeding colonies of 46. We estimated the breeding population of emperor penguins at each colony during 2009 and provide a population estimate of ∼238,000 breeding pairs (compared with the last previously published count of 135,000–175,000 pairs). Based on published values of the relationship between breeders and non-breeders, this translates to a total population of ∼595,000 adult birds. There is a growing consensus in the literature that global and regional emperor penguin populations will be affected by changing climate, a driver thought to be critical to their future survival. However, a complete understanding is severely limited by the lack of detailed knowledge about much of their ecology, and importantly a poor understanding of their total breeding population. To address the second of these issues, our work now provides a comprehensive estimate of the total breeding population that can be used in future population models and will provide a baseline for long-term research. PMID:22514609

Statistical aspects of point count sampling

USGS Publications Warehouse

Barker, R.J.; Sauer, J.R.; Ralph, C.J.; Sauer, J.R.; Droege, S.

1995-01-01

The dominant feature of point counts is that they do not census birds, but instead provide incomplete counts of individuals present within a survey plot. Considering a simple model for point count sampling, we demon-strate that use of these incomplete counts can bias estimators and testing procedures, leading to inappropriate conclusions. A large portion of the variability in point counts is caused by the incomplete counting, and this within-count variation can be confounded with ecologically meaningful varia-tion. We recommend caution in the analysis of estimates obtained from point counts. Using; our model, we also consider optimal allocation of sampling effort. The critical step in the optimization process is in determining the goals of the study and methods that will be used to meet these goals. By explicitly defining the constraints on sampling and by estimating the relationship between precision and bias of estimators and time spent counting, we can predict the optimal time at a point for each of several monitoring goals. In general, time spent at a point will differ depending on the goals of the study.

Validity and feasibility of a satellite imagery-based method for rapid estimation of displaced populations

PubMed Central

2013-01-01

Background Estimating the size of forcibly displaced populations is key to documenting their plight and allocating sufficient resources to their assistance, but is often not done, particularly during the acute phase of displacement, due to methodological challenges and inaccessibility. In this study, we explored the potential use of very high resolution satellite imagery to remotely estimate forcibly displaced populations. Methods Our method consisted of multiplying (i) manual counts of assumed residential structures on a satellite image and (ii) estimates of the mean number of people per structure (structure occupancy) obtained from publicly available reports. We computed population estimates for 11 sites in Bangladesh, Chad, Democratic Republic of Congo, Ethiopia, Haiti, Kenya and Mozambique (six refugee camps, three internally displaced persons’ camps and two urban neighbourhoods with a mixture of residents and displaced) ranging in population from 1,969 to 90,547, and compared these to “gold standard” reference population figures from census or other robust methods. Results Structure counts by independent analysts were reasonably consistent. Between one and 11 occupancy reports were available per site and most of these reported people per household rather than per structure. The imagery-based method had a precision relative to reference population figures of <10% in four sites and 10–30% in three sites, but severely over-estimated the population in an Ethiopian camp with implausible occupancy data and two post-earthquake Haiti sites featuring dense and complex residential layout. For each site, estimates were produced in 2–5 working person-days. Conclusions In settings with clearly distinguishable individual structures, the remote, imagery-based method had reasonable accuracy for the purposes of rapid estimation, was simple and quick to implement, and would likely perform better in more current application. However, it may have insurmountable limitations in settings featuring connected buildings or shelters, a complex pattern of roofs and multi-level buildings. Based on these results, we discuss possible ways forward for the method’s development. PMID:23343099

Validity and feasibility of a satellite imagery-based method for rapid estimation of displaced populations.

PubMed

Checchi, Francesco; Stewart, Barclay T; Palmer, Jennifer J; Grundy, Chris

2013-01-23

Estimating the size of forcibly displaced populations is key to documenting their plight and allocating sufficient resources to their assistance, but is often not done, particularly during the acute phase of displacement, due to methodological challenges and inaccessibility. In this study, we explored the potential use of very high resolution satellite imagery to remotely estimate forcibly displaced populations. Our method consisted of multiplying (i) manual counts of assumed residential structures on a satellite image and (ii) estimates of the mean number of people per structure (structure occupancy) obtained from publicly available reports. We computed population estimates for 11 sites in Bangladesh, Chad, Democratic Republic of Congo, Ethiopia, Haiti, Kenya and Mozambique (six refugee camps, three internally displaced persons' camps and two urban neighbourhoods with a mixture of residents and displaced) ranging in population from 1,969 to 90,547, and compared these to "gold standard" reference population figures from census or other robust methods. Structure counts by independent analysts were reasonably consistent. Between one and 11 occupancy reports were available per site and most of these reported people per household rather than per structure. The imagery-based method had a precision relative to reference population figures of <10% in four sites and 10-30% in three sites, but severely over-estimated the population in an Ethiopian camp with implausible occupancy data and two post-earthquake Haiti sites featuring dense and complex residential layout. For each site, estimates were produced in 2-5 working person-days. In settings with clearly distinguishable individual structures, the remote, imagery-based method had reasonable accuracy for the purposes of rapid estimation, was simple and quick to implement, and would likely perform better in more current application. However, it may have insurmountable limitations in settings featuring connected buildings or shelters, a complex pattern of roofs and multi-level buildings. Based on these results, we discuss possible ways forward for the method's development.

Estimating and comparing microbial diversity in the presence of sequencing errors

PubMed Central

Chiu, Chun-Huo

2016-01-01

Estimating and comparing microbial diversity are statistically challenging due to limited sampling and possible sequencing errors for low-frequency counts, producing spurious singletons. The inflated singleton count seriously affects statistical analysis and inferences about microbial diversity. Previous statistical approaches to tackle the sequencing errors generally require different parametric assumptions about the sampling model or about the functional form of frequency counts. Different parametric assumptions may lead to drastically different diversity estimates. We focus on nonparametric methods which are universally valid for all parametric assumptions and can be used to compare diversity across communities. We develop here a nonparametric estimator of the true singleton count to replace the spurious singleton count in all methods/approaches. Our estimator of the true singleton count is in terms of the frequency counts of doubletons, tripletons and quadrupletons, provided these three frequency counts are reliable. To quantify microbial alpha diversity for an individual community, we adopt the measure of Hill numbers (effective number of taxa) under a nonparametric framework. Hill numbers, parameterized by an order q that determines the measures’ emphasis on rare or common species, include taxa richness (q = 0), Shannon diversity (q = 1, the exponential of Shannon entropy), and Simpson diversity (q = 2, the inverse of Simpson index). A diversity profile which depicts the Hill number as a function of order q conveys all information contained in a taxa abundance distribution. Based on the estimated singleton count and the original non-singleton frequency counts, two statistical approaches (non-asymptotic and asymptotic) are developed to compare microbial diversity for multiple communities. (1) A non-asymptotic approach refers to the comparison of estimated diversities of standardized samples with a common finite sample size or sample completeness. This approach aims to compare diversity estimates for equally-large or equally-complete samples; it is based on the seamless rarefaction and extrapolation sampling curves of Hill numbers, specifically for q = 0, 1 and 2. (2) An asymptotic approach refers to the comparison of the estimated asymptotic diversity profiles. That is, this approach compares the estimated profiles for complete samples or samples whose size tends to be sufficiently large. It is based on statistical estimation of the true Hill number of any order q ≥ 0. In the two approaches, replacing the spurious singleton count by our estimated count, we can greatly remove the positive biases associated with diversity estimates due to spurious singletons and also make fair comparisons across microbial communities, as illustrated in our simulation results and in applying our method to analyze sequencing data from viral metagenomes. PMID:26855872

Children's Numerical Estimation: Flexibility in the Use of Counting.

ERIC Educational Resources Information Center

Newman, Richard S.; Berger, Carl F.

1984-01-01

Using a microcomputer "dart" game, this study of 61 primary school students investigated how children of different ages used counting to make numerical estimates. Results showed developmental differences in accuracy of estimation, fluency in counting and sophistication of self-reported strategy use. (BS)

A robust hypothesis test for the sensitive detection of constant speed radiation moving sources

NASA Astrophysics Data System (ADS)

Dumazert, Jonathan; Coulon, Romain; Kondrasovs, Vladimir; Boudergui, Karim; Moline, Yoann; Sannié, Guillaume; Gameiro, Jordan; Normand, Stéphane; Méchin, Laurence

2015-09-01

Radiation Portal Monitors are deployed in linear networks to detect radiological material in motion. As a complement to single and multichannel detection algorithms, inefficient under too low signal-to-noise ratios, temporal correlation algorithms have been introduced. Test hypothesis methods based on empirically estimated mean and variance of the signals delivered by the different channels have shown significant gain in terms of a tradeoff between detection sensitivity and false alarm probability. This paper discloses the concept of a new hypothesis test for temporal correlation detection methods, taking advantage of the Poisson nature of the registered counting signals, and establishes a benchmark between this test and its empirical counterpart. The simulation study validates that in the four relevant configurations of a pedestrian source carrier under respectively high and low count rate radioactive backgrounds, and a vehicle source carrier under the same respectively high and low count rate radioactive backgrounds, the newly introduced hypothesis test ensures a significantly improved compromise between sensitivity and false alarm. It also guarantees that the optimal coverage factor for this compromise remains stable regardless of signal-to-noise ratio variations between 2 and 0.8, therefore allowing the final user to parametrize the test with the sole prior knowledge of background amplitude.

Virus Characterization by FFF-MALS Assay

NASA Astrophysics Data System (ADS)

Razinkov, Vladimer

2009-03-01

Adequate biophysical characterization of influenza virions is important for vaccine development. The influenza virus vaccines are produced from the allantoic fluid of developing chicken embryos. The process of viral replication produces a heterogeneous mixture of infectious and non-infectious viral particles with varying states of aggregation. The study of the relative distribution and behavior of different subpopulations and their inter-correlation can assist in the development of a robust process for a live virus vaccine. This report describes a field flow fractionation and multiangle light scattering (FFF-MALS) method optimized for the analysis of size distribution and total particle counts. A method using a combination of asymmetric flow field-flow fractionation (AFFFF) and multiangle light scattering (MALS) techniques has been shown to improve the estimation of virus particle counts and the amount of aggregated virus in laboratory samples. The FFF-MALS method was compared with several other methods such as transmission electron microscopy (TEM), atomic force microscopy (AFM), size exclusion chromatography followed by MALS (SEC-MALS), quantitative reverse transcription polymerase chain reaction (RT Q-PCR), median tissue culture dose (TCID(50)), and the fluorescent focus assay (FFA). The correlation between the various methods for determining total particle counts, infectivity and size distribution is reported. The pros and cons of each of the analytical methods are discussed.

Deep 1.1mm-wavelength imaging of the GOODS-S field by AzTEC/ASTE - I. Source catalogue and number counts

NASA Astrophysics Data System (ADS)

Scott, K. S.; Yun, M. S.; Wilson, G. W.; Austermann, J. E.; Aguilar, E.; Aretxaga, I.; Ezawa, H.; Ferrusca, D.; Hatsukade, B.; Hughes, D. H.; Iono, D.; Giavalisco, M.; Kawabe, R.; Kohno, K.; Mauskopf, P. D.; Oshima, T.; Perera, T. A.; Rand, J.; Tamura, Y.; Tosaki, T.; Velazquez, M.; Williams, C. C.; Zeballos, M.

2010-07-01

We present the first results from a confusion-limited map of the Great Observatories Origins Deep Survey-South (GOODS-S) taken with the AzTEC camera on the Atacama Submillimeter Telescope Experiment. We imaged a field to a 1σ depth of 0.48-0.73 mJybeam-1, making this one of the deepest blank-field surveys at mm-wavelengths ever achieved. Although by traditional standards our GOODS-S map is extremely confused due to a sea of faint underlying sources, we demonstrate through simulations that our source identification and number counts analyses are robust, and the techniques discussed in this paper are relevant for other deeply confused surveys. We find a total of 41 dusty starburst galaxies with signal-to-noise ratios S/N >= 3. 5 within this uniformly covered region, where only two are expected to be false detections, and an additional seven robust source candidates located in the noisier (1σ ~ 1 mJybeam-1) outer region of the map. We derive the 1.1 mm number counts from this field using two different methods: a fluctuation or ``P(d)'' analysis and a semi-Bayesian technique and find that both methods give consistent results. Our data are well fit by a Schechter function model with . Given the depth of this survey, we put the first tight constraints on the 1.1 mm number counts at S1.1mm = 0.5 mJy, and we find evidence that the faint end of the number counts at from various SCUBA surveys towards lensing clusters are biased high. In contrast to the 870μm survey of this field with the LABOCA camera, we find no apparent underdensity of sources compared to previous surveys at 1.1mm the estimates of the number counts of SMGs at flux densities >1mJy determined here are consistent with those measured from the AzTEC/SHADES survey. Additionally, we find a significant number of SMGs not identified in the LABOCA catalogue. We find that in contrast to observations at λ <= 500μm, MIPS 24μm sources do not resolve the total energy density in the cosmic infrared background at 1.1 mm, demonstrating that a population of z >~ 3 dust-obscured galaxies that are unaccounted for at these shorter wavelengths potentially contribute to a large fraction (~2/3) of the infrared background at 1.1 mm.

Development and validation of a melanoma risk score based on pooled data from 16 case-control studies

PubMed Central

Davies, John R; Chang, Yu-mei; Bishop, D Timothy; Armstrong, Bruce K; Bataille, Veronique; Bergman, Wilma; Berwick, Marianne; Bracci, Paige M; Elwood, J Mark; Ernstoff, Marc S; Green, Adele; Gruis, Nelleke A; Holly, Elizabeth A; Ingvar, Christian; Kanetsky, Peter A; Karagas, Margaret R; Lee, Tim K; Le Marchand, Loïc; Mackie, Rona M; Olsson, Håkan; Østerlind, Anne; Rebbeck, Timothy R; Reich, Kristian; Sasieni, Peter; Siskind, Victor; Swerdlow, Anthony J; Titus, Linda; Zens, Michael S; Ziegler, Andreas; Gallagher, Richard P.; Barrett, Jennifer H; Newton-Bishop, Julia

2015-01-01

Background We report the development of a cutaneous melanoma risk algorithm based upon 7 factors; hair colour, skin type, family history, freckling, nevus count, number of large nevi and history of sunburn, intended to form the basis of a self-assessment webtool for the general public. Methods Predicted odds of melanoma were estimated by analysing a pooled dataset from 16 case-control studies using logistic random coefficients models. Risk categories were defined based on the distribution of the predicted odds in the controls from these studies. Imputation was used to estimate missing data in the pooled datasets. The 30th, 60th and 90th centiles were used to distribute individuals into four risk groups for their age, sex and geographic location. Cross-validation was used to test the robustness of the thresholds for each group by leaving out each study one by one. Performance of the model was assessed in an independent UK case-control study dataset. Results Cross-validation confirmed the robustness of the threshold estimates. Cases and controls were well discriminated in the independent dataset (area under the curve 0.75, 95% CI 0.73-0.78). 29% of cases were in the highest risk group compared with 7% of controls, and 43% of controls were in the lowest risk group compared with 13% of cases. Conclusion We have identified a composite score representing an estimate of relative risk and successfully validated this score in an independent dataset. Impact This score may be a useful tool to inform members of the public about their melanoma risk. PMID:25713022

The MUSE Hubble Ultra Deep Field Survey. IX. Evolution of galaxy merger fraction since z ≈ 6

NASA Astrophysics Data System (ADS)

Ventou, E.; Contini, T.; Bouché, N.; Epinat, B.; Brinchmann, J.; Bacon, R.; Inami, H.; Lam, D.; Drake, A.; Garel, T.; Michel-Dansac, L.; Pello, R.; Steinmetz, M.; Weilbacher, P. M.; Wisotzki, L.; Carollo, M.

2017-11-01

We provide, for the first time, robust observational constraints on the galaxy major merger fraction up to z ≈ 6 using spectroscopic close pair counts. Deep Multi Unit Spectroscopic Explorer (MUSE) observations in the Hubble Ultra Deep Field (HUDF) and Hubble Deep Field South (HDF-S) are used to identify 113 secure close pairs of galaxies among a parent sample of 1801 galaxies spread over a large redshift range (0.2 < z < 6) and stellar masses (107-1011 M⊙), thus probing about 12 Gyr of galaxy evolution. Stellar masses are estimated from spectral energy distribution (SED) fitting over the extensive UV-to-NIR HST photometry available in these deep Hubble fields, adding Spitzer IRAC bands to better constrain masses for high-redshift (z ⩾ 3) galaxies. These stellar masses are used to isolate a sample of 54 major close pairs with a galaxy mass ratio limit of 1:6. Among this sample, 23 pairs are identified at high redshift (z ⩾ 3) through their Lyα emission. The sample of major close pairs is divided into five redshift intervals in order to probe the evolution of the merger fraction with cosmic time. Our estimates are in very good agreement with previous close pair counts with a constant increase of the merger fraction up to z ≈ 3 where it reaches a maximum of 20%. At higher redshift, we show that the fraction slowly decreases down to about 10% at z ≈ 6. The sample is further divided into two ranges of stellar masses using either a constant separation limit of 109.5 M⊙ or the median value of stellar mass computed in each redshift bin. Overall, the major close pair fraction for low-mass and massive galaxies follows the same trend. These new, homogeneous, and robust estimates of the major merger fraction since z ≈ 6 are in good agreement with recent predictions of cosmological numerical simulations. Based on observations made with ESO telescopes at the La Silla-Paranal Observatory under programmes 094.A-0289(B), 095.A-0010(A), 096.A-0045(A) and 096.A-0045(B).

Estimating the Effects of Detection Heterogeneity and Overdispersion on Trends Estimated from Avian Point Counts

EPA Science Inventory

Point counts are a common method for sampling avian distribution and abundance. Though methods for estimating detection probabilities are available, many analyses use raw counts and do not correct for detectability. We use a removal model of detection within an N-mixture approa...

Designing a Bicycle and Pedestrian Traffic Count Program to Estimate Performance Measures on Streets and Sidewalks in Blacksburg, VA

DOT National Transportation Integrated Search

2016-05-31

We developed and implemented a traffic count program in Blacksburg, VA to estimate performance measures of bicycle and pedestrian traffic. We deployed and validated automated counters at 101 count sites; the count sites consisted of 4 permanent refer...

Point Counts of Birds: What Are We Estimating?

Treesearch

Douglas H. Johnson

1995-01-01

Point counts of birds are made for many reasons, including estimating local densities, determining population trends, assessing habitat preferences, and exploiting the activities of recreational birdwatchers. Problems arise unless there is a clear understanding of what point counts mean in terms of actual populations of birds. Criteria for conducting point counts...

A Multiple Parameters Biodosimetry Tool with Various Blood Cell Counts - the Hemodose Approach

NASA Technical Reports Server (NTRS)

Hu, Shaowen

2014-01-01

There continue to be important concerns about the possibility of the occurrence of acute radiation syndromes following nuclear and radiological terrorism or accidents that may result in mass casualties in densely populated areas. To guide medical personnel in their clinical decisions for effective medical management and treatment of the exposed individuals, biological markers are usually applied to examine radiation induced biological changes to assess the severity of radiation injury to sensitive organ systems. Among these the peripheral blood cell counts are widely used to assess the extent of radiation induced bone marrow injury. This is due to the fact that the hematopoietic system is the most vulnerable part of the human body to radiation damage. Particularly, the lymphocyte, granulocyte, and platelet cells are the most radiosensitive of the blood elements, and monitoring their changes after exposure is regarded as a practical and recommended laboratory test to estimate radiation dose and injury. Based upon years of physiological and pathophysiological investigation of mammalian hematopoietic systems, and rigorous coarse-grained bio-mathematical modeling and validation on species from mouse, to dog, monkey, and human, we have developed a set of software tools Hemodose, which can use single or serial granulocyte, lymphocyte, leukocyte, or platelet counts after exposure to estimate absorbed doses of adult victims very rapidly and accurately. Some patient data from historical accidents are utilized as examples to demonstrate the capabilities of these tools as a rapid point-of-care diagnostic or centralized high-throughput assay system in a large-scale radiological disaster scenario. Most significant to the improvement of national and local preparedness of a potential nuclear/radiological disaster, this HemoDose approach establishes robust correlations between the absorbed doses and victim's various types of blood cell counts not only in the early time window (1 or 2 days), but also in the very late phase (up to 4 weeks) after exposure.

Incorporating availability for detection in estimates of bird abundance

USGS Publications Warehouse

Diefenbach, D.R.; Marshall, M.R.; Mattice, J.A.; Brauning, D.W.

2007-01-01

Several bird-survey methods have been proposed that provide an estimated detection probability so that bird-count statistics can be used to estimate bird abundance. However, some of these estimators adjust counts of birds observed by the probability that a bird is detected and assume that all birds are available to be detected at the time of the survey. We marked male Henslow's Sparrows (Ammodramus henslowii) and Grasshopper Sparrows (A. savannarum) and monitored their behavior during May-July 2002 and 2003 to estimate the proportion of time they were available for detection. We found that the availability of Henslow's Sparrows declined in late June to <10% for 5- or 10-min point counts when a male had to sing and be visible to the observer; but during 20 May-19 June, males were available for detection 39.1% (SD = 27.3) of the time for 5-min point counts and 43.9% (SD = 28.9) of the time for 10-min point counts (n = 54). We detected no temporal changes in availability for Grasshopper Sparrows, but estimated availability to be much lower for 5-min point counts (10.3%, SD = 12.2) than for 10-min point counts (19.2%, SD = 22.3) when males had to be visible and sing during the sampling period (n = 80). For distance sampling, we estimated the availability of Henslow's Sparrows to be 44.2% (SD = 29.0) and the availability of Grasshopper Sparrows to be 20.6% (SD = 23.5). We show how our estimates of availability can be incorporated in the abundance and variance estimators for distance sampling and modify the abundance and variance estimators for the double-observer method. Methods that directly estimate availability from bird counts but also incorporate detection probabilities need further development and will be important for obtaining unbiased estimates of abundance for these species.

Statistical Analysis and Time Series Modeling of Air Traffic Operations Data From Flight Service Stations and Terminal Radar Approach Control Facilities : Two Case Studies

DOT National Transportation Integrated Search

1981-10-01

Two statistical procedures have been developed to estimate hourly or daily aircraft counts. These counts can then be transformed into estimates of instantaneous air counts. The first procedure estimates the stable (deterministic) mean level of hourly...

The origin and reduction of spurious extrahepatic counts observed in 90Y non-TOF PET imaging post radioembolization

NASA Astrophysics Data System (ADS)

Walrand, Stephan; Hesse, Michel; Jamar, François; Lhommel, Renaud

2018-04-01

Our literature survey revealed a physical effect unknown to the nuclear medicine community, i.e. internal bremsstrahlung emission, and also the existence of long energy resolution tails in crystal scintillation. None of these effects has ever been modelled in PET Monte Carlo (MC) simulations. This study investigates whether these two effects could be at the origin of two unexplained observations in 90Y imaging by PET: the increasing tails in the radial profile of true coincidences, and the presence of spurious extrahepatic counts post radioembolization in non-TOF PET and their absence in TOF PET. These spurious extrahepatic counts hamper the microsphere delivery check in liver radioembolization. An acquisition of a 32P vial was performed on a GSO PET system. This is the ideal setup to study the impact of bremsstrahlung x-rays on the true coincidence rate when no positron emission and no crystal radioactivity are present. A MC simulation of the acquisition was performed using Gate-Geant4. MC simulations of non-TOF PET and TOF-PET imaging of a synthetic 90Y human liver radioembolization phantom were also performed. Internal bremsstrahlung and long energy resolution tails inclusion in MC simulations quantitatively predict the increasing tails in the radial profile. In addition, internal bremsstrahlung explains the discrepancy previously observed in bremsstrahlung SPECT between the measure of the 90Y bremsstrahlung spectrum and its simulation with Gate-Geant4. However the spurious extrahepatic counts in non-TOF PET mainly result from the failure of conventional random correction methods in such low count rate studies and poor robustness versus emission-transmission inconsistency. A novel proposed random correction method succeeds in cleaning the spurious extrahepatic counts in non-TOF PET. Two physical effects not considered up to now in nuclear medicine were identified to be at the origin of the unusual 90Y true coincidences radial profile. TOF reconstruction removing of the spurious extrahepatic counts was theoretically explained by a better robustness against emission-transmission inconsistency. A novel random correction method was proposed to overcome the issue in non-TOF PET. Further studies are needed to assess the novel random correction method robustness.

High throughput single cell counting in droplet-based microfluidics.

PubMed

Lu, Heng; Caen, Ouriel; Vrignon, Jeremy; Zonta, Eleonora; El Harrak, Zakaria; Nizard, Philippe; Baret, Jean-Christophe; Taly, Valérie

2017-05-02

Droplet-based microfluidics is extensively and increasingly used for high-throughput single-cell studies. However, the accuracy of the cell counting method directly impacts the robustness of such studies. We describe here a simple and precise method to accurately count a large number of adherent and non-adherent human cells as well as bacteria. Our microfluidic hemocytometer provides statistically relevant data on large populations of cells at a high-throughput, used to characterize cell encapsulation and cell viability during incubation in droplets.

Data-Adaptive Bias-Reduced Doubly Robust Estimation.

PubMed

Vermeulen, Karel; Vansteelandt, Stijn

2016-05-01

Doubly robust estimators have now been proposed for a variety of target parameters in the causal inference and missing data literature. These consistently estimate the parameter of interest under a semiparametric model when one of two nuisance working models is correctly specified, regardless of which. The recently proposed bias-reduced doubly robust estimation procedure aims to partially retain this robustness in more realistic settings where both working models are misspecified. These so-called bias-reduced doubly robust estimators make use of special (finite-dimensional) nuisance parameter estimators that are designed to locally minimize the squared asymptotic bias of the doubly robust estimator in certain directions of these finite-dimensional nuisance parameters under misspecification of both parametric working models. In this article, we extend this idea to incorporate the use of data-adaptive estimators (infinite-dimensional nuisance parameters), by exploiting the bias reduction estimation principle in the direction of only one nuisance parameter. We additionally provide an asymptotic linearity theorem which gives the influence function of the proposed doubly robust estimator under correct specification of a parametric nuisance working model for the missingness mechanism/propensity score but a possibly misspecified (finite- or infinite-dimensional) outcome working model. Simulation studies confirm the desirable finite-sample performance of the proposed estimators relative to a variety of other doubly robust estimators.

Low CD4+ T cell count as a major atherosclerosis risk factor in HIV-infected women and men

PubMed Central

Kaplan, Robert C; Kingsley, Lawrence A; Gange, Stephen J; Benning, Lorie; Jacobson, Lisa P; Lazar, Jason; Anastos, Kathryn; Tien, Phyllis C; Sharrett, A Richey; Hodis, Howard N

2009-01-01

Objective To assess the association of HIV infection, HIV disease parameters (including CD4+ T-cell counts, HIV viral load, and AIDS) and antiretroviral medication use with subclinical carotid artery atherosclerosis. Design Cross-sectional study nested within a prospective cohort study Methods Among participants in the Women's Interagency HIV Study (1,331 HIV-infected women, 534 HIV-uninfected women) and Multicenter AIDS Cohort Study (600 HIV-infected men, 325 HIV-uninfected men), we measured subclinical carotid artery lesions and common carotid artery intima-media thickness (CIMT) using B-mode ultrasound. We estimated adjusted mean CIMT differences and prevalence ratios (PRs) for carotid lesions associated with HIV-related disease and treatments, with multivariate adjustment to control for possible confounding variables. Results Among HIV-infected individuals, a low CD4+ T cell count was independently associated with an increased prevalence of carotid lesions. Compared to the reference group of HIV-uninfected individuals, the adjusted PR for lesions among HIV-infected individuals with CD4+ T-cell count <200 cells/mm3 was 2.00 (95% confidence interval 1.22, 3.28) in women and 1.74 (95% confidence interval 1.04, 2.93) in men. No consistent association of antiretroviral medications with carotid atherosclerosis was observed, except for a borderline significant association between protease inhibitor use and carotid lesions in men (with no association among women). History of clinical AIDS and HIV viral load were not significantly associated with carotid atherosclerosis. Conclusions Beyond traditional cardiovascular disease risk factors, low CD4+ T-cell count is the most robust risk factor for increased subclinical carotid atherosclerosis in HIV-infected women and men. PMID:18670221

Calculation of in situ acoustic sediment attenuation using off-the-shelf horizontal ADCPs in low concentration settings

USGS Publications Warehouse

Haught, Dan; Venditti, Jeremy G.; Wright, Scott A.

2017-01-01

The use of “off-the-shelf” acoustic Doppler velocity profilers (ADCPs) to estimate suspended sediment concentration and grain-size in rivers requires robust methods to estimate sound attenuation by suspended sediment. Theoretical estimates of sediment attenuation require a priori knowledge of the concentration and grain-size distribution (GSD), making the method impractical to apply in routine monitoring programs. In situ methods use acoustic backscatter profile slope to estimate sediment attenuation, and are a more attractive option. However, the performance of in situ sediment attenuation methods has not been extensively compared to theoretical methods. We used three collocated horizontally mounted ADCPs in the Fraser River at Mission, British Columbia and 298 observations of concentration and GSD along the acoustic beams to calculate theoretical and in situ sediment attenuation. Conversion of acoustic intensity from counts to decibels is influenced by the instrument noise floor, which affects the backscatter profile shape and therefore in situ attenuation. We develop a method that converts counts to decibels to maximize profile length, which is useful in rivers where cross-channel acoustic profile penetration is a fraction of total channel width. Nevertheless, the agreement between theoretical and in situ attenuation is poor at low concentrations because cross-stream gradients in concentration, sediment size or GSD can develop, which affect the backscatter profiles. We establish threshold concentrations below which in situ attenuation is unreliable in Fraser River. Our results call for careful examination of cross-stream changes in suspended sediment characteristics and acoustic profiles across a range of flows before in situ attenuation methods are applied in river monitoring programs.

HEMODOSE: A Set of Multi-parameter Biodosimetry Tools

NASA Technical Reports Server (NTRS)

Hu, Shaowen; Blakely, William F.; Cucinotta, Francis A.

2014-01-01

After the events of September 11, 2001 and recent events at the Fukushima reactors in Japan, there is an increasing concern of the occurrence of nuclear and radiological terrorism or accidents that may result in large casualty in densely populated areas. To guide medical personnel in their clinical decisions for effective medical management and treatment of the exposed individuals, biological markers are usually applied to examine the radiation induced changes at different biological levels. Among these the peripheral blood cell counts are widely used to assess the extent of radiation induced injury. This is due to the fact that hematopoietic system is the most vulnerable part of the human body to radiation damage. Particularly, the lymphocyte, granulocyte, and platelet cells are the most radiosensitive of the blood elements, and monitoring their changes after exposure is regarded as the most practical and best laboratory test to estimate radiation dose. The HEMODOSE web tools are built upon solid physiological and pathophysiological understanding of mammalian hematopoietic systems, and rigorous coarse-grained biomathematical modeling and validation. Using single or serial granulocyte, lymphocyte, leukocyte, or platelet counts after exposure, these tools can estimate absorbed doses of adult victims very rapidly and accurately. Some patient data in historical accidents are utilized as examples to demonstrate the capabilities of these tools as a rapid point-of-care diagnostic or centralized high-throughput assay system in a large scale radiological disaster scenario. Unlike previous dose prediction algorithms, the HEMODOSE web tools establish robust correlations between the absorbed doses and victim's various types of blood cell counts not only in the early time window (1 or 2 days), but also in very late phase (up to 4 weeks) after exposure

HEMODOSE: A Set of Multi-parameter Biodosimetry Tools

NASA Technical Reports Server (NTRS)

Hu, Shaowen; Blakely, William F.; Cucinotta, Francis A.

2014-01-01

There continues to be important concerns of the possibility of the occurrence of acute radiation syndromes following nuclear and radiological terrorism or accidents that may result in mass casualties in densely populated areas. To guide medical personnel in their clinical decisions for effective medical management and treatment of the exposed individuals, biological markers are usually applied to examine radiation induced biological changes to assess the severity of radiation injury to sensitive organ systems. Among these the peripheral blood cell counts are widely used to assess the extent of radiation induced bone marrow (BM) injury. This is due to the fact that hematopoietic system is a vulnerable part of the human body to radiation damage. Particularly, the lymphocyte, granulocyte, and platelet cells are the most radiosensitive of the blood elements, and monitoring their changes after exposure is regarded as a practical and recommended laboratory test to estimate radiation dose and injury. In this work we describe the HEMODOSE web tools, which are built upon solid physiological and pathophysiological understanding of mammalian hematopoietic systems, and rigorous coarse-grained biomathematical modeling and validation. Using single or serial granulocyte, lymphocyte, leukocyte, or platelet counts after exposure, these tools can estimate absorbed doses of adult victims very rapidly and accurately to assess the severity of BM radiation injury. Some patient data from historical accidents are utilized as examples to demonstrate the capabilities of these tools as a rapid point-of-care diagnostic or centralized high-throughput assay system in a large-scale radiological disaster scenario. HEMODOSE web tools establish robust correlations between the absorbed doses and victim's various types of blood cell counts not only in the early time window (1 or 2 days), but also in very late phase (up to 4 weeks) after exposure.

Risk of poor development in young children in low-income and middle-income countries: an estimation and analysis at the global, regional, and country level

PubMed Central

Lu, Chunling; Black, Maureen M; Richter, Linda M

2018-01-01

Summary Background A 2007 study published in The Lancet estimated that approximately 219 million children aged younger than 5 years were exposed to stunting or extreme poverty in 2004. We updated the 2004 estimates with the use of improved data and methods and generated estimates for 2010. Methods We used country-level prevalence of stunting in children younger than 5 years based on the 2006 Growth Standards proposed by WHO and poverty ratios from the World Bank to estimate children who were either stunted or lived in extreme poverty for 141 low-income and middle-income countries in 2004 and 2010. To avoid counting the same children twice, we excluded children jointly exposed to stunting and extreme poverty from children living in extreme poverty. To examine the robustness of estimates, we also used moderate poverty measures. Findings The 2007 study underestimated children at risk of poor development. The estimated number of children exposed to the two risk factors in low-income and middle-income countries decreased from 279·1 million (95% CI 250·4 million–307·4 million) in 2004 to 249·4 million (209·3 million–292·6 million) in 2010; prevalence of children at risk fell from 51% (95% CI 46–56) to 43% (36–51). The decline occurred in all income groups and regions with south Asia experiencing the largest drop. Sub-Saharan Africa had the highest prevalence in both years. These findings were robust to variations in poverty measures. Interpretation Progress has been made in reducing the number of children exposed to stunting or poverty between 2004 and 2010, but this is still not enough. Scaling up of effective interventions targeting the most vulnerable children is urgently needed. Funding National Institutes of Health, Bill & Melinda Gates Foundation, Hilton Foundation, and WHO. PMID:27717632

Comparison and assessment of aerial and ground estimates of waterbird colonies

USGS Publications Warehouse

Green, M.C.; Luent, M.C.; Michot, T.C.; Jeske, C.W.; Leberg, P.L.

2008-01-01

Aerial surveys are often used to quantify sizes of waterbird colonies; however, these surveys would benefit from a better understanding of associated biases. We compared estimates of breeding pairs of waterbirds, in colonies across southern Louisiana, USA, made from the ground, fixed-wing aircraft, and a helicopter. We used a marked-subsample method for ground-counting colonies to obtain estimates of error and visibility bias. We made comparisons over 2 sampling periods: 1) surveys conducted on the same colonies using all 3 methods during 3-11 May 2005 and 2) an expanded fixed-wing and ground-survey comparison conducted over 4 periods (May and Jun, 2004-2005). Estimates from fixed-wing aircraft were approximately 65% higher than those from ground counts for overall estimated number of breeding pairs and for both dark and white-plumaged species. The coefficient of determination between estimates based on ground and fixed-wing aircraft was ???0.40 for most species, and based on the assumption that estimates from the ground were closer to the true count, fixed-wing aerial surveys appeared to overestimate numbers of nesting birds of some species; this bias often increased with the size of the colony. Unlike estimates from fixed-wing aircraft, numbers of nesting pairs made from ground and helicopter surveys were very similar for all species we observed. Ground counts by one observer resulted in underestimated number of breeding pairs by 20% on average. The marked-subsample method provided an estimate of the number of missed nests as well as an estimate of precision. These estimates represent a major advantage of marked-subsample ground counts over aerial methods; however, ground counts are difficult in large or remote colonies. Helicopter surveys and ground counts provide less biased, more precise estimates of breeding pairs than do surveys made from fixed-wing aircraft. We recommend managers employ ground counts using double observers for surveying waterbird colonies when feasible. Fixed-wing aerial surveys may be suitable to determine colony activity and composition of common waterbird species. The most appropriate combination of survey approaches will be based on the need for precise and unbiased estimates, balanced with financial and logistical constraints.

Robustly detecting differential expression in RNA sequencing data using observation weights

PubMed Central

Zhou, Xiaobei; Lindsay, Helen; Robinson, Mark D.

2014-01-01

A popular approach for comparing gene expression levels between (replicated) conditions of RNA sequencing data relies on counting reads that map to features of interest. Within such count-based methods, many flexible and advanced statistical approaches now exist and offer the ability to adjust for covariates (e.g. batch effects). Often, these methods include some sort of ‘sharing of information’ across features to improve inferences in small samples. It is important to achieve an appropriate tradeoff between statistical power and protection against outliers. Here, we study the robustness of existing approaches for count-based differential expression analysis and propose a new strategy based on observation weights that can be used within existing frameworks. The results suggest that outliers can have a global effect on differential analyses. We demonstrate the effectiveness of our new approach with real data and simulated data that reflects properties of real datasets (e.g. dispersion-mean trend) and develop an extensible framework for comprehensive testing of current and future methods. In addition, we explore the origin of such outliers, in some cases highlighting additional biological or technical factors within the experiment. Further details can be downloaded from the project website: http://imlspenticton.uzh.ch/robinson_lab/edgeR_robust/. PMID:24753412

A Two-Stage Algorithm for Origin-Destination Matrices Estimation Considering Dynamic Dispersion Parameter for Route Choice

PubMed Central

Wang, Yong; Ma, Xiaolei; Liu, Yong; Gong, Ke; Henricakson, Kristian C.; Xu, Maozeng; Wang, Yinhai

2016-01-01

This paper proposes a two-stage algorithm to simultaneously estimate origin-destination (OD) matrix, link choice proportion, and dispersion parameter using partial traffic counts in a congested network. A non-linear optimization model is developed which incorporates a dynamic dispersion parameter, followed by a two-stage algorithm in which Generalized Least Squares (GLS) estimation and a Stochastic User Equilibrium (SUE) assignment model are iteratively applied until the convergence is reached. To evaluate the performance of the algorithm, the proposed approach is implemented in a hypothetical network using input data with high error, and tested under a range of variation coefficients. The root mean squared error (RMSE) of the estimated OD demand and link flows are used to evaluate the model estimation results. The results indicate that the estimated dispersion parameter theta is insensitive to the choice of variation coefficients. The proposed approach is shown to outperform two established OD estimation methods and produce parameter estimates that are close to the ground truth. In addition, the proposed approach is applied to an empirical network in Seattle, WA to validate the robustness and practicality of this methodology. In summary, this study proposes and evaluates an innovative computational approach to accurately estimate OD matrices using link-level traffic flow data, and provides useful insight for optimal parameter selection in modeling travelers’ route choice behavior. PMID:26761209

Sparse representation and dictionary learning penalized image reconstruction for positron emission tomography.

PubMed

Chen, Shuhang; Liu, Huafeng; Shi, Pengcheng; Chen, Yunmei

2015-01-21

Accurate and robust reconstruction of the radioactivity concentration is of great importance in positron emission tomography (PET) imaging. Given the Poisson nature of photo-counting measurements, we present a reconstruction framework that integrates sparsity penalty on a dictionary into a maximum likelihood estimator. Patch-sparsity on a dictionary provides the regularization for our effort, and iterative procedures are used to solve the maximum likelihood function formulated on Poisson statistics. Specifically, in our formulation, a dictionary could be trained on CT images, to provide intrinsic anatomical structures for the reconstructed images, or adaptively learned from the noisy measurements of PET. Accuracy of the strategy with very promising application results from Monte-Carlo simulations, and real data are demonstrated.

Robust Magnetotelluric Impedance Estimation

NASA Astrophysics Data System (ADS)

Sutarno, D.

2010-12-01

Robust magnetotelluric (MT) response function estimators are now in standard use by the induction community. Properly devised and applied, these have ability to reduce the influence of unusual data (outliers). The estimators always yield impedance estimates which are better than the conventional least square (LS) estimation because the `real' MT data almost never satisfy the statistical assumptions of Gaussian distribution and stationary upon which normal spectral analysis is based. This paper discuses the development and application of robust estimation procedures which can be classified as M-estimators to MT data. Starting with the description of the estimators, special attention is addressed to the recent development of a bounded-influence robust estimation, including utilization of the Hilbert Transform (HT) operation on causal MT impedance functions. The resulting robust performances are illustrated using synthetic as well as real MT data.

On the asymptotic standard error of a class of robust estimators of ability in dichotomous item response models.

PubMed

Magis, David

2014-11-01

In item response theory, the classical estimators of ability are highly sensitive to response disturbances and can return strongly biased estimates of the true underlying ability level. Robust methods were introduced to lessen the impact of such aberrant responses on the estimation process. The computation of asymptotic (i.e., large-sample) standard errors (ASE) for these robust estimators, however, has not yet been fully considered. This paper focuses on a broad class of robust ability estimators, defined by an appropriate selection of the weight function and the residual measure, for which the ASE is derived from the theory of estimating equations. The maximum likelihood (ML) and the robust estimators, together with their estimated ASEs, are then compared in a simulation study by generating random guessing disturbances. It is concluded that both the estimators and their ASE perform similarly in the absence of random guessing, while the robust estimator and its estimated ASE are less biased and outperform their ML counterparts in the presence of random guessing with large impact on the item response process. © 2013 The British Psychological Society.

Robust Methods for Moderation Analysis with a Two-Level Regression Model.

PubMed

Yang, Miao; Yuan, Ke-Hai

2016-01-01

Moderation analysis has many applications in social sciences. Most widely used estimation methods for moderation analysis assume that errors are normally distributed and homoscedastic. When these assumptions are not met, the results from a classical moderation analysis can be misleading. For more reliable moderation analysis, this article proposes two robust methods with a two-level regression model when the predictors do not contain measurement error. One method is based on maximum likelihood with Student's t distribution and the other is based on M-estimators with Huber-type weights. An algorithm for obtaining the robust estimators is developed. Consistent estimates of standard errors of the robust estimators are provided. The robust approaches are compared against normal-distribution-based maximum likelihood (NML) with respect to power and accuracy of parameter estimates through a simulation study. Results show that the robust approaches outperform NML under various distributional conditions. Application of the robust methods is illustrated through a real data example. An R program is developed and documented to facilitate the application of the robust methods.

Guidebooks for estimating total transit usage through extrapolating incomplete counts : final report.

DOT National Transportation Integrated Search

2016-09-01

This report provides guidance for transit agencies to estimate transit usage for reporting to the National Transit : Database (NTD) when their counting procedure that is designed to perform full counts misses some trips. Transit usage : refers to unl...

On estimating scale invariance in stratocumulus cloud fields

NASA Technical Reports Server (NTRS)

Seze, Genevieve; Smith, Leonard A.

1990-01-01

Examination of cloud radiance fields derived from satellite observations sometimes indicates the existence of a range of scales over which the statistics of the field are scale invariant. Many methods were developed to quantify this scaling behavior in geophysics. The usefulness of such techniques depends both on the physics of the process being robust over a wide range of scales and on the availability of high resolution, low noise observations over these scales. These techniques (area perimeter relation, distribution of areas, estimation of the capacity, d0, through box counting, correlation exponent) are applied to the high resolution satellite data taken during the FIRE experiment and provides initial estimates of the quality of data required by analyzing simple sets. The results of the observed fields are contrasted with those of images of objects with known characteristics (e.g., dimension) where the details of the constructed image simulate current observational limits. Throughout when cloud elements and cloud boundaries are mentioned; it should be clearly understood that by this structures in the radiance field are meant: all the boundaries considered are defined by simple threshold arguments.

Variable selection for zero-inflated and overdispersed data with application to health care demand in Germany

PubMed Central

Wang, Zhu; Shuangge, Ma; Wang, Ching-Yun

2017-01-01

In health services and outcome research, count outcomes are frequently encountered and often have a large proportion of zeros. The zero-inflated negative binomial (ZINB) regression model has important applications for this type of data. With many possible candidate risk factors, this paper proposes new variable selection methods for the ZINB model. We consider maximum likelihood function plus a penalty including the least absolute shrinkage and selection operator (LASSO), smoothly clipped absolute deviation (SCAD) and minimax concave penalty (MCP). An EM (expectation-maximization) algorithm is proposed for estimating the model parameters and conducting variable selection simultaneously. This algorithm consists of estimating penalized weighted negative binomial models and penalized logistic models via the coordinated descent algorithm. Furthermore, statistical properties including the standard error formulae are provided. A simulation study shows that the new algorithm not only has more accurate or at least comparable estimation, also is more robust than the traditional stepwise variable selection. The proposed methods are applied to analyze the health care demand in Germany using an open-source R package mpath. PMID:26059498

The robust corrective action priority-an improved approach for selecting competing corrective actions in FMEA based on principle of robust design

NASA Astrophysics Data System (ADS)

Sutrisno, Agung; Gunawan, Indra; Vanany, Iwan

2017-11-01

In spite of being integral part in risk - based quality improvement effort, studies improving quality of selection of corrective action priority using FMEA technique are still limited in literature. If any, none is considering robustness and risk in selecting competing improvement initiatives. This study proposed a theoretical model to select risk - based competing corrective action by considering robustness and risk of competing corrective actions. We incorporated the principle of robust design in counting the preference score among corrective action candidates. Along with considering cost and benefit of competing corrective actions, we also incorporate the risk and robustness of corrective actions. An example is provided to represent the applicability of the proposed model.

The factors affecting on estimation of carbohydrate content of meals in carbohydrate counting

PubMed Central

Kawamura, Tomoyuki; Takamura, Chihiro; Hirose, Masakazu; Hashimoto, Tomomi; Higashide, Takashi; Kashihara, Yoneo; Hashimura, Kayako; Shintaku, Haruo

2015-01-01

Abstract. The objective of this study was to identify factors affecting on errors in carbohydrate (CHO) content estimation during CHO counting. Thirty-seven type 1 diabetes patients and 22 of their parents and 28 physicians/dieticians were enrolled in this study. CHO counting was counted in “Carb”, with 1 Carb defined as 10 g of CHO. To evaluate the accuracy of CHO counting, 80 real-size photographs of cooked meals were presented to the subjects for Carb estimation. Carbs tended to be overestimated for foods containing relatively small amounts of Carbs. On the other hands, Carbs tended to be underestimated for foods with higher than 6 Carbs. Accurate estimation of the Carbs in food containing a large amount of rice was particularly difficult even in the subjects having the CHO counting experience. The Carb contents of high-calorie foods such as meats, fried foods, and desserts tended to be overestimated. This error was smaller in subjects having the CHO counting experience. In conclusion, misunderstanding of high-calorie dishes containing high amounts of CHO was observed in inexperienced subjects, indicating the efficacy of the current methodology of CHO counting. On the other hand it was difficult even for experienced subjects to assess the amount of seasoned rice, suggesting the need for a new methodology for accurate estimation. PMID:26568656

A double-observer approach for estimating detection probability and abundance from point counts

USGS Publications Warehouse

Nichols, J.D.; Hines, J.E.; Sauer, J.R.; Fallon, F.W.; Fallon, J.E.; Heglund, P.J.

2000-01-01

Although point counts are frequently used in ornithological studies, basic assumptions about detection probabilities often are untested. We apply a double-observer approach developed to estimate detection probabilities for aerial surveys (Cook and Jacobson 1979) to avian point counts. At each point count, a designated 'primary' observer indicates to another ('secondary') observer all birds detected. The secondary observer records all detections of the primary observer as well as any birds not detected by the primary observer. Observers alternate primary and secondary roles during the course of the survey. The approach permits estimation of observer-specific detection probabilities and bird abundance. We developed a set of models that incorporate different assumptions about sources of variation (e.g. observer, bird species) in detection probability. Seventeen field trials were conducted, and models were fit to the resulting data using program SURVIV. Single-observer point counts generally miss varying proportions of the birds actually present, and observer and bird species were found to be relevant sources of variation in detection probabilities. Overall detection probabilities (probability of being detected by at least one of the two observers) estimated using the double-observer approach were very high (>0.95), yielding precise estimates of avian abundance. We consider problems with the approach and recommend possible solutions, including restriction of the approach to fixed-radius counts to reduce the effect of variation in the effective radius of detection among various observers and to provide a basis for using spatial sampling to estimate bird abundance on large areas of interest. We believe that most questions meriting the effort required to carry out point counts also merit serious attempts to estimate detection probabilities associated with the counts. The double-observer approach is a method that can be used for this purpose.

A conceptual guide to detection probability for point counts and other count-based survey methods

Treesearch

D. Archibald McCallum

2005-01-01

Accurate and precise estimates of numbers of animals are vitally needed both to assess population status and to evaluate management decisions. Various methods exist for counting birds, but most of those used with territorial landbirds yield only indices, not true estimates of population size. The need for valid density estimates has spawned a number of models for...

Comparison of methods for estimating density of forest songbirds from point counts

Treesearch

Jennifer L. Reidy; Frank R. Thompson; J. Wesley. Bailey

2011-01-01

New analytical methods have been promoted for estimating the probability of detection and density of birds from count data but few studies have compared these methods using real data. We compared estimates of detection probability and density from distance and time-removal models and survey protocols based on 5- or 10-min counts and outer radii of 50 or 100 m. We...

Anatomical-based partial volume correction for low-dose dedicated cardiac SPECT/CT

NASA Astrophysics Data System (ADS)

Liu, Hui; Chan, Chung; Grobshtein, Yariv; Ma, Tianyu; Liu, Yaqiang; Wang, Shi; Stacy, Mitchel R.; Sinusas, Albert J.; Liu, Chi

2015-09-01

Due to the limited spatial resolution, partial volume effect has been a major degrading factor on quantitative accuracy in emission tomography systems. This study aims to investigate the performance of several anatomical-based partial volume correction (PVC) methods for a dedicated cardiac SPECT/CT system (GE Discovery NM/CT 570c) with focused field-of-view over a clinically relevant range of high and low count levels for two different radiotracer distributions. These PVC methods include perturbation geometry transfer matrix (pGTM), pGTM followed by multi-target correction (MTC), pGTM with known concentration in blood pool, the former followed by MTC and our newly proposed methods, which perform the MTC method iteratively, where the mean values in all regions are estimated and updated by the MTC-corrected images each time in the iterative process. The NCAT phantom was simulated for cardiovascular imaging with 99mTc-tetrofosmin, a myocardial perfusion agent, and 99mTc-red blood cell (RBC), a pure intravascular imaging agent. Images were acquired at six different count levels to investigate the performance of PVC methods in both high and low count levels for low-dose applications. We performed two large animal in vivo cardiac imaging experiments following injection of 99mTc-RBC for evaluation of intramyocardial blood volume (IMBV). The simulation results showed our proposed iterative methods provide superior performance than other existing PVC methods in terms of image quality, quantitative accuracy, and reproducibility (standard deviation), particularly for low-count data. The iterative approaches are robust for both 99mTc-tetrofosmin perfusion imaging and 99mTc-RBC imaging of IMBV and blood pool activity even at low count levels. The animal study results indicated the effectiveness of PVC to correct the overestimation of IMBV due to blood pool contamination. In conclusion, the iterative PVC methods can achieve more accurate quantification, particularly for low count cardiac SPECT studies, typically obtained from low-dose protocols, gated studies, and dynamic applications.

On performance of parametric and distribution-free models for zero-inflated and over-dispersed count responses.

PubMed

Tang, Wan; Lu, Naiji; Chen, Tian; Wang, Wenjuan; Gunzler, Douglas David; Han, Yu; Tu, Xin M

2015-10-30

Zero-inflated Poisson (ZIP) and negative binomial (ZINB) models are widely used to model zero-inflated count responses. These models extend the Poisson and negative binomial (NB) to address excessive zeros in the count response. By adding a degenerate distribution centered at 0 and interpreting it as describing a non-risk group in the population, the ZIP (ZINB) models a two-component population mixture. As in applications of Poisson and NB, the key difference between ZIP and ZINB is the allowance for overdispersion by the ZINB in its NB component in modeling the count response for the at-risk group. Overdispersion arising in practice too often does not follow the NB, and applications of ZINB to such data yield invalid inference. If sources of overdispersion are known, other parametric models may be used to directly model the overdispersion. Such models too are subject to assumed distributions. Further, this approach may not be applicable if information about the sources of overdispersion is unavailable. In this paper, we propose a distribution-free alternative and compare its performance with these popular parametric models as well as a moment-based approach proposed by Yu et al. [Statistics in Medicine 2013; 32: 2390-2405]. Like the generalized estimating equations, the proposed approach requires no elaborate distribution assumptions. Compared with the approach of Yu et al., it is more robust to overdispersed zero-inflated responses. We illustrate our approach with both simulated and real study data. Copyright © 2015 John Wiley & Sons, Ltd.

Temporal variability of local abundance, sex ratio and activity in the Sardinian chalk hill blue butterfly

USGS Publications Warehouse

Casula, P.; Nichols, J.D.

2003-01-01

When capturing and marking of individuals is possible, the application of newly developed capture-recapture models can remove several sources of bias in the estimation of population parameters such as local abundance and sex ratio. For example, observation of distorted sex ratios in counts or captures can reflect either different abundances of the sexes or different sex-specific capture probabilities, and capture-recapture models can help distinguish between these two possibilities. Robust design models and a model selection procedure based on information-theoretic methods were applied to study the local population structure of the endemic Sardinian chalk hill blue butterfly, Polyommatus coridon gennargenti. Seasonal variations of abundance, plus daily and weather-related variations of active populations of males and females were investigated. Evidence was found of protandry and male pioneering of the breeding space. Temporary emigration probability, which describes the proportion of the population not exposed to capture (e.g. absent from the study area) during the sampling process, was estimated, differed between sexes, and was related to temperature, a factor known to influence animal activity. The correlation between temporary emigration and average daily temperature suggested interpreting temporary emigration as inactivity of animals. Robust design models were used successfully to provide a detailed description of the population structure and activity in this butterfly and are recommended for studies of local abundance and animal activity in the field.

Impact of double counting and transfer bias on estimated rates and outcomes of acute myocardial infarction.

PubMed

Westfall, J M; McGloin, J

2001-05-01

Ischemic heart disease is the leading cause of death in the United States. Recent studies report inconsistent findings on the changes in the incidence of hospitalizations for ischemic heart disease. These reports have relied primarily on hospital discharge data. Preliminary data suggest that a significant percentage of patients suffering acute myocardial infarction (MI) in rural communities are transferred to urban centers for care. Patients transferred to a second hospital may be counted twice for one episode of ischemic heart disease. To describe the impact of double counting and transfer bias on the estimation of incidence rates and outcomes of ischemic heart disease, specifically acute MI, in the United States. Analysis of state hospital discharge data from Kansas, Colorado (State Inpatient Database [SID]), Nebraska, Arizona, New Jersey, Michigan, Pennsylvania, and Illinois (SID) for the years 1995 to 1997. A matching algorithm was developed for hospital discharges to determine patients counted twice for one episode of ischemic heart disease. Validation of our matching algorithm. Patients reported to have suffered ischemic heart disease (ICD9 codes 410-414, 786.5). Number of patients counted twice for one episode of acute MI. It is estimated that double count rates range from 10% to 15% for all states and increased over the 3 years. Moderate sized rural counties had the highest estimated double count rates at 15% to 20% with a few counties having estimated double count rates a high as 35% to 50%. Older patients and females were less likely to be double counted (P <0.05). Double counting patients has resulted in a significant overestimation in the incidence rate for hospitalization for acute MI. Correction of this double counting reveals a significantly lower incidence rate and a higher in-hospital mortality rate for acute MI. Transferred patients differ significantly from nontransferred patients, introducing significant bias into MI outcome studies. Double counting and transfer bias should be considered when conducting and interpreting research on ischemic heart disease, particularly in rural regions.

Robust estimation for partially linear models with large-dimensional covariates

PubMed Central

Zhu, LiPing; Li, RunZe; Cui, HengJian

2014-01-01

We are concerned with robust estimation procedures to estimate the parameters in partially linear models with large-dimensional covariates. To enhance the interpretability, we suggest implementing a noncon-cave regularization method in the robust estimation procedure to select important covariates from the linear component. We establish the consistency for both the linear and the nonlinear components when the covariate dimension diverges at the rate of o(n), where n is the sample size. We show that the robust estimate of linear component performs asymptotically as well as its oracle counterpart which assumes the baseline function and the unimportant covariates were known a priori. With a consistent estimator of the linear component, we estimate the nonparametric component by a robust local linear regression. It is proved that the robust estimate of nonlinear component performs asymptotically as well as if the linear component were known in advance. Comprehensive simulation studies are carried out and an application is presented to examine the finite-sample performance of the proposed procedures. PMID:24955087

Robust estimation for partially linear models with large-dimensional covariates.

PubMed

Zhu, LiPing; Li, RunZe; Cui, HengJian

2013-10-01

We are concerned with robust estimation procedures to estimate the parameters in partially linear models with large-dimensional covariates. To enhance the interpretability, we suggest implementing a noncon-cave regularization method in the robust estimation procedure to select important covariates from the linear component. We establish the consistency for both the linear and the nonlinear components when the covariate dimension diverges at the rate of [Formula: see text], where n is the sample size. We show that the robust estimate of linear component performs asymptotically as well as its oracle counterpart which assumes the baseline function and the unimportant covariates were known a priori. With a consistent estimator of the linear component, we estimate the nonparametric component by a robust local linear regression. It is proved that the robust estimate of nonlinear component performs asymptotically as well as if the linear component were known in advance. Comprehensive simulation studies are carried out and an application is presented to examine the finite-sample performance of the proposed procedures.

HgCdTe APD-based linear-mode photon counting components and ladar receivers

NASA Astrophysics Data System (ADS)

Jack, Michael; Wehner, Justin; Edwards, John; Chapman, George; Hall, Donald N. B.; Jacobson, Shane M.

2011-05-01

Linear mode photon counting (LMPC) provides significant advantages in comparison with Geiger Mode (GM) Photon Counting including absence of after-pulsing, nanosecond pulse to pulse temporal resolution and robust operation in the present of high density obscurants or variable reflectivity objects. For this reason Raytheon has developed and previously reported on unique linear mode photon counting components and modules based on combining advanced APDs and advanced high gain circuits. By using HgCdTe APDs we enable Poisson number preserving photon counting. A metric of photon counting technology is dark count rate and detection probability. In this paper we report on a performance breakthrough resulting from improvement in design, process and readout operation enabling >10x reduction in dark counts rate to ~10,000 cps and >104x reduction in surface dark current enabling long 10 ms integration times. Our analysis of key dark current contributors suggest that substantial further reduction in DCR to ~ 1/sec or less can be achieved by optimizing wavelength, operating voltage and temperature.

Robust time and frequency domain estimation methods in adaptive control

NASA Technical Reports Server (NTRS)

Lamaire, Richard Orville

1987-01-01

A robust identification method was developed for use in an adaptive control system. The type of estimator is called the robust estimator, since it is robust to the effects of both unmodeled dynamics and an unmeasurable disturbance. The development of the robust estimator was motivated by a need to provide guarantees in the identification part of an adaptive controller. To enable the design of a robust control system, a nominal model as well as a frequency-domain bounding function on the modeling uncertainty associated with this nominal model must be provided. Two estimation methods are presented for finding parameter estimates, and, hence, a nominal model. One of these methods is based on the well developed field of time-domain parameter estimation. In a second method of finding parameter estimates, a type of weighted least-squares fitting to a frequency-domain estimated model is used. The frequency-domain estimator is shown to perform better, in general, than the time-domain parameter estimator. In addition, a methodology for finding a frequency-domain bounding function on the disturbance is used to compute a frequency-domain bounding function on the additive modeling error due to the effects of the disturbance and the use of finite-length data. The performance of the robust estimator in both open-loop and closed-loop situations is examined through the use of simulations.

Using counts to simultaneously estimate abundance and detection probabilities in a salamander community

USGS Publications Warehouse

Dodd, C.K.; Dorazio, R.M.

2004-01-01

A critical variable in both ecological and conservation field studies is determining how many individuals of a species are present within a defined sampling area. Labor intensive techniques such as capture-mark-recapture and removal sampling may provide estimates of abundance, but there are many logistical constraints to their widespread application. Many studies on terrestrial and aquatic salamanders use counts as an index of abundance, assuming that detection remains constant while sampling. If this constancy is violated, determination of detection probabilities is critical to the accurate estimation of abundance. Recently, a model was developed that provides a statistical approach that allows abundance and detection to be estimated simultaneously from spatially and temporally replicated counts. We adapted this model to estimate these parameters for salamanders sampled over a six vear period in area-constrained plots in Great Smoky Mountains National Park. Estimates of salamander abundance varied among years, but annual changes in abundance did not vary uniformly among species. Except for one species, abundance estimates were not correlated with site covariates (elevation/soil and water pH, conductivity, air and water temperature). The uncertainty in the estimates was so large as to make correlations ineffectual in predicting which covariates might influence abundance. Detection probabilities also varied among species and sometimes among years for the six species examined. We found such a high degree of variation in our counts and in estimates of detection among species, sites, and years as to cast doubt upon the appropriateness of using count data to monitor population trends using a small number of area-constrained survey plots. Still, the model provided reasonable estimates of abundance that could make it useful in estimating population size from count surveys.

Conclusions on measurement uncertainty in microbiology.

PubMed

Forster, Lynne I

2009-01-01

Since its first issue in 1999, testing laboratories wishing to comply with all the requirements of ISO/IEC 17025 have been collecting data for estimating uncertainty of measurement for quantitative determinations. In the microbiological field of testing, some debate has arisen as to whether uncertainty needs to be estimated for each method performed in the laboratory for each type of sample matrix tested. Queries also arise concerning the estimation of uncertainty when plate/membrane filter colony counts are below recommended method counting range limits. A selection of water samples (with low to high contamination) was tested in replicate with the associated uncertainty of measurement being estimated from the analytical results obtained. The analyses performed on the water samples included total coliforms, fecal coliforms, fecal streptococci by membrane filtration, and heterotrophic plate counts by the pour plate technique. For those samples where plate/membrane filter colony counts were > or =20, uncertainty estimates at a 95% confidence level were very similar for the methods, being estimated as 0.13, 0.14, 0.14, and 0.12, respectively. For those samples where plate/membrane filter colony counts were <20, estimated uncertainty values for each sample showed close agreement with published confidence limits established using a Poisson distribution approach.

Use of Surveillance Data on HIV Diagnoses with HIV-Related Symptoms to Estimate the Number of People Living with Undiagnosed HIV in Need of Antiretroviral Therapy

PubMed Central

van Sighem, Ard; Sabin, Caroline A.; Phillips, Andrew N.

2015-01-01

Background It is important to have methods available to estimate the number of people who have undiagnosed HIV and are in need of antiretroviral therapy (ART). Methods The method uses the concept that a predictable level of occurrence of AIDS or other HIV-related clinical symptoms which lead to presentation for care, and hence diagnosis of HIV, arises in undiagnosed people with a given CD4 count. The method requires surveillance data on numbers of new HIV diagnoses with HIV-related symptoms, and the CD4 count at diagnosis. The CD4 count-specific rate at which HIV-related symptoms develop are estimated from cohort data. 95% confidence intervals can be constructed using a simple simulation method. Results For example, if there were 13 HIV diagnoses with HIV-related symptoms made in one year with CD4 count at diagnosis between 150–199 cells/mm3, then since the CD4 count-specific rate of HIV-related symptoms is estimated as 0.216 per person-year, the estimated number of person years lived in people with undiagnosed HIV with CD4 count 150–199 cells/mm3 is 13/0.216 = 60 (95% confidence interval: 29–100), which is considered an estimate of the number of people living with undiagnosed HIV in this CD4 count stratum. Conclusions The method is straightforward to implement within a short period once a surveillance system of all new HIV diagnoses, collecting data on HIV-related symptoms at diagnosis, is in place and is most suitable for estimating the number of undiagnosed people with CD4 count <200 cells/mm3 due to the low rate of developing HIV-related symptoms at higher CD4 counts. A potential source of bias is under-diagnosis and under-reporting of diagnoses with HIV-related symptoms. Although this method has limitations as with all approaches, it is important for prompting increased efforts to identify undiagnosed people, particularly those with low CD4 count, and for informing levels of unmet need for ART. PMID:25768925

Use of surveillance data on HIV diagnoses with HIV-related symptoms to estimate the number of people living with undiagnosed HIV in need of antiretroviral therapy.

PubMed

Lodwick, Rebecca K; Nakagawa, Fumiyo; van Sighem, Ard; Sabin, Caroline A; Phillips, Andrew N

2015-01-01

It is important to have methods available to estimate the number of people who have undiagnosed HIV and are in need of antiretroviral therapy (ART). The method uses the concept that a predictable level of occurrence of AIDS or other HIV-related clinical symptoms which lead to presentation for care, and hence diagnosis of HIV, arises in undiagnosed people with a given CD4 count. The method requires surveillance data on numbers of new HIV diagnoses with HIV-related symptoms, and the CD4 count at diagnosis. The CD4 count-specific rate at which HIV-related symptoms develop are estimated from cohort data. 95% confidence intervals can be constructed using a simple simulation method. For example, if there were 13 HIV diagnoses with HIV-related symptoms made in one year with CD4 count at diagnosis between 150-199 cells/mm3, then since the CD4 count-specific rate of HIV-related symptoms is estimated as 0.216 per person-year, the estimated number of person years lived in people with undiagnosed HIV with CD4 count 150-199 cells/mm3 is 13/0.216 = 60 (95% confidence interval: 29-100), which is considered an estimate of the number of people living with undiagnosed HIV in this CD4 count stratum. The method is straightforward to implement within a short period once a surveillance system of all new HIV diagnoses, collecting data on HIV-related symptoms at diagnosis, is in place and is most suitable for estimating the number of undiagnosed people with CD4 count <200 cells/mm3 due to the low rate of developing HIV-related symptoms at higher CD4 counts. A potential source of bias is under-diagnosis and under-reporting of diagnoses with HIV-related symptoms. Although this method has limitations as with all approaches, it is important for prompting increased efforts to identify undiagnosed people, particularly those with low CD4 count, and for informing levels of unmet need for ART.

Physical activity of Canadian children and youth: accelerometer results from the 2007 to 2009 Canadian Health Measures Survey.

PubMed

Colley, Rachel C; Garriguet, Didier; Janssen, Ian; Craig, Cora L; Clarke, Janine; Tremblay, Mark S

2011-03-01

Physical activity is an important determinant of health and fitness. This study provides contemporary estimates of the physical activity levels of Canadians aged 6 to 19 years. Data are from the 2007 to 2009 Canadian Health Measures Survey. The physical activity of a nationally representative sample was measured using accelerometers. Data are presented as time spent in sedentary, light, moderate and vigorous intensity movement, and in steps accumulated per day. An estimated 9% of boys and 4% of girls accumulate 60 minutes of moderate-to-vigorous physical activity on at least 6 days a week. Regardless of age group, boys are more active than girls. Canadian children and youth spend 8.6 hours per day-62% of their waking hours-in sedentary pursuits. Daily step counts average 12,100 for boys and 10,300 for girls. Based on objective and robust measures, physical activity levels of Canadian children and youth are low.

How much is energy R and D worth?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schock, R. N., LLNL

1997-05-06

The value of energy technology R and D as an insurance investment to reduce the cost of climate change stabilization, oil price shocks, urban air pollution, and energy disruptions is estimated to be $5-8 billion/year in sum total. However, the total that is justified is actually less than this sum because some R and D is applicable to more than one risk. nevertheless, the total DOE investment in energy technology R and D (about $1.3 billion/year in FY97) seems easily justified by its insurance value alone; and, in fact, more might be warranted, particularly in the areas related to climatemore » change and urban air pollution. This conclusion appears robust even if the private sector is assumed to be investing a comparable amount. Not counted is the value to the economy and to US competitiveness of better energy technologies that may result from the R and D; only the insurance value for reducing the cost of these four risks to society was estimated.« less

Interferometric superlocalization of two incoherent optical point sources.

PubMed

Nair, Ranjith; Tsang, Mankei

2016-02-22

A novel interferometric method - SLIVER (Super Localization by Image inVERsion interferometry) - is proposed for estimating the separation of two incoherent point sources with a mean squared error that does not deteriorate as the sources are brought closer. The essential component of the interferometer is an image inversion device that inverts the field in the transverse plane about the optical axis, assumed to pass through the centroid of the sources. The performance of the device is analyzed using the Cramér-Rao bound applied to the statistics of spatially-unresolved photon counting using photon number-resolving and on-off detectors. The analysis is supported by Monte-Carlo simulations of the maximum likelihood estimator for the source separation, demonstrating the superlocalization effect for separations well below that set by the Rayleigh criterion. Simulations indicating the robustness of SLIVER to mismatch between the optical axis and the centroid are also presented. The results are valid for any imaging system with a circularly symmetric point-spread function.

Doubly robust nonparametric inference on the average treatment effect.

PubMed

Benkeser, D; Carone, M; Laan, M J Van Der; Gilbert, P B

2017-12-01

Doubly robust estimators are widely used to draw inference about the average effect of a treatment. Such estimators are consistent for the effect of interest if either one of two nuisance parameters is consistently estimated. However, if flexible, data-adaptive estimators of these nuisance parameters are used, double robustness does not readily extend to inference. We present a general theoretical study of the behaviour of doubly robust estimators of an average treatment effect when one of the nuisance parameters is inconsistently estimated. We contrast different methods for constructing such estimators and investigate the extent to which they may be modified to also allow doubly robust inference. We find that while targeted minimum loss-based estimation can be used to solve this problem very naturally, common alternative frameworks appear to be inappropriate for this purpose. We provide a theoretical study and a numerical evaluation of the alternatives considered. Our simulations highlight the need for and usefulness of these approaches in practice, while our theoretical developments have broad implications for the construction of estimators that permit doubly robust inference in other problems.

Robust geostatistical analysis of spatial data

NASA Astrophysics Data System (ADS)

Papritz, Andreas; Künsch, Hans Rudolf; Schwierz, Cornelia; Stahel, Werner A.

2013-04-01

Most of the geostatistical software tools rely on non-robust algorithms. This is unfortunate, because outlying observations are rather the rule than the exception, in particular in environmental data sets. Outliers affect the modelling of the large-scale spatial trend, the estimation of the spatial dependence of the residual variation and the predictions by kriging. Identifying outliers manually is cumbersome and requires expertise because one needs parameter estimates to decide which observation is a potential outlier. Moreover, inference after the rejection of some observations is problematic. A better approach is to use robust algorithms that prevent automatically that outlying observations have undue influence. Former studies on robust geostatistics focused on robust estimation of the sample variogram and ordinary kriging without external drift. Furthermore, Richardson and Welsh (1995) proposed a robustified version of (restricted) maximum likelihood ([RE]ML) estimation for the variance components of a linear mixed model, which was later used by Marchant and Lark (2007) for robust REML estimation of the variogram. We propose here a novel method for robust REML estimation of the variogram of a Gaussian random field that is possibly contaminated by independent errors from a long-tailed distribution. It is based on robustification of estimating equations for the Gaussian REML estimation (Welsh and Richardson, 1997). Besides robust estimates of the parameters of the external drift and of the variogram, the method also provides standard errors for the estimated parameters, robustified kriging predictions at both sampled and non-sampled locations and kriging variances. Apart from presenting our modelling framework, we shall present selected simulation results by which we explored the properties of the new method. This will be complemented by an analysis a data set on heavy metal contamination of the soil in the vicinity of a metal smelter. Marchant, B.P. and Lark, R.M. 2007. Robust estimation of the variogram by residual maximum likelihood. Geoderma 140: 62-72. Richardson, A.M. and Welsh, A.H. 1995. Robust restricted maximum likelihood in mixed linear models. Biometrics 51: 1429-1439. Welsh, A.H. and Richardson, A.M. 1997. Approaches to the robust estimation of mixed models. In: Handbook of Statistics Vol. 15, Elsevier, pp. 343-384.

Kalman-variant estimators for state of charge in lithium-sulfur batteries

NASA Astrophysics Data System (ADS)

Propp, Karsten; Auger, Daniel J.; Fotouhi, Abbas; Longo, Stefano; Knap, Vaclav

2017-03-01

Lithium-sulfur batteries are now commercially available, offering high specific energy density, low production costs and high safety. However, there is no commercially-available battery management system for them, and there are no published methods for determining state of charge in situ. This paper describes a study to address this gap. The properties and behaviours of lithium-sulfur are briefly introduced, and the applicability of 'standard' lithium-ion state-of-charge estimation methods is explored. Open-circuit voltage methods and 'Coulomb counting' are found to have a poor fit for lithium-sulfur, and model-based methods, particularly recursive Bayesian filters, are identified as showing strong promise. Three recursive Bayesian filters are implemented: an extended Kalman filter (EKF), an unscented Kalman filter (UKF) and a particle filter (PF). These estimators are tested through practical experimentation, considering both a pulse-discharge test and a test based on the New European Driving Cycle (NEDC). Experimentation is carried out at a constant temperature, mirroring the environment expected in the authors' target automotive application. It is shown that the estimators, which are based on a relatively simple equivalent-circuit-network model, can deliver useful results. If the three estimators implemented, the unscented Kalman filter gives the most robust and accurate performance, with an acceptable computational effort.

Tower counts

USGS Publications Warehouse

Woody, Carol Ann; Johnson, D.H.; Shrier, Brianna M.; O'Neal, Jennifer S.; Knutzen, John A.; Augerot, Xanthippe; O'Neal, Thomas A.; Pearsons, Todd N.

2007-01-01

Counting towers provide an accurate, low-cost, low-maintenance, low-technology, and easily mobilized escapement estimation program compared to other methods (e.g., weirs, hydroacoustics, mark-recapture, and aerial surveys) (Thompson 1962; Siebel 1967; Cousens et al. 1982; Symons and Waldichuk 1984; Anderson 2000; Alaska Department of Fish and Game 2003). Counting tower data has been found to be consistent with that of digital video counts (Edwards 2005). Counting towers do not interfere with natural fish migration patterns, nor are fish handled or stressed; however, their use is generally limited to clear rivers that meet specific site selection criteria. The data provided by counting tower sampling allow fishery managers to determine reproductive population size, estimate total return (escapement + catch) and its uncertainty, evaluate population productivity and trends, set harvest rates, determine spawning escapement goals, and forecast future returns (Alaska Department of Fish and Game 1974-2000 and 1975-2004). The number of spawning fish is determined by subtracting subsistence, sport-caught fish, and prespawn mortality from the total estimated escapement. The methods outlined in this protocol for tower counts can be used to provide reasonable estimates ( plus or minus 6%-10%) of reproductive salmon population size and run timing in clear rivers. 

Testing the Accuracy of Aerial Surveys for Large Mammals: An Experiment with African Savanna Elephants (Loxodonta africana).

PubMed

Schlossberg, Scott; Chase, Michael J; Griffin, Curtice R

2016-01-01

Accurate counts of animals are critical for prioritizing conservation efforts. Past research, however, suggests that observers on aerial surveys may fail to detect all individuals of the target species present in the survey area. Such errors could bias population estimates low and confound trend estimation. We used two approaches to assess the accuracy of aerial surveys for African savanna elephants (Loxodonta africana) in northern Botswana. First, we used double-observer sampling, in which two observers make observations on the same herds, to estimate detectability of elephants and determine what variables affect it. Second, we compared total counts, a complete survey of the entire study area, against sample counts, in which only a portion of the study area is sampled. Total counts are often considered a complete census, so comparing total counts against sample counts can help to determine if sample counts are underestimating elephant numbers. We estimated that observers detected only 76% ± SE of 2% of elephant herds and 87 ± 1% of individual elephants present in survey strips. Detectability increased strongly with elephant herd size. Out of the four observers used in total, one observer had a lower detection probability than the other three, and detectability was higher in the rear row of seats than the front. The habitat immediately adjacent to animals also affected detectability, with detection more likely in more open habitats. Total counts were not statistically distinguishable from sample counts. Because, however, the double-observer samples revealed that observers missed 13% of elephants, we conclude that total counts may be undercounting elephants as well. These results suggest that elephant population estimates from both sample and total counts are biased low. Because factors such as observer and habitat affected detectability of elephants, comparisons of elephant populations across time or space may be confounded. We encourage survey teams to incorporate detectability analysis in all aerial surveys for mammals.

Testing the Accuracy of Aerial Surveys for Large Mammals: An Experiment with African Savanna Elephants (Loxodonta africana)

PubMed Central

Schlossberg, Scott; Chase, Michael J.; Griffin, Curtice R.

2016-01-01

Accurate counts of animals are critical for prioritizing conservation efforts. Past research, however, suggests that observers on aerial surveys may fail to detect all individuals of the target species present in the survey area. Such errors could bias population estimates low and confound trend estimation. We used two approaches to assess the accuracy of aerial surveys for African savanna elephants (Loxodonta africana) in northern Botswana. First, we used double-observer sampling, in which two observers make observations on the same herds, to estimate detectability of elephants and determine what variables affect it. Second, we compared total counts, a complete survey of the entire study area, against sample counts, in which only a portion of the study area is sampled. Total counts are often considered a complete census, so comparing total counts against sample counts can help to determine if sample counts are underestimating elephant numbers. We estimated that observers detected only 76% ± SE of 2% of elephant herds and 87 ± 1% of individual elephants present in survey strips. Detectability increased strongly with elephant herd size. Out of the four observers used in total, one observer had a lower detection probability than the other three, and detectability was higher in the rear row of seats than the front. The habitat immediately adjacent to animals also affected detectability, with detection more likely in more open habitats. Total counts were not statistically distinguishable from sample counts. Because, however, the double-observer samples revealed that observers missed 13% of elephants, we conclude that total counts may be undercounting elephants as well. These results suggest that elephant population estimates from both sample and total counts are biased low. Because factors such as observer and habitat affected detectability of elephants, comparisons of elephant populations across time or space may be confounded. We encourage survey teams to incorporate detectability analysis in all aerial surveys for mammals. PMID:27755570

Point count length and detection of forest neotropical migrant birds

USGS Publications Warehouse

Dawson, D.K.; Smith, D.R.; Robbins, C.S.; Ralph, C. John; Sauer, John R.; Droege, Sam

1995-01-01

Comparisons of bird abundances among years or among habitats assume that the rates at which birds are detected and counted are constant within species. We use point count data collected in forests of the Mid-Atlantic states to estimate detection probabilities for Neotropical migrant bird species as a function of count length. For some species, significant differences existed among years or observers in both the probability of detecting the species and in the rate at which individuals are counted. We demonstrate the consequence that variability in species' detection probabilities can have on estimates of population change, and discuss ways for reducing this source of bias in point count studies.

Estimating equations estimates of trends

USGS Publications Warehouse

Link, W.A.; Sauer, J.R.

1994-01-01

The North American Breeding Bird Survey monitors changes in bird populations through time using annual counts at fixed survey sites. The usual method of estimating trends has been to use the logarithm of the counts in a regression analysis. It is contended that this procedure is reasonably satisfactory for more abundant species, but produces biased estimates for less abundant species. An alternative estimation procedure based on estimating equations is presented.

Effects of Near-Term Sea-Level Rise on Coastal Infrastructure

DTIC Science & Technology

2013-03-01

methodology is more objective, and more robust, than the standard methods of counting overwash sand layers or identifying marine microfossils in the...duration thresholds on Atlantic tropical cyclone counts , J. Climate, 23, 2508-2519, doi:10.1175/2009JCLI3034.1. Lane, P., Donnelly, J.P., Woodruff...Holocene Climate in the Northern Great Plains Inferred from Sediment Stratigraphy, Stable Isotopes, Carbonate Geochemistry, Diatoms, and Pollen at Moon

Robust variance estimation with dependent effect sizes: practical considerations including a software tutorial in Stata and spss.

PubMed

Tanner-Smith, Emily E; Tipton, Elizabeth

2014-03-01

Methodologists have recently proposed robust variance estimation as one way to handle dependent effect sizes in meta-analysis. Software macros for robust variance estimation in meta-analysis are currently available for Stata (StataCorp LP, College Station, TX, USA) and spss (IBM, Armonk, NY, USA), yet there is little guidance for authors regarding the practical application and implementation of those macros. This paper provides a brief tutorial on the implementation of the Stata and spss macros and discusses practical issues meta-analysts should consider when estimating meta-regression models with robust variance estimates. Two example databases are used in the tutorial to illustrate the use of meta-analysis with robust variance estimates. Copyright © 2013 John Wiley & Sons, Ltd.

Evaluation of heterotrophic plate and chromogenic agar colony counting in water quality laboratories.

PubMed

Hallas, Gary; Monis, Paul

2015-01-01

The enumeration of bacteria using plate-based counts is a core technique used by food and water microbiology testing laboratories. However, manual counting of bacterial colonies is both time and labour intensive, can vary between operators and also requires manual entry of results into laboratory information management systems, which can be a source of data entry error. An alternative is to use automated digital colony counters, but there is a lack of peer-reviewed validation data to allow incorporation into standards. We compared the performance of digital counting technology (ProtoCOL3) against manual counting using criteria defined in internationally recognized standard methods. Digital colony counting provided a robust, standardized system suitable for adoption in a commercial testing environment. The digital technology has several advantages:•Improved measurement of uncertainty by using a standard and consistent counting methodology with less operator error.•Efficiency for labour and time (reduced cost).•Elimination of manual entry of data onto LIMS.•Faster result reporting to customers.

Matching the Statistical Model to the Research Question for Dental Caries Indices with Many Zero Counts.

PubMed

Preisser, John S; Long, D Leann; Stamm, John W

2017-01-01

Marginalized zero-inflated count regression models have recently been introduced for the statistical analysis of dental caries indices and other zero-inflated count data as alternatives to traditional zero-inflated and hurdle models. Unlike the standard approaches, the marginalized models directly estimate overall exposure or treatment effects by relating covariates to the marginal mean count. This article discusses model interpretation and model class choice according to the research question being addressed in caries research. Two data sets, one consisting of fictional dmft counts in 2 groups and the other on DMFS among schoolchildren from a randomized clinical trial comparing 3 toothpaste formulations to prevent incident dental caries, are analyzed with negative binomial hurdle, zero-inflated negative binomial, and marginalized zero-inflated negative binomial models. In the first example, estimates of treatment effects vary according to the type of incidence rate ratio (IRR) estimated by the model. Estimates of IRRs in the analysis of the randomized clinical trial were similar despite their distinctive interpretations. The choice of statistical model class should match the study's purpose, while accounting for the broad decline in children's caries experience, such that dmft and DMFS indices more frequently generate zero counts. Marginalized (marginal mean) models for zero-inflated count data should be considered for direct assessment of exposure effects on the marginal mean dental caries count in the presence of high frequencies of zero counts. © 2017 S. Karger AG, Basel.

Matching the Statistical Model to the Research Question for Dental Caries Indices with Many Zero Counts

PubMed Central

Preisser, John S.; Long, D. Leann; Stamm, John W.

2017-01-01

Marginalized zero-inflated count regression models have recently been introduced for the statistical analysis of dental caries indices and other zero-inflated count data as alternatives to traditional zero-inflated and hurdle models. Unlike the standard approaches, the marginalized models directly estimate overall exposure or treatment effects by relating covariates to the marginal mean count. This article discusses model interpretation and model class choice according to the research question being addressed in caries research. Two datasets, one consisting of fictional dmft counts in two groups and the other on DMFS among schoolchildren from a randomized clinical trial (RCT) comparing three toothpaste formulations to prevent incident dental caries, are analysed with negative binomial hurdle (NBH), zero-inflated negative binomial (ZINB), and marginalized zero-inflated negative binomial (MZINB) models. In the first example, estimates of treatment effects vary according to the type of incidence rate ratio (IRR) estimated by the model. Estimates of IRRs in the analysis of the RCT were similar despite their distinctive interpretations. Choice of statistical model class should match the study’s purpose, while accounting for the broad decline in children’s caries experience, such that dmft and DMFS indices more frequently generate zero counts. Marginalized (marginal mean) models for zero-inflated count data should be considered for direct assessment of exposure effects on the marginal mean dental caries count in the presence of high frequencies of zero counts. PMID:28291962

Long-term monitoring of endangered Laysan ducks: Index validation and population estimates 1998–2012

USGS Publications Warehouse

Reynolds, Michelle H.; Courtot, Karen; Brinck, Kevin W.; Rehkemper, Cynthia; Hatfield, Jeffrey

2015-01-01

Monitoring endangered wildlife is essential to assessing management or recovery objectives and learning about population status. We tested assumptions of a population index for endangered Laysan duck (or teal; Anas laysanensis) monitored using mark–resight methods on Laysan Island, Hawai’i. We marked 723 Laysan ducks between 1998 and 2009 and identified seasonal surveys through 2012 that met accuracy and precision criteria for estimating population abundance. Our results provide a 15-y time series of seasonal population estimates at Laysan Island. We found differences in detection among seasons and how observed counts related to population estimates. The highest counts and the strongest relationship between count and population estimates occurred in autumn (September–November). The best autumn surveys yielded population abundance estimates that ranged from 674 (95% CI = 619–730) in 2003 to 339 (95% CI = 265–413) in 2012. A population decline of 42% was observed between 2010 and 2012 after consecutive storms and Japan’s To¯hoku earthquake-generated tsunami in 2011. Our results show positive correlations between the seasonal maximum counts and population estimates from the same date, and support the use of standardized bimonthly counts of unmarked birds as a valid index to monitor trends among years within a season at Laysan Island.

Modeling visual clutter perception using proto-object segmentation

PubMed Central

Yu, Chen-Ping; Samaras, Dimitris; Zelinsky, Gregory J.

2014-01-01

We introduce the proto-object model of visual clutter perception. This unsupervised model segments an image into superpixels, then merges neighboring superpixels that share a common color cluster to obtain proto-objects—defined here as spatially extended regions of coherent features. Clutter is estimated by simply counting the number of proto-objects. We tested this model using 90 images of realistic scenes that were ranked by observers from least to most cluttered. Comparing this behaviorally obtained ranking to a ranking based on the model clutter estimates, we found a significant correlation between the two (Spearman's ρ = 0.814, p < 0.001). We also found that the proto-object model was highly robust to changes in its parameters and was generalizable to unseen images. We compared the proto-object model to six other models of clutter perception and demonstrated that it outperformed each, in some cases dramatically. Importantly, we also showed that the proto-object model was a better predictor of clutter perception than an actual count of the number of objects in the scenes, suggesting that the set size of a scene may be better described by proto-objects than objects. We conclude that the success of the proto-object model is due in part to its use of an intermediate level of visual representation—one between features and objects—and that this is evidence for the potential importance of a proto-object representation in many common visual percepts and tasks. PMID:24904121

Robust estimation approach for blind denoising.

PubMed

Rabie, Tamer

2005-11-01

This work develops a new robust statistical framework for blind image denoising. Robust statistics addresses the problem of estimation when the idealized assumptions about a system are occasionally violated. The contaminating noise in an image is considered as a violation of the assumption of spatial coherence of the image intensities and is treated as an outlier random variable. A denoised image is estimated by fitting a spatially coherent stationary image model to the available noisy data using a robust estimator-based regression method within an optimal-size adaptive window. The robust formulation aims at eliminating the noise outliers while preserving the edge structures in the restored image. Several examples demonstrating the effectiveness of this robust denoising technique are reported and a comparison with other standard denoising filters is presented.

Automated tumor analysis for molecular profiling in lung cancer

PubMed Central

Boyd, Clinton; James, Jacqueline A.; Loughrey, Maurice B.; Hougton, Joseph P.; Boyle, David P.; Kelly, Paul; Maxwell, Perry; McCleary, David; Diamond, James; McArt, Darragh G.; Tunstall, Jonathon; Bankhead, Peter; Salto-Tellez, Manuel

2015-01-01

The discovery and clinical application of molecular biomarkers in solid tumors, increasingly relies on nucleic acid extraction from FFPE tissue sections and subsequent molecular profiling. This in turn requires the pathological review of haematoxylin & eosin (H&E) stained slides, to ensure sample quality, tumor DNA sufficiency by visually estimating the percentage tumor nuclei and tumor annotation for manual macrodissection. In this study on NSCLC, we demonstrate considerable variation in tumor nuclei percentage between pathologists, potentially undermining the precision of NSCLC molecular evaluation and emphasising the need for quantitative tumor evaluation. We subsequently describe the development and validation of a system called TissueMark for automated tumor annotation and percentage tumor nuclei measurement in NSCLC using computerized image analysis. Evaluation of 245 NSCLC slides showed precise automated tumor annotation of cases using Tissuemark, strong concordance with manually drawn boundaries and identical EGFR mutational status, following manual macrodissection from the image analysis generated tumor boundaries. Automated analysis of cell counts for % tumor measurements by Tissuemark showed reduced variability and significant correlation (p < 0.001) with benchmark tumor cell counts. This study demonstrates a robust image analysis technology that can facilitate the automated quantitative analysis of tissue samples for molecular profiling in discovery and diagnostics. PMID:26317646

2015-2016 Palila abundance estimates

USGS Publications Warehouse

Camp, Richard J.; Brinck, Kevin W.; Banko, Paul C.

2016-01-01

The palila (Loxioides bailleui) population was surveyed annually during 1998−2016 on Mauna Kea Volcano to determine abundance, population trend, and spatial distribution. In the latest surveys, the 2015 population was estimated at 852−1,406 birds (point estimate: 1,116) and the 2016 population was estimated at 1,494−2,385 (point estimate: 1,934). Similar numbers of palila were detected during the first and subsequent counts within each year during 2012−2016; the proportion of the total annual detections in each count ranged from 46% to 56%; and there was no difference in the detection probability due to count sequence. Furthermore, conducting repeat counts improved the abundance estimates by reducing the width of the confidence intervals between 9% and 32% annually. This suggests that multiple counts do not affect bird or observer behavior and can be continued in the future to improve the precision of abundance estimates. Five palila were detected on supplemental survey stations in the Ka‘ohe restoration area, outside the core survey area but still within Palila Critical Habitat (one in 2015 and four in 2016), suggesting that palila are present in habitat that is recovering from cattle grazing on the southwest slope. The average rate of decline during 1998−2016 was 150 birds per year. Over the 18-year monitoring period, the estimated rate of change equated to a 58% decline in the population.

Reliability of Classifying Multiple Sclerosis Disease Activity Using Magnetic Resonance Imaging in a Multiple Sclerosis Clinic

PubMed Central

Altay, Ebru Erbayat; Fisher, Elizabeth; Jones, Stephen E.; Hara-Cleaver, Claire; Lee, Jar-Chi; Rudick, Richard A.

2013-01-01

Objective To assess the reliability of new magnetic resonance imaging (MRI) lesion counts by clinicians in a multiple sclerosis specialty clinic. Design An observational study. Setting A multiple sclerosis specialty clinic. Patients Eighty-five patients with multiple sclerosis participating in a National Institutes of Health–supported longitudinal study were included. Intervention Each patient had a brain MRI scan at entry and 6 months later using a standardized protocol. Main Outcome Measures The number of new T2 lesions, newly enlarging T2 lesions, and gadolinium-enhancing lesions were measured on the 6-month MRI using a computer-based image analysis program for the original study. For this study, images were reanalyzed by an expert neuroradiologist and 3 clinician raters. The neuroradiologist evaluated the original image pairs; the clinicians evaluated image pairs that were modified to simulate clinical practice. New lesion counts were compared across raters, as was classification of patients as MRI active or inactive. Results Agreement on lesion counts was highest for gadolinium-enhancing lesions, intermediate for new T2 lesions, and poor for enlarging T2 lesions. In 18% to 25% of the cases, MRI activity was classified differently by the clinician raters compared with the neuroradiologist or computer program. Variability among the clinical raters for estimates of new T2 lesions was affected most strongly by the image modifications that simulated low image quality and different head position. Conclusions Between-rater variability in new T2 lesion counts may be reduced by improved standardization of image acquisitions, but this approach may not be practical in most clinical environments. Ultimately, more reliable, robust, and accessible image analysis methods are needed for accurate multiple sclerosis disease-modifying drug monitoring and decision making in the routine clinic setting. PMID:23599930

A new model to predict weak-lensing peak counts. II. Parameter constraint strategies

NASA Astrophysics Data System (ADS)

Lin, Chieh-An; Kilbinger, Martin

2015-11-01

Context. Peak counts have been shown to be an excellent tool for extracting the non-Gaussian part of the weak lensing signal. Recently, we developed a fast stochastic forward model to predict weak-lensing peak counts. Our model is able to reconstruct the underlying distribution of observables for analysis. Aims: In this work, we explore and compare various strategies for constraining a parameter using our model, focusing on the matter density Ωm and the density fluctuation amplitude σ8. Methods: First, we examine the impact from the cosmological dependency of covariances (CDC). Second, we perform the analysis with the copula likelihood, a technique that makes a weaker assumption than does the Gaussian likelihood. Third, direct, non-analytic parameter estimations are applied using the full information of the distribution. Fourth, we obtain constraints with approximate Bayesian computation (ABC), an efficient, robust, and likelihood-free algorithm based on accept-reject sampling. Results: We find that neglecting the CDC effect enlarges parameter contours by 22% and that the covariance-varying copula likelihood is a very good approximation to the true likelihood. The direct techniques work well in spite of noisier contours. Concerning ABC, the iterative process converges quickly to a posterior distribution that is in excellent agreement with results from our other analyses. The time cost for ABC is reduced by two orders of magnitude. Conclusions: The stochastic nature of our weak-lensing peak count model allows us to use various techniques that approach the true underlying probability distribution of observables, without making simplifying assumptions. Our work can be generalized to other observables where forward simulations provide samples of the underlying distribution.

The comparison between several robust ridge regression estimators in the presence of multicollinearity and multiple outliers

NASA Astrophysics Data System (ADS)

Zahari, Siti Meriam; Ramli, Norazan Mohamed; Moktar, Balkiah; Zainol, Mohammad Said

2014-09-01

In the presence of multicollinearity and multiple outliers, statistical inference of linear regression model using ordinary least squares (OLS) estimators would be severely affected and produces misleading results. To overcome this, many approaches have been investigated. These include robust methods which were reported to be less sensitive to the presence of outliers. In addition, ridge regression technique was employed to tackle multicollinearity problem. In order to mitigate both problems, a combination of ridge regression and robust methods was discussed in this study. The superiority of this approach was examined when simultaneous presence of multicollinearity and multiple outliers occurred in multiple linear regression. This study aimed to look at the performance of several well-known robust estimators; M, MM, RIDGE and robust ridge regression estimators, namely Weighted Ridge M-estimator (WRM), Weighted Ridge MM (WRMM), Ridge MM (RMM), in such a situation. Results of the study showed that in the presence of simultaneous multicollinearity and multiple outliers (in both x and y-direction), the RMM and RIDGE are more or less similar in terms of superiority over the other estimators, regardless of the number of observation, level of collinearity and percentage of outliers used. However, when outliers occurred in only single direction (y-direction), the WRMM estimator is the most superior among the robust ridge regression estimators, by producing the least variance. In conclusion, the robust ridge regression is the best alternative as compared to robust and conventional least squares estimators when dealing with simultaneous presence of multicollinearity and outliers.

A frequency-domain estimator for use in adaptive control systems

NASA Technical Reports Server (NTRS)

Lamaire, Richard O.; Valavani, Lena; Athans, Michael; Stein, Gunter

1991-01-01

This paper presents a frequency-domain estimator that can identify both a parametrized nominal model of a plant as well as a frequency-domain bounding function on the modeling error associated with this nominal model. This estimator, which we call a robust estimator, can be used in conjunction with a robust control-law redesign algorithm to form a robust adaptive controller.

Can children with Type 1 diabetes and their caregivers estimate the carbohydrate content of meals and snacks?

PubMed

Smart, C E; Ross, K; Edge, J A; King, B R; McElduff, P; Collins, C E

2010-03-01

Carbohydrate (CHO) counting allows children with Type 1 diabetes to adjust mealtime insulin dose to carbohydrate intake. Little is known about the ability of children to count CHO and whether a particular method for assessing CHO quantity is better than others. We investigated how accurately children and their caregivers estimate carbohydrate, and whether counting in gram increments improves accuracy compared with CHO portions or exchanges. One hundred and two children and adolescents (age range 8.3-18.1 years) on intensive insulin therapy and 110 caregivers independently estimated the CHO content of 17 standardized meals (containing 8-90 g CHO), using whichever method of carbohydrate quantification they had been taught (gram increments, 10-g portions or 15-g exchanges). Seventy-three per cent (n = 2530) of all estimates were within 10-15 g of actual CHO content. There was no relationship between the mean percentage error and method of carbohydrate counting or glycated haemoglobin (HbA(1c)) (P > 0.05). Mean gram error and meal size were negatively correlated (r = -0.70, P < 0.0001). The longer children had been CHO counting the greater the mean percentage error (r = 0.173, P = 0.014). Core foods in non-standard quantities were most frequently inaccurately estimated, while individually labelled foods were most often accurately estimated. Children with Type 1 diabetes and their caregivers can estimate the carbohydrate content of meals with reasonable accuracy. Teaching CHO counting in gram increments did not improve accuracy compared with CHO portions or exchanges. Large meals tended to be underestimated and snacks overestimated. Repeated age-appropriate education appears necessary to maintain accuracy in carbohydrate estimations.

Risk of poor development in young children in low-income and middle-income countries: an estimation and analysis at the global, regional, and country level.

PubMed

Lu, Chunling; Black, Maureen M; Richter, Linda M

2016-12-01

A 2007 study published in The Lancet estimated that approximately 219 million children aged younger than 5 years were exposed to stunting or extreme poverty in 2004. We updated the 2004 estimates with the use of improved data and methods and generated estimates for 2010. We used country-level prevalence of stunting in children younger than 5 years based on the 2006 Growth Standards proposed by WHO and poverty ratios from the World Bank to estimate children who were either stunted or lived in extreme poverty for 141 low-income and middle-income countries in 2004 and 2010. To avoid counting the same children twice, we excluded children jointly exposed to stunting and extreme poverty from children living in extreme poverty. To examine the robustness of estimates, we also used moderate poverty measures. The 2007 study underestimated children at risk of poor development. The estimated number of children exposed to the two risk factors in low-income and middle-income countries decreased from 279·1 million (95% CI 250·4 million-307·4 million) in 2004 to 249·4 million (209·3 million-292·6 million) in 2010; prevalence of children at risk fell from 51% (95% CI 46-56) to 43% (36-51). The decline occurred in all income groups and regions with south Asia experiencing the largest drop. Sub-Saharan Africa had the highest prevalence in both years. These findings were robust to variations in poverty measures. Progress has been made in reducing the number of children exposed to stunting or poverty between 2004 and 2010, but this is still not enough. Scaling up of effective interventions targeting the most vulnerable children is urgently needed. National Institutes of Health, Bill & Melinda Gates Foundation, Hilton Foundation, and WHO. Copyright © 2016 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND license. Published by Elsevier Ltd.. All rights reserved.

Incorporating harvest rates into the sex-age-kill model for white-tailed deer

USGS Publications Warehouse

Norton, Andrew S.; Diefenbach, Duane R.; Rosenberry, Christopher S.; Wallingford, Bret D.

2013-01-01

Although monitoring population trends is an essential component of game species management, wildlife managers rarely have complete counts of abundance. Often, they rely on population models to monitor population trends. As imperfect representations of real-world populations, models must be rigorously evaluated to be applied appropriately. Previous research has evaluated population models for white-tailed deer (Odocoileus virginianus); however, the precision and reliability of these models when tested against empirical measures of variability and bias largely is untested. We were able to statistically evaluate the Pennsylvania sex-age-kill (PASAK) population model using realistic error measured using data from 1,131 radiocollared white-tailed deer in Pennsylvania from 2002 to 2008. We used these data and harvest data (number killed, age-sex structure, etc.) to estimate precision of abundance estimates, identify the most efficient harvest data collection with respect to precision of parameter estimates, and evaluate PASAK model robustness to violation of assumptions. Median coefficient of variation (CV) estimates by Wildlife Management Unit, 13.2% in the most recent year, were slightly above benchmarks recommended for managing game species populations. Doubling reporting rates by hunters or doubling the number of deer checked by personnel in the field reduced median CVs to recommended levels. The PASAK model was robust to errors in estimates for adult male harvest rates but was sensitive to errors in subadult male harvest rates, especially in populations with lower harvest rates. In particular, an error in subadult (1.5-yr-old) male harvest rates resulted in the opposite error in subadult male, adult female, and juvenile population estimates. Also, evidence of a greater harvest probability for subadult female deer when compared with adult (≥2.5-yr-old) female deer resulted in a 9.5% underestimate of the population using the PASAK model. Because obtaining appropriate sample sizes, by management unit, to estimate harvest rate parameters each year may be too expensive, assumptions of constant annual harvest rates may be necessary. However, if changes in harvest regulations or hunter behavior influence subadult male harvest rates, the PASAK model could provide an unreliable index to population changes. 

A removal model for estimating detection probabilities from point-count surveys

USGS Publications Warehouse

Farnsworth, G.L.; Pollock, K.H.; Nichols, J.D.; Simons, T.R.; Hines, J.E.; Sauer, J.R.

2002-01-01

Use of point-count surveys is a popular method for collecting data on abundance and distribution of birds. However, analyses of such data often ignore potential differences in detection probability. We adapted a removal model to directly estimate detection probability during point-count surveys. The model assumes that singing frequency is a major factor influencing probability of detection when birds are surveyed using point counts. This may be appropriate for surveys in which most detections are by sound. The model requires counts to be divided into several time intervals. Point counts are often conducted for 10 min, where the number of birds recorded is divided into those first observed in the first 3 min, the subsequent 2 min, and the last 5 min. We developed a maximum-likelihood estimator for the detectability of birds recorded during counts divided into those intervals. This technique can easily be adapted to point counts divided into intervals of any length. We applied this method to unlimited-radius counts conducted in Great Smoky Mountains National Park. We used model selection criteria to identify whether detection probabilities varied among species, throughout the morning, throughout the season, and among different observers. We found differences in detection probability among species. Species that sing frequently such as Winter Wren (Troglodytes troglodytes) and Acadian Flycatcher (Empidonax virescens) had high detection probabilities (∼90%) and species that call infrequently such as Pileated Woodpecker (Dryocopus pileatus) had low detection probability (36%). We also found detection probabilities varied with the time of day for some species (e.g. thrushes) and between observers for other species. We used the same approach to estimate detection probability and density for a subset of the observations with limited-radius point counts.

Point counts from clustered populations: Lessons from an experiment with Hawaiian crows

USGS Publications Warehouse

Hayward, G.D.; Kepler, C.B.; Scott, J.M.

1991-01-01

We designed an experiment to identify factors contributing most to error in counts of Hawaiian Crow or Alala (Corvus hawaiiensis) groups that are detected aurally. Seven observers failed to detect calling Alala on 197 of 361 3-min point counts on four transects extending from cages with captive Alala. A detection curve describing the relation between frequency of flock detection and distance typified the distribution expected in transect or point counts. Failure to detect calling Alala was affected most by distance, observer, and Alala calling frequency. The number of individual Alala calling was not important in detection rate. Estimates of the number of Alala calling (flock size) were biased and imprecise: average difference between number of Alala calling and number heard was 3.24 (.+-. 0.277). Distance, observer, number of Alala calling, and Alala calling frequency all contributed to errors in estimates of group size (P < 0.0001). Multiple regression suggested that number of Alala calling contributed most to errors. These results suggest that well-designed point counts may be used to estimate the number of Alala flocks but cast doubt on attempts to estimate flock size when individuals are counted aurally.

Do bacterial cell numbers follow a theoretical Poisson distribution? Comparison of experimentally obtained numbers of single cells with random number generation via computer simulation.

PubMed

Koyama, Kento; Hokunan, Hidekazu; Hasegawa, Mayumi; Kawamura, Shuso; Koseki, Shigenobu

2016-12-01

We investigated a bacterial sample preparation procedure for single-cell studies. In the present study, we examined whether single bacterial cells obtained via 10-fold dilution followed a theoretical Poisson distribution. Four serotypes of Salmonella enterica, three serotypes of enterohaemorrhagic Escherichia coli and one serotype of Listeria monocytogenes were used as sample bacteria. An inoculum of each serotype was prepared via a 10-fold dilution series to obtain bacterial cell counts with mean values of one or two. To determine whether the experimentally obtained bacterial cell counts follow a theoretical Poisson distribution, a likelihood ratio test between the experimentally obtained cell counts and Poisson distribution which parameter estimated by maximum likelihood estimation (MLE) was conducted. The bacterial cell counts of each serotype sufficiently followed a Poisson distribution. Furthermore, to examine the validity of the parameters of Poisson distribution from experimentally obtained bacterial cell counts, we compared these with the parameters of a Poisson distribution that were estimated using random number generation via computer simulation. The Poisson distribution parameters experimentally obtained from bacterial cell counts were within the range of the parameters estimated using a computer simulation. These results demonstrate that the bacterial cell counts of each serotype obtained via 10-fold dilution followed a Poisson distribution. The fact that the frequency of bacterial cell counts follows a Poisson distribution at low number would be applied to some single-cell studies with a few bacterial cells. In particular, the procedure presented in this study enables us to develop an inactivation model at the single-cell level that can estimate the variability of survival bacterial numbers during the bacterial death process. Copyright © 2016 Elsevier Ltd. All rights reserved.

Trends in one-year cumulative incidence of death between 2005 and 2013 among patients initiating antiretroviral therapy in Uganda.

PubMed

Bebell, Lisa M; Siedner, Mark J; Musinguzi, Nicholas; Boum, Yap; Bwana, Bosco M; Muyindike, Winnie; Hunt, Peter W; Martin, Jeffrey N; Bangsberg, David R

2017-07-01

Recent ecological data demonstrate improving outcomes for HIV-infected people in sub-Saharan Africa. Recently, Uganda has experienced a resurgence in HIV incidence and prevalence, but trends in HIV-related deaths have not been well described. Data were collected through the Uganda AIDS Rural Treatment Outcomes (UARTO) Study, an observational longitudinal cohort of Ugandan adults initiating antiretroviral therapy (ART) between 2005 and 2013. We calculated cumulative incidence of death within one year of ART initiation, and fit Poisson models with robust variance estimators to estimate the effect enrollment period on one-year risk of death and loss to follow-up. Of 760 persons in UARTO who started ART, 30 deaths occurred within one year of ART initiation (cumulative incidence 3.9%, 95% confidence interval [CI] 2.7-5.6%). Risk of death was highest for those starting ART in 2005 (13.0%, 95% CI 6.0-24.0%), decreased in 2006-2007 to 4% (95% CI 2.0-6.0%), and did not change thereafter ( P = 0.61). These results were robust to adjustment for age, sex, CD4 cell count, viral load, asset wealth, baseline depression, and body mass index. Here, we demonstrate that one-year cumulative incidence of death was high just after free ART rollout, decreased the following year, and remained low thereafter. Once established, ART programs in President's Emergency Fund for AIDS Relief-supported countries can maintain high quality care.

Comparison of Drive Counts and Mark-Resight As Methods of Population Size Estimation of Highly Dense Sika Deer (Cervus nippon) Populations.

PubMed

Takeshita, Kazutaka; Ikeda, Takashi; Takahashi, Hiroshi; Yoshida, Tsuyoshi; Igota, Hiromasa; Matsuura, Yukiko; Kaji, Koichi

2016-01-01

Assessing temporal changes in abundance indices is an important issue in the management of large herbivore populations. The drive counts method has been frequently used as a deer abundance index in mountainous regions. However, despite an inherent risk for observation errors in drive counts, which increase with deer density, evaluations of the utility of drive counts at a high deer density remain scarce. We compared the drive counts and mark-resight (MR) methods in the evaluation of a highly dense sika deer population (MR estimates ranged between 11 and 53 individuals/km2) on Nakanoshima Island, Hokkaido, Japan, between 1999 and 2006. This deer population experienced two large reductions in density; approximately 200 animals in total were taken from the population through a large-scale population removal and a separate winter mass mortality event. Although the drive counts tracked temporal changes in deer abundance on the island, they overestimated the counts for all years in comparison to the MR method. Increased overestimation in drive count estimates after the winter mass mortality event may be due to a double count derived from increased deer movement and recovery of body condition secondary to the mitigation of density-dependent food limitations. Drive counts are unreliable because they are affected by unfavorable factors such as bad weather, and they are cost-prohibitive to repeat, which precludes the calculation of confidence intervals. Therefore, the use of drive counts to infer the deer abundance needs to be reconsidered.

Fast clustering using adaptive density peak detection.

PubMed

Wang, Xiao-Feng; Xu, Yifan

2017-12-01

Common limitations of clustering methods include the slow algorithm convergence, the instability of the pre-specification on a number of intrinsic parameters, and the lack of robustness to outliers. A recent clustering approach proposed a fast search algorithm of cluster centers based on their local densities. However, the selection of the key intrinsic parameters in the algorithm was not systematically investigated. It is relatively difficult to estimate the "optimal" parameters since the original definition of the local density in the algorithm is based on a truncated counting measure. In this paper, we propose a clustering procedure with adaptive density peak detection, where the local density is estimated through the nonparametric multivariate kernel estimation. The model parameter is then able to be calculated from the equations with statistical theoretical justification. We also develop an automatic cluster centroid selection method through maximizing an average silhouette index. The advantage and flexibility of the proposed method are demonstrated through simulation studies and the analysis of a few benchmark gene expression data sets. The method only needs to perform in one single step without any iteration and thus is fast and has a great potential to apply on big data analysis. A user-friendly R package ADPclust is developed for public use.

Adjusting for background mutation frequency biases improves the identification of cancer driver genes.

PubMed

Evans, Perry; Avey, Stefan; Kong, Yong; Krauthammer, Michael

2013-09-01

A common goal of tumor sequencing projects is finding genes whose mutations are selected for during tumor development. This is accomplished by choosing genes that have more non-synonymous mutations than expected from an estimated background mutation frequency. While this background frequency is unknown, it can be estimated using both the observed synonymous mutation frequency and the non-synonymous to synonymous mutation ratio. The synonymous mutation frequency can be determined across all genes or in a gene-specific manner. This choice introduces an interesting trade-off. A gene-specific frequency adjusts for an underlying mutation bias, but is difficult to estimate given missing synonymous mutation counts. Using a genome-wide synonymous frequency is more robust, but is less suited for adjusting biases. Studying four evaluation criteria for identifying genes with high non-synonymous mutation burden (reflecting preferential selection of expressed genes, genes with mutations in conserved bases, genes with many protein interactions, and genes that show loss of heterozygosity), we find that the gene-specific synonymous frequency is superior in the gene expression and protein interaction tests. In conclusion, the use of the gene-specific synonymous mutation frequency is well suited for assessing a gene's non-synonymous mutation burden.

Variable selection for zero-inflated and overdispersed data with application to health care demand in Germany.

PubMed

Wang, Zhu; Ma, Shuangge; Wang, Ching-Yun

2015-09-01

In health services and outcome research, count outcomes are frequently encountered and often have a large proportion of zeros. The zero-inflated negative binomial (ZINB) regression model has important applications for this type of data. With many possible candidate risk factors, this paper proposes new variable selection methods for the ZINB model. We consider maximum likelihood function plus a penalty including the least absolute shrinkage and selection operator (LASSO), smoothly clipped absolute deviation (SCAD), and minimax concave penalty (MCP). An EM (expectation-maximization) algorithm is proposed for estimating the model parameters and conducting variable selection simultaneously. This algorithm consists of estimating penalized weighted negative binomial models and penalized logistic models via the coordinated descent algorithm. Furthermore, statistical properties including the standard error formulae are provided. A simulation study shows that the new algorithm not only has more accurate or at least comparable estimation, but also is more robust than the traditional stepwise variable selection. The proposed methods are applied to analyze the health care demand in Germany using the open-source R package mpath. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Platelet Counts in Insoluble Platelet-Rich Fibrin Clots: A Direct Method for Accurate Determination.

PubMed

Kitamura, Yutaka; Watanabe, Taisuke; Nakamura, Masayuki; Isobe, Kazushige; Kawabata, Hideo; Uematsu, Kohya; Okuda, Kazuhiro; Nakata, Koh; Tanaka, Takaaki; Kawase, Tomoyuki

2018-01-01

Platelet-rich fibrin (PRF) clots have been used in regenerative dentistry most often, with the assumption that growth factor levels are concentrated in proportion to the platelet concentration. Platelet counts in PRF are generally determined indirectly by platelet counting in other liquid fractions. This study shows a method for direct estimation of platelet counts in PRF. To validate this method by determination of the recovery rate, whole-blood samples were obtained with an anticoagulant from healthy donors, and platelet-rich plasma (PRP) fractions were clotted with CaCl 2 by centrifugation and digested with tissue-plasminogen activator. Platelet counts were estimated before clotting and after digestion using an automatic hemocytometer. The method was then tested on PRF clots. The quality of platelets was examined by scanning electron microscopy and flow cytometry. In PRP-derived fibrin matrices, the recovery rate of platelets and white blood cells was 91.6 and 74.6%, respectively, after 24 h of digestion. In PRF clots associated with small and large red thrombi, platelet counts were 92.6 and 67.2% of the respective total platelet counts. These findings suggest that our direct method is sufficient for estimating the number of platelets trapped in an insoluble fibrin matrix and for determining that platelets are distributed in PRF clots and red thrombi roughly in proportion to their individual volumes. Therefore, we propose this direct digestion method for more accurate estimation of platelet counts in most types of platelet-enriched fibrin matrix.

Platelet Counts in Insoluble Platelet-Rich Fibrin Clots: A Direct Method for Accurate Determination

PubMed Central

Kitamura, Yutaka; Watanabe, Taisuke; Nakamura, Masayuki; Isobe, Kazushige; Kawabata, Hideo; Uematsu, Kohya; Okuda, Kazuhiro; Nakata, Koh; Tanaka, Takaaki; Kawase, Tomoyuki

2018-01-01

Platelet-rich fibrin (PRF) clots have been used in regenerative dentistry most often, with the assumption that growth factor levels are concentrated in proportion to the platelet concentration. Platelet counts in PRF are generally determined indirectly by platelet counting in other liquid fractions. This study shows a method for direct estimation of platelet counts in PRF. To validate this method by determination of the recovery rate, whole-blood samples were obtained with an anticoagulant from healthy donors, and platelet-rich plasma (PRP) fractions were clotted with CaCl2 by centrifugation and digested with tissue-plasminogen activator. Platelet counts were estimated before clotting and after digestion using an automatic hemocytometer. The method was then tested on PRF clots. The quality of platelets was examined by scanning electron microscopy and flow cytometry. In PRP-derived fibrin matrices, the recovery rate of platelets and white blood cells was 91.6 and 74.6%, respectively, after 24 h of digestion. In PRF clots associated with small and large red thrombi, platelet counts were 92.6 and 67.2% of the respective total platelet counts. These findings suggest that our direct method is sufficient for estimating the number of platelets trapped in an insoluble fibrin matrix and for determining that platelets are distributed in PRF clots and red thrombi roughly in proportion to their individual volumes. Therefore, we propose this direct digestion method for more accurate estimation of platelet counts in most types of platelet-enriched fibrin matrix. PMID:29450197

Data analysis in emission tomography using emission-count posteriors

NASA Astrophysics Data System (ADS)

Sitek, Arkadiusz

2012-11-01

A novel approach to the analysis of emission tomography data using the posterior probability of the number of emissions per voxel (emission count) conditioned on acquired tomographic data is explored. The posterior is derived from the prior and the Poisson likelihood of the emission-count data by marginalizing voxel activities. Based on emission-count posteriors, examples of Bayesian analysis including estimation and classification tasks in emission tomography are provided. The application of the method to computer simulations of 2D tomography is demonstrated. In particular, the minimum-mean-square-error point estimator of the emission count is demonstrated. The process of finding this estimator can be considered as a tomographic image reconstruction technique since the estimates of the number of emissions per voxel divided by voxel sensitivities and acquisition time are the estimates of the voxel activities. As an example of a classification task, a hypothesis stating that some region of interest (ROI) emitted at least or at most r-times the number of events in some other ROI is tested. The ROIs are specified by the user. The analysis described in this work provides new quantitative statistical measures that can be used in decision making in diagnostic imaging using emission tomography.

Robust linear discriminant models to solve financial crisis in banking sectors

NASA Astrophysics Data System (ADS)

Lim, Yai-Fung; Yahaya, Sharipah Soaad Syed; Idris, Faoziah; Ali, Hazlina; Omar, Zurni

2014-12-01

Linear discriminant analysis (LDA) is a widely-used technique in patterns classification via an equation which will minimize the probability of misclassifying cases into their respective categories. However, the performance of classical estimators in LDA highly depends on the assumptions of normality and homoscedasticity. Several robust estimators in LDA such as Minimum Covariance Determinant (MCD), S-estimators and Minimum Volume Ellipsoid (MVE) are addressed by many authors to alleviate the problem of non-robustness of the classical estimates. In this paper, we investigate on the financial crisis of the Malaysian banking institutions using robust LDA and classical LDA methods. Our objective is to distinguish the "distress" and "non-distress" banks in Malaysia by using the LDA models. Hit ratio is used to validate the accuracy predictive of LDA models. The performance of LDA is evaluated by estimating the misclassification rate via apparent error rate. The results and comparisons show that the robust estimators provide a better performance than the classical estimators for LDA.

Robust Fault Detection Using Robust Z1 Estimation and Fuzzy Logic

NASA Technical Reports Server (NTRS)

Curry, Tramone; Collins, Emmanuel G., Jr.; Selekwa, Majura; Guo, Ten-Huei (Technical Monitor)

2001-01-01

This research considers the application of robust Z(sub 1), estimation in conjunction with fuzzy logic to robust fault detection for an aircraft fight control system. It begins with the development of robust Z(sub 1) estimators based on multiplier theory and then develops a fixed threshold approach to fault detection (FD). It then considers the use of fuzzy logic for robust residual evaluation and FD. Due to modeling errors and unmeasurable disturbances, it is difficult to distinguish between the effects of an actual fault and those caused by uncertainty and disturbance. Hence, it is the aim of a robust FD system to be sensitive to faults while remaining insensitive to uncertainty and disturbances. While fixed thresholds only allow a decision on whether a fault has or has not occurred, it is more valuable to have the residual evaluation lead to a conclusion related to the degree of, or probability of, a fault. Fuzzy logic is a viable means of determining the degree of a fault and allows the introduction of human observations that may not be incorporated in the rigorous threshold theory. Hence, fuzzy logic can provide a more reliable and informative fault detection process. Using an aircraft flight control system, the results of FD using robust Z(sub 1) estimation with a fixed threshold are demonstrated. FD that combines robust Z(sub 1) estimation and fuzzy logic is also demonstrated. It is seen that combining the robust estimator with fuzzy logic proves to be advantageous in increasing the sensitivity to smaller faults while remaining insensitive to uncertainty and disturbances.

Multivariate poisson lognormal modeling of crashes by type and severity on rural two lane highways.

PubMed

Wang, Kai; Ivan, John N; Ravishanker, Nalini; Jackson, Eric

2017-02-01

In an effort to improve traffic safety, there has been considerable interest in estimating crash prediction models and identifying factors contributing to crashes. To account for crash frequency variations among crash types and severities, crash prediction models have been estimated by type and severity. The univariate crash count models have been used by researchers to estimate crashes by crash type or severity, in which the crash counts by type or severity are assumed to be independent of one another and modelled separately. When considering crash types and severities simultaneously, this may neglect the potential correlations between crash counts due to the presence of shared unobserved factors across crash types or severities for a specific roadway intersection or segment, and might lead to biased parameter estimation and reduce model accuracy. The focus on this study is to estimate crashes by both crash type and crash severity using the Integrated Nested Laplace Approximation (INLA) Multivariate Poisson Lognormal (MVPLN) model, and identify the different effects of contributing factors on different crash type and severity counts on rural two-lane highways. The INLA MVPLN model can simultaneously model crash counts by crash type and crash severity by accounting for the potential correlations among them and significantly decreases the computational time compared with a fully Bayesian fitting of the MVPLN model using Markov Chain Monte Carlo (MCMC) method. This paper describes estimation of MVPLN models for three-way stop controlled (3ST) intersections, four-way stop controlled (4ST) intersections, four-way signalized (4SG) intersections, and roadway segments on rural two-lane highways. Annual Average Daily traffic (AADT) and variables describing roadway conditions (including presence of lighting, presence of left-turn/right-turn lane, lane width and shoulder width) were used as predictors. A Univariate Poisson Lognormal (UPLN) was estimated by crash type and severity for each highway facility, and their prediction results are compared with the MVPLN model based on the Average Predicted Mean Absolute Error (APMAE) statistic. A UPLN model for total crashes was also estimated to compare the coefficients of contributing factors with the models that estimate crashes by crash type and severity. The model coefficient estimates show that the signs of coefficients for presence of left-turn lane, presence of right-turn lane, land width and speed limit are different across crash type or severity counts, which suggest that estimating crashes by crash type or severity might be more helpful in identifying crash contributing factors. The standard errors of covariates in the MVPLN model are slightly lower than the UPLN model when the covariates are statistically significant, and the crash counts by crash type and severity are significantly correlated. The model prediction comparisons illustrate that the MVPLN model outperforms the UPLN model in prediction accuracy. Therefore, when predicting crash counts by crash type and crash severity for rural two-lane highways, the MVPLN model should be considered to avoid estimation error and to account for the potential correlations among crash type counts and crash severity counts. Copyright © 2016 Elsevier Ltd. All rights reserved.

Power estimation using simulations for air pollution time-series studies

PubMed Central

2012-01-01

Background Estimation of power to assess associations of interest can be challenging for time-series studies of the acute health effects of air pollution because there are two dimensions of sample size (time-series length and daily outcome counts), and because these studies often use generalized linear models to control for complex patterns of covariation between pollutants and time trends, meteorology and possibly other pollutants. In general, statistical software packages for power estimation rely on simplifying assumptions that may not adequately capture this complexity. Here we examine the impact of various factors affecting power using simulations, with comparison of power estimates obtained from simulations with those obtained using statistical software. Methods Power was estimated for various analyses within a time-series study of air pollution and emergency department visits using simulations for specified scenarios. Mean daily emergency department visit counts, model parameter value estimates and daily values for air pollution and meteorological variables from actual data (8/1/98 to 7/31/99 in Atlanta) were used to generate simulated daily outcome counts with specified temporal associations with air pollutants and randomly generated error based on a Poisson distribution. Power was estimated by conducting analyses of the association between simulated daily outcome counts and air pollution in 2000 data sets for each scenario. Power estimates from simulations and statistical software (G*Power and PASS) were compared. Results In the simulation results, increasing time-series length and average daily outcome counts both increased power to a similar extent. Our results also illustrate the low power that can result from using outcomes with low daily counts or short time series, and the reduction in power that can accompany use of multipollutant models. Power estimates obtained using standard statistical software were very similar to those from the simulations when properly implemented; implementation, however, was not straightforward. Conclusions These analyses demonstrate the similar impact on power of increasing time-series length versus increasing daily outcome counts, which has not previously been reported. Implementation of power software for these studies is discussed and guidance is provided. PMID:22995599

Power estimation using simulations for air pollution time-series studies.

PubMed

Winquist, Andrea; Klein, Mitchel; Tolbert, Paige; Sarnat, Stefanie Ebelt

2012-09-20

Estimation of power to assess associations of interest can be challenging for time-series studies of the acute health effects of air pollution because there are two dimensions of sample size (time-series length and daily outcome counts), and because these studies often use generalized linear models to control for complex patterns of covariation between pollutants and time trends, meteorology and possibly other pollutants. In general, statistical software packages for power estimation rely on simplifying assumptions that may not adequately capture this complexity. Here we examine the impact of various factors affecting power using simulations, with comparison of power estimates obtained from simulations with those obtained using statistical software. Power was estimated for various analyses within a time-series study of air pollution and emergency department visits using simulations for specified scenarios. Mean daily emergency department visit counts, model parameter value estimates and daily values for air pollution and meteorological variables from actual data (8/1/98 to 7/31/99 in Atlanta) were used to generate simulated daily outcome counts with specified temporal associations with air pollutants and randomly generated error based on a Poisson distribution. Power was estimated by conducting analyses of the association between simulated daily outcome counts and air pollution in 2000 data sets for each scenario. Power estimates from simulations and statistical software (G*Power and PASS) were compared. In the simulation results, increasing time-series length and average daily outcome counts both increased power to a similar extent. Our results also illustrate the low power that can result from using outcomes with low daily counts or short time series, and the reduction in power that can accompany use of multipollutant models. Power estimates obtained using standard statistical software were very similar to those from the simulations when properly implemented; implementation, however, was not straightforward. These analyses demonstrate the similar impact on power of increasing time-series length versus increasing daily outcome counts, which has not previously been reported. Implementation of power software for these studies is discussed and guidance is provided.

New robust statistical procedures for the polytomous logistic regression models.

PubMed

Castilla, Elena; Ghosh, Abhik; Martin, Nirian; Pardo, Leandro

2018-05-17

This article derives a new family of estimators, namely the minimum density power divergence estimators, as a robust generalization of the maximum likelihood estimator for the polytomous logistic regression model. Based on these estimators, a family of Wald-type test statistics for linear hypotheses is introduced. Robustness properties of both the proposed estimators and the test statistics are theoretically studied through the classical influence function analysis. Appropriate real life examples are presented to justify the requirement of suitable robust statistical procedures in place of the likelihood based inference for the polytomous logistic regression model. The validity of the theoretical results established in the article are further confirmed empirically through suitable simulation studies. Finally, an approach for the data-driven selection of the robustness tuning parameter is proposed with empirical justifications. © 2018, The International Biometric Society.

A comparison of cosegregation analysis methods for the clinical setting.

PubMed

Rañola, John Michael O; Liu, Quanhui; Rosenthal, Elisabeth A; Shirts, Brian H

2018-04-01

Quantitative cosegregation analysis can help evaluate the pathogenicity of genetic variants. However, genetics professionals without statistical training often use simple methods, reporting only qualitative findings. We evaluate the potential utility of quantitative cosegregation in the clinical setting by comparing three methods. One thousand pedigrees each were simulated for benign and pathogenic variants in BRCA1 and MLH1 using United States historical demographic data to produce pedigrees similar to those seen in the clinic. These pedigrees were analyzed using two robust methods, full likelihood Bayes factors (FLB) and cosegregation likelihood ratios (CSLR), and a simpler method, counting meioses. Both FLB and CSLR outperform counting meioses when dealing with pathogenic variants, though counting meioses is not far behind. For benign variants, FLB and CSLR greatly outperform as counting meioses is unable to generate evidence for benign variants. Comparing FLB and CSLR, we find that the two methods perform similarly, indicating that quantitative results from either of these methods could be combined in multifactorial calculations. Combining quantitative information will be important as isolated use of cosegregation in single families will yield classification for less than 1% of variants. To encourage wider use of robust cosegregation analysis, we present a website ( http://www.analyze.myvariant.org ) which implements the CSLR, FLB, and Counting Meioses methods for ATM, BRCA1, BRCA2, CHEK2, MEN1, MLH1, MSH2, MSH6, and PMS2. We also present an R package, CoSeg, which performs the CSLR analysis on any gene with user supplied parameters. Future variant classification guidelines should allow nuanced inclusion of cosegregation evidence against pathogenicity.

Bird biodiversity assessments in temperate forest: the value of point count versus acoustic monitoring protocols.

PubMed

Klingbeil, Brian T; Willig, Michael R

2015-01-01

Effective monitoring programs for biodiversity are needed to assess trends in biodiversity and evaluate the consequences of management. This is particularly true for birds and faunas that occupy interior forest and other areas of low human population density, as these are frequently under-sampled compared to other habitats. For birds, Autonomous Recording Units (ARUs) have been proposed as a supplement or alternative to point counts made by human observers to enhance monitoring efforts. We employed two strategies (i.e., simultaneous-collection and same-season) to compare point count and ARU methods for quantifying species richness and composition of birds in temperate interior forests. The simultaneous-collection strategy compares surveys by ARUs and point counts, with methods matched in time, location, and survey duration such that the person and machine simultaneously collect data. The same-season strategy compares surveys from ARUs and point counts conducted at the same locations throughout the breeding season, but methods differ in the number, duration, and frequency of surveys. This second strategy more closely follows the ways in which monitoring programs are likely to be implemented. Site-specific estimates of richness (but not species composition) differed between methods; however, the nature of the relationship was dependent on the assessment strategy. Estimates of richness from point counts were greater than estimates from ARUs in the simultaneous-collection strategy. Woodpeckers in particular, were less frequently identified from ARUs than point counts with this strategy. Conversely, estimates of richness were lower from point counts than ARUs in the same-season strategy. Moreover, in the same-season strategy, ARUs detected the occurrence of passerines at a higher frequency than did point counts. Differences between ARU and point count methods were only detected in site-level comparisons. Importantly, both methods provide similar estimates of species richness and composition for the region. Consequently, if single visits to sites or short-term monitoring are the goal, point counts will likely perform better than ARUs, especially if species are rare or vocalize infrequently. However, if seasonal or annual monitoring of sites is the goal, ARUs offer a viable alternative to standard point-count methods, especially in the context of large-scale or long-term monitoring of temperate forest birds.

N-mixture models for estimating population size from spatially replicated counts

USGS Publications Warehouse

Royle, J. Andrew

2004-01-01

Spatial replication is a common theme in count surveys of animals. Such surveys often generate sparse count data from which it is difficult to estimate population size while formally accounting for detection probability. In this article, i describe a class of models (n-mixture models) which allow for estimation of population size from such data. The key idea is to view site-specific population sizes, n, as independent random variables distributed according to some mixing distribution (e.g., Poisson). Prior parameters are estimated from the marginal likelihood of the data, having integrated over the prior distribution for n. Carroll and lombard (1985, journal of american statistical association 80, 423-426) proposed a class of estimators based on mixing over a prior distribution for detection probability. Their estimator can be applied in limited settings, but is sensitive to prior parameter values that are fixed a priori. Spatial replication provides additional information regarding the parameters of the prior distribution on n that is exploited by the n-mixture models and which leads to reasonable estimates of abundance from sparse data. A simulation study demonstrates superior operating characteristics (bias, confidence interval coverage) of the n-mixture estimator compared to the caroll and lombard estimator. Both estimators are applied to point count data on six species of birds illustrating the sensitivity to choice of prior on p and substantially different estimates of abundance as a consequence.

Robust Alternatives to the Standard Deviation in Processing of Physics Experimental Data

NASA Astrophysics Data System (ADS)

Shulenin, V. P.

2016-10-01

Properties of robust estimations of the scale parameter are studied. It is noted that the median of absolute deviations and the modified estimation of the average Gini differences have asymptotically normal distributions and bounded influence functions, are B-robust estimations, and hence, unlike the estimation of the standard deviation, are protected from the presence of outliers in the sample. Results of comparison of estimations of the scale parameter are given for a Gaussian model with contamination. An adaptive variant of the modified estimation of the average Gini differences is considered.

Application of Multivariate Modeling for Radiation Injury Assessment: A Proof of Concept

PubMed Central

Bolduc, David L.; Villa, Vilmar; Sandgren, David J.; Ledney, G. David; Blakely, William F.; Bünger, Rolf

2014-01-01

Multivariate radiation injury estimation algorithms were formulated for estimating severe hematopoietic acute radiation syndrome (H-ARS) injury (i.e., response category three or RC3) in a rhesus monkey total-body irradiation (TBI) model. Classical CBC and serum chemistry blood parameters were examined prior to irradiation (d 0) and on d 7, 10, 14, 21, and 25 after irradiation involving 24 nonhuman primates (NHP) (Macaca mulatta) given 6.5-Gy 60Co Υ-rays (0.4 Gy min−1) TBI. A correlation matrix was formulated with the RC3 severity level designated as the “dependent variable” and independent variables down selected based on their radioresponsiveness and relatively low multicollinearity using stepwise-linear regression analyses. Final candidate independent variables included CBC counts (absolute number of neutrophils, lymphocytes, and platelets) in formulating the “CBC” RC3 estimation algorithm. Additionally, the formulation of a diagnostic CBC and serum chemistry “CBC-SCHEM” RC3 algorithm expanded upon the CBC algorithm model with the addition of hematocrit and the serum enzyme levels of aspartate aminotransferase, creatine kinase, and lactate dehydrogenase. Both algorithms estimated RC3 with over 90% predictive power. Only the CBC-SCHEM RC3 algorithm, however, met the critical three assumptions of linear least squares demonstrating slightly greater precision for radiation injury estimation, but with significantly decreased prediction error indicating increased statistical robustness. PMID:25165485

Robust location and spread measures for nonparametric probability density function estimation.

PubMed

López-Rubio, Ezequiel

2009-10-01

Robustness against outliers is a desirable property of any unsupervised learning scheme. In particular, probability density estimators benefit from incorporating this feature. A possible strategy to achieve this goal is to substitute the sample mean and the sample covariance matrix by more robust location and spread estimators. Here we use the L1-median to develop a nonparametric probability density function (PDF) estimator. We prove its most relevant properties, and we show its performance in density estimation and classification applications.

Post-precipitation bias in band-tailed pigeon surveys conducted at mineral sites

USGS Publications Warehouse

Overton, C.T.; Schmitz, R.A.; Casazza, Michael L.

2005-01-01

Many animal surveys to estimate populations or index trends include protocol prohibiting counts during rain but fail to address effects of rainfall preceding the count. Prior research on Pacific Coast band-tailed pigeons (Patagioenas fasciata monilis) documented declines in use of mineral sites during rainfall. We hypothesized that prior precipitation was associated with a short-term increase in use of mineral sites following rain. We conducted weekly counts of band-tailed pigeons at 19 Pacific Northwest mineral sites in 2001 and 20 sites in 2002. Results from regression analysis indicated higher counts ???2 days after rain (11.31??5.00% [x????SE]) compared to ???3 days. Individual index counts conducted ???2 days after rain were biased high, resulting in reduced ability to accurately estimate population trends. Models of band-tailed pigeon visitation rates throughout the summer showed increased mineral-site counts during both June and August migration periods, relative to the July breeding period. Our research supported previous studies recommending that mineral-site counts used to index the band-tailed pigeon population be conducted during July. We further recommend conducting counts >3 days after rain to avoid weather-related bias in index estimation. The design of other population sampling strategies that rely on annual counts should consider the influence of aberrant weather not only coincident with but also preceding surveys if weather patterns are thought to influence behavior or detection probability of target species.

Consideraciones para la estimacion de abundancia de poblaciones de mamiferos. [Considerations for the estimation of abundance of mammal populations.

USGS Publications Warehouse

Walker, R.S.; Novare, A.J.; Nichols, J.D.

2000-01-01

Estimation of abundance of mammal populations is essential for monitoring programs and for many ecological investigations. The first step for any study of variation in mammal abundance over space or time is to define the objectives of the study and how and why abundance data are to be used. The data used to estimate abundance are count statistics in the form of counts of animals or their signs. There are two major sources of uncertainty that must be considered in the design of the study: spatial variation and the relationship between abundance and the count statistic. Spatial variation in the distribution of animals or signs may be taken into account with appropriate spatial sampling. Count statistics may be viewed as random variables, with the expected value of the count statistic equal to the true abundance of the population multiplied by a coefficient p. With direct counts, p represents the probability of detection or capture of individuals, and with indirect counts it represents the rate of production of the signs as well as their probability of detection. Comparisons of abundance using count statistics from different times or places assume that the p are the same for all times or places being compared (p= pi). In spite of considerable evidence that this assumption rarely holds true, it is commonly made in studies of mammal abundance, as when the minimum number alive or indices based on sign counts are used to compare abundance in different habitats or times. Alternatives to relying on this assumption are to calibrate the index used by testing the assumption of p= pi, or to incorporate the estimation of p into the study design.

Comparison of point counts and territory mapping for detecting effects of forest management on songbirds

USGS Publications Warehouse

Newell, Felicity L.; Sheehan, James; Wood, Petra Bohall; Rodewald, Amanda D.; Buehler, David A.; Keyser, Patrick D.; Larkin, Jeffrey L.; Beachy, Tiffany A.; Bakermans, Marja H.; Boves, Than J.; Evans, Andrea; George, Gregory A.; McDermott, Molly E.; Perkins, Kelly A.; White, Matthew; Wigley, T. Bently

2013-01-01

Point counts are commonly used to assess changes in bird abundance, including analytical approaches such as distance sampling that estimate density. Point-count methods have come under increasing scrutiny because effects of detection probability and field error are difficult to quantify. For seven forest songbirds, we compared fixed-radii counts (50 m and 100 m) and density estimates obtained from distance sampling to known numbers of birds determined by territory mapping. We applied point-count analytic approaches to a typical forest management question and compared results to those obtained by territory mapping. We used a before–after control impact (BACI) analysis with a data set collected across seven study areas in the central Appalachians from 2006 to 2010. Using a 50-m fixed radius, variance in error was at least 1.5 times that of the other methods, whereas a 100-m fixed radius underestimated actual density by >3 territories per 10 ha for the most abundant species. Distance sampling improved accuracy and precision compared to fixed-radius counts, although estimates were affected by birds counted outside 10-ha units. In the BACI analysis, territory mapping detected an overall treatment effect for five of the seven species, and effects were generally consistent each year. In contrast, all point-count methods failed to detect two treatment effects due to variance and error in annual estimates. Overall, our results highlight the need for adequate sample sizes to reduce variance, and skilled observers to reduce the level of error in point-count data. Ultimately, the advantages and disadvantages of different survey methods should be considered in the context of overall study design and objectives, allowing for trade-offs among effort, accuracy, and power to detect treatment effects.

Statistical Aspects of Point Count Sampling

Treesearch

Richard J. Barker; John R. Sauer

1995-01-01

The dominant feature of point counts is that they do not census birds, but instead provide incomplete counts of individuals present within a survey plot. Considering a simple model for point count sampling, we demonstrate that use of these incomplete counts can bias estimators and testing procedures, leading to inappropriate conclusions. A large portion of the...

Comparison of robustness to outliers between robust poisson models and log-binomial models when estimating relative risks for common binary outcomes: a simulation study.

PubMed

Chen, Wansu; Shi, Jiaxiao; Qian, Lei; Azen, Stanley P

2014-06-26

To estimate relative risks or risk ratios for common binary outcomes, the most popular model-based methods are the robust (also known as modified) Poisson and the log-binomial regression. Of the two methods, it is believed that the log-binomial regression yields more efficient estimators because it is maximum likelihood based, while the robust Poisson model may be less affected by outliers. Evidence to support the robustness of robust Poisson models in comparison with log-binomial models is very limited. In this study a simulation was conducted to evaluate the performance of the two methods in several scenarios where outliers existed. The findings indicate that for data coming from a population where the relationship between the outcome and the covariate was in a simple form (e.g. log-linear), the two models yielded comparable biases and mean square errors. However, if the true relationship contained a higher order term, the robust Poisson models consistently outperformed the log-binomial models even when the level of contamination is low. The robust Poisson models are more robust (or less sensitive) to outliers compared to the log-binomial models when estimating relative risks or risk ratios for common binary outcomes. Users should be aware of the limitations when choosing appropriate models to estimate relative risks or risk ratios.

Comparison of Drive Counts and Mark-Resight As Methods of Population Size Estimation of Highly Dense Sika Deer (Cervus nippon) Populations

PubMed Central

Takeshita, Kazutaka; Yoshida, Tsuyoshi; Igota, Hiromasa; Matsuura, Yukiko

2016-01-01

Assessing temporal changes in abundance indices is an important issue in the management of large herbivore populations. The drive counts method has been frequently used as a deer abundance index in mountainous regions. However, despite an inherent risk for observation errors in drive counts, which increase with deer density, evaluations of the utility of drive counts at a high deer density remain scarce. We compared the drive counts and mark-resight (MR) methods in the evaluation of a highly dense sika deer population (MR estimates ranged between 11 and 53 individuals/km2) on Nakanoshima Island, Hokkaido, Japan, between 1999 and 2006. This deer population experienced two large reductions in density; approximately 200 animals in total were taken from the population through a large-scale population removal and a separate winter mass mortality event. Although the drive counts tracked temporal changes in deer abundance on the island, they overestimated the counts for all years in comparison to the MR method. Increased overestimation in drive count estimates after the winter mass mortality event may be due to a double count derived from increased deer movement and recovery of body condition secondary to the mitigation of density-dependent food limitations. Drive counts are unreliable because they are affected by unfavorable factors such as bad weather, and they are cost-prohibitive to repeat, which precludes the calculation of confidence intervals. Therefore, the use of drive counts to infer the deer abundance needs to be reconsidered. PMID:27711181

Logistic quantile regression provides improved estimates for bounded avian counts: a case study of California Spotted Owl fledgling production

Treesearch

Brian S. Cade; Barry R. Noon; Rick D. Scherer; John J. Keane

2017-01-01

Counts of avian fledglings, nestlings, or clutch size that are bounded below by zero and above by some small integer form a discrete random variable distribution that is not approximated well by conventional parametric count distributions such as the Poisson or negative binomial. We developed a logistic quantile regression model to provide estimates of the empirical...

A removal model for estimating detection probabilities from point-count surveys

USGS Publications Warehouse

Farnsworth, G.L.; Pollock, K.H.; Nichols, J.D.; Simons, T.R.; Hines, J.E.; Sauer, J.R.

2000-01-01

We adapted a removal model to estimate detection probability during point count surveys. The model assumes one factor influencing detection during point counts is the singing frequency of birds. This may be true for surveys recording forest songbirds when most detections are by sound. The model requires counts to be divided into several time intervals. We used time intervals of 2, 5, and 10 min to develop a maximum-likelihood estimator for the detectability of birds during such surveys. We applied this technique to data from bird surveys conducted in Great Smoky Mountains National Park. We used model selection criteria to identify whether detection probabilities varied among species, throughout the morning, throughout the season, and among different observers. The overall detection probability for all birds was 75%. We found differences in detection probability among species. Species that sing frequently such as Winter Wren and Acadian Flycatcher had high detection probabilities (about 90%) and species that call infrequently such as Pileated Woodpecker had low detection probability (36%). We also found detection probabilities varied with the time of day for some species (e.g. thrushes) and between observers for other species. This method of estimating detectability during point count surveys offers a promising new approach to using count data to address questions of the bird abundance, density, and population trends.

Correction of differential renal function for asymmetric renal area ratio in unilateral hydronephrosis.

PubMed

Aktaş, Gul Ege; Sarıkaya, Ali

2015-11-01

Children with unilateral hydronephrosis are followed up with anteroposterior pelvic diameter (APD), hydronephrosis grade, mercaptoacetyltriglycine (MAG-3) drainage pattern and differential renal function (DRF). Indeterminate drainage preserved DRF in higher grades of hydronephrosis, in some situations, complicating the decision-making process. Due to an asymmetric renal area ratio, falsely negative DRF estimations can result in missed optimal surgery times. This study was designed to assess whether correcting the DRF estimation according to kidney area could reflect the clinical situation of a hydronephrotic kidney better than a classical DRF calculation, concurrently with the hydronephrosis grade, APD and MAG-3 drainage pattern. We reviewed the MAG-3, dimercaptosuccinic acid (DMSA) scans and ultrasonography (US) of 23 children (6 girls, 17 boys, mean age: 29 ± 50 months) with unilateral hydronephrosis. MAG-3 and DMSA scans were performed within 3 months (mean 25.4 ± 30.7 days). The closest US findings (mean 41.5 ± 28.2 days) were used. DMSA DRF estimations were obtained using the geometric mean method. Secondary calculations were performed to correct the counts (the total counts divided by the number of pixels in ROI) according to kidney area. The renogram patterns of patients were evaluated and separated into subgroups. The visual assessment of DMSA scans was noted and the hydronephrotic kidney was classified in comparison to the normal contralateral kidney's uptake. The correlations of the DRF values of classical and area-corrected methods with MAG-3 renogram patterns, the visual classification of DMSA scan, the hydronephrosis grade and the APD were assessed. DRF estimations of two methods were statistically different (p: 0.001). The categories of 12 hydronephrotic kidneys were changed. There were no correlations between classical DRF estimations and the hydronephrosis grade, APD, visual classification of the DMSA scan and uptake evaluation. The DRF distributions according to MAG-3 drainage patterns were not different. Area-corrected DRF estimations correlated with all: with an increasing hydronephrosis grade and APD, DRF estimations decreased and MAG-3 drainage patterns worsened. A decrease in DRF (< 45 %) was determined when APD was ≥ 10 mm. When APD was ≥ 26 mm, a reduction of DRF below 40 % was determined. Our results suggest that correcting DRF estimation for asymmetric renal area ratio in unilateral hydronephrosis can be more robust than the classical method, especially for higher grades of hydronephrotic kidneys, under equivocal circumstances.

Robust Portfolio Optimization Using Pseudodistances.

PubMed

Toma, Aida; Leoni-Aubin, Samuela

2015-01-01

The presence of outliers in financial asset returns is a frequently occurring phenomenon which may lead to unreliable mean-variance optimized portfolios. This fact is due to the unbounded influence that outliers can have on the mean returns and covariance estimators that are inputs in the optimization procedure. In this paper we present robust estimators of mean and covariance matrix obtained by minimizing an empirical version of a pseudodistance between the assumed model and the true model underlying the data. We prove and discuss theoretical properties of these estimators, such as affine equivariance, B-robustness, asymptotic normality and asymptotic relative efficiency. These estimators can be easily used in place of the classical estimators, thereby providing robust optimized portfolios. A Monte Carlo simulation study and applications to real data show the advantages of the proposed approach. We study both in-sample and out-of-sample performance of the proposed robust portfolios comparing them with some other portfolios known in literature.

Robust Portfolio Optimization Using Pseudodistances

PubMed Central

2015-01-01

The presence of outliers in financial asset returns is a frequently occurring phenomenon which may lead to unreliable mean-variance optimized portfolios. This fact is due to the unbounded influence that outliers can have on the mean returns and covariance estimators that are inputs in the optimization procedure. In this paper we present robust estimators of mean and covariance matrix obtained by minimizing an empirical version of a pseudodistance between the assumed model and the true model underlying the data. We prove and discuss theoretical properties of these estimators, such as affine equivariance, B-robustness, asymptotic normality and asymptotic relative efficiency. These estimators can be easily used in place of the classical estimators, thereby providing robust optimized portfolios. A Monte Carlo simulation study and applications to real data show the advantages of the proposed approach. We study both in-sample and out-of-sample performance of the proposed robust portfolios comparing them with some other portfolios known in literature. PMID:26468948

Robust interferon-α and IL-12 responses by dendritic cells are related to efficient CD4+ T-cell recovery in HIV patients on ART.

PubMed

Tan, Dino Bee Aik; Yong, Yean Kong; Lim, Andrew; Tan, Hong Yien; Kamarulzaman, Adeeba; French, Martyn; Price, Patricia

2011-05-01

Amongst HIV patients with successful virological responses to antiretroviral therapy (ART), poor CD4(+) T-cell recovery is associated with low nadir CD4(+) T-cell counts and persistent immune activation. These factors might be influenced by dendritic cell (DC) function. Interferon-α-producing plasmacytoid DC and IL-12-producing myeloid DC were quantified by flow cytometry after stimulation with agonists to TLR7/8 (CL075) or TLR9 (CpG-ODN). These were compared between patients who achieved CD4(+) T-cell counts above or below 200 cells/μL after 6 months on ART (High vs. Low groups). High Group patients had more DC producing interferon-α or IL-12 at Weeks 6 and 12 on ART than Low Group patients. The frequencies of cytokine-producing DC at Week 12 were directly correlated with CD4(+) T-cell counts at baseline and at Week 12. Patients with good recovery of CD4(+) T-cells had robust TLR-mediated interferon-α responses by plasmacytoid DC and IL-12 responses by myeloid DC during early ART (1-3 months). Copyright © 2011 Elsevier Inc. All rights reserved.

4D ML reconstruction as a tool for volumetric PET-based treatment verification in ion beam radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

De Bernardi, E., E-mail: elisabetta.debernardi@unimib.it; Ricotti, R.; Riboldi, M.

2016-02-15

Purpose: An innovative strategy to improve the sensitivity of positron emission tomography (PET)-based treatment verification in ion beam radiotherapy is proposed. Methods: Low counting statistics PET images acquired during or shortly after the treatment (Measured PET) and a Monte Carlo estimate of the same PET images derived from the treatment plan (Expected PET) are considered as two frames of a 4D dataset. A 4D maximum likelihood reconstruction strategy was adapted to iteratively estimate the annihilation events distribution in a reference frame and the deformation motion fields that map it in the Expected PET and Measured PET frames. The outputs generatedmore » by the proposed strategy are as follows: (1) an estimate of the Measured PET with an image quality comparable to the Expected PET and (2) an estimate of the motion field mapping Expected PET to Measured PET. The details of the algorithm are presented and the strategy is preliminarily tested on analytically simulated datasets. Results: The algorithm demonstrates (1) robustness against noise, even in the worst conditions where 1.5 × 10{sup 4} true coincidences and a random fraction of 73% are simulated; (2) a proper sensitivity to different kind and grade of mismatches ranging between 1 and 10 mm; (3) robustness against bias due to incorrect washout modeling in the Monte Carlo simulation up to 1/3 of the original signal amplitude; and (4) an ability to describe the mismatch even in presence of complex annihilation distributions such as those induced by two perpendicular superimposed ion fields. Conclusions: The promising results obtained in this work suggest the applicability of the method as a quantification tool for PET-based treatment verification in ion beam radiotherapy. An extensive assessment of the proposed strategy on real treatment verification data is planned.« less

The effectiveness of visitation proxy variables in improving recreation use estimates for the USDA Forest Service

Treesearch

Donald B.K. English; Susan M. Kocis; J. Ross Arnold; Stanley J. Zarnoch; Larry Warren

2003-01-01

In estimating recreation visitation at the National Forest level in the US, annual counts of a number of types of visitation proxy measures were used. The intent was to improve the overall precision of the visitation estimate by employing the proxy counts. The precision of visitation estimates at sites that had proxy information versus those that did not is examined....

Accuracy or precision: Implications of sample design and methodology on abundance estimation

USGS Publications Warehouse

Kowalewski, Lucas K.; Chizinski, Christopher J.; Powell, Larkin A.; Pope, Kevin L.; Pegg, Mark A.

2015-01-01

Sampling by spatially replicated counts (point-count) is an increasingly popular method of estimating population size of organisms. Challenges exist when sampling by point-count method, and it is often impractical to sample entire area of interest and impossible to detect every individual present. Ecologists encounter logistical limitations that force them to sample either few large-sample units or many small sample-units, introducing biases to sample counts. We generated a computer environment and simulated sampling scenarios to test the role of number of samples, sample unit area, number of organisms, and distribution of organisms in the estimation of population sizes using N-mixture models. Many sample units of small area provided estimates that were consistently closer to true abundance than sample scenarios with few sample units of large area. However, sample scenarios with few sample units of large area provided more precise abundance estimates than abundance estimates derived from sample scenarios with many sample units of small area. It is important to consider accuracy and precision of abundance estimates during the sample design process with study goals and objectives fully recognized, although and with consequence, consideration of accuracy and precision of abundance estimates is often an afterthought that occurs during the data analysis process.

Method for hyperspectral imagery exploitation and pixel spectral unmixing

NASA Technical Reports Server (NTRS)

Lin, Ching-Fang (Inventor)

2003-01-01

An efficiently hybrid approach to exploit hyperspectral imagery and unmix spectral pixels. This hybrid approach uses a genetic algorithm to solve the abundance vector for the first pixel of a hyperspectral image cube. This abundance vector is used as initial state in a robust filter to derive the abundance estimate for the next pixel. By using Kalman filter, the abundance estimate for a pixel can be obtained in one iteration procedure which is much fast than genetic algorithm. The output of the robust filter is fed to genetic algorithm again to derive accurate abundance estimate for the current pixel. The using of robust filter solution as starting point of the genetic algorithm speeds up the evolution of the genetic algorithm. After obtaining the accurate abundance estimate, the procedure goes to next pixel, and uses the output of genetic algorithm as the previous state estimate to derive abundance estimate for this pixel using robust filter. And again use the genetic algorithm to derive accurate abundance estimate efficiently based on the robust filter solution. This iteration continues until pixels in a hyperspectral image cube end.

Robust Data Detection for the Photon-Counting Free-Space Optical System With Implicit CSI Acquisition and Background Radiation Compensation

NASA Astrophysics Data System (ADS)

Song, Tianyu; Kam, Pooi-Yuen

2016-02-01

Since atmospheric turbulence and pointing errors cause signal intensity fluctuations and the background radiation surrounding the free-space optical (FSO) receiver contributes an undesired noisy component, the receiver requires accurate channel state information (CSI) and background information to adjust the detection threshold. In most previous studies, for CSI acquisition, pilot symbols were employed, which leads to a reduction of spectral and energy efficiency; and an impractical assumption that the background radiation component is perfectly known was made. In this paper, we develop an efficient and robust sequence receiver, which acquires the CSI and the background information implicitly and requires no knowledge about the channel model information. It is robust since it can automatically estimate the CSI and background component and detect the data sequence accordingly. Its decision metric has a simple form and involves no integrals, and thus can be easily evaluated. A Viterbi-type trellis-search algorithm is adopted to improve the search efficiency, and a selective-store strategy is adopted to overcome a potential error floor problem as well as to increase the memory efficiency. To further simplify the receiver, a decision-feedback symbol-by-symbol receiver is proposed as an approximation of the sequence receiver. By simulations and theoretical analysis, we show that the performance of both the sequence receiver and the symbol-by-symbol receiver, approach that of detection with perfect knowledge of the CSI and background radiation, as the length of the window for forming the decision metric increases.

Wild turkey poult survival in southcentral Iowa

USGS Publications Warehouse

Hubbard, M.W.; Garner, D.L.; Klaas, E.E.

1999-01-01

Poult survival is key to understanding annual change in wild turkey (Meleagris gallopavo) populations. Survival of eastern wild turkey poults (M. g. silvestris) 0-4 weeks posthatch was studied in southcentral Iowa during 1994-97. Survival estimates of poults were calculated based on biweekly flush counts and daily locations acquired via radiotelemetry. Poult survival averaged 0.52 ?? 0.14% (?? ?? SE) for telemetry counts and 0.40 ?? 0.15 for flush counts. No within-year or across-year differences were detected between estimation techniques. More than 72% (n = 32) of documented poult mortality occurred ???14 days posthatch, and mammalian predation accounted for 92.9% of documented mortality. If mortality agents are not of concern, we suggest biologists conduct 4-week flush counts to obtain poult survival estimates for use in population models and development of harvest recommendations.

Robust Variance Estimation with Dependent Effect Sizes: Practical Considerations Including a Software Tutorial in Stata and SPSS

ERIC Educational Resources Information Center

Tanner-Smith, Emily E.; Tipton, Elizabeth

2014-01-01

Methodologists have recently proposed robust variance estimation as one way to handle dependent effect sizes in meta-analysis. Software macros for robust variance estimation in meta-analysis are currently available for Stata (StataCorp LP, College Station, TX, USA) and SPSS (IBM, Armonk, NY, USA), yet there is little guidance for authors regarding…

Covariate selection with group lasso and doubly robust estimation of causal effects

PubMed Central

Koch, Brandon; Vock, David M.; Wolfson, Julian

2017-01-01

Summary The efficiency of doubly robust estimators of the average causal effect (ACE) of a treatment can be improved by including in the treatment and outcome models only those covariates which are related to both treatment and outcome (i.e., confounders) or related only to the outcome. However, it is often challenging to identify such covariates among the large number that may be measured in a given study. In this paper, we propose GLiDeR (Group Lasso and Doubly Robust Estimation), a novel variable selection technique for identifying confounders and predictors of outcome using an adaptive group lasso approach that simultaneously performs coefficient selection, regularization, and estimation across the treatment and outcome models. The selected variables and corresponding coefficient estimates are used in a standard doubly robust ACE estimator. We provide asymptotic results showing that, for a broad class of data generating mechanisms, GLiDeR yields a consistent estimator of the ACE when either the outcome or treatment model is correctly specified. A comprehensive simulation study shows that GLiDeR is more efficient than doubly robust methods using standard variable selection techniques and has substantial computational advantages over a recently proposed doubly robust Bayesian model averaging method. We illustrate our method by estimating the causal treatment effect of bilateral versus single-lung transplant on forced expiratory volume in one year after transplant using an observational registry. PMID:28636276

Covariate selection with group lasso and doubly robust estimation of causal effects.

PubMed

Koch, Brandon; Vock, David M; Wolfson, Julian

2018-03-01

The efficiency of doubly robust estimators of the average causal effect (ACE) of a treatment can be improved by including in the treatment and outcome models only those covariates which are related to both treatment and outcome (i.e., confounders) or related only to the outcome. However, it is often challenging to identify such covariates among the large number that may be measured in a given study. In this article, we propose GLiDeR (Group Lasso and Doubly Robust Estimation), a novel variable selection technique for identifying confounders and predictors of outcome using an adaptive group lasso approach that simultaneously performs coefficient selection, regularization, and estimation across the treatment and outcome models. The selected variables and corresponding coefficient estimates are used in a standard doubly robust ACE estimator. We provide asymptotic results showing that, for a broad class of data generating mechanisms, GLiDeR yields a consistent estimator of the ACE when either the outcome or treatment model is correctly specified. A comprehensive simulation study shows that GLiDeR is more efficient than doubly robust methods using standard variable selection techniques and has substantial computational advantages over a recently proposed doubly robust Bayesian model averaging method. We illustrate our method by estimating the causal treatment effect of bilateral versus single-lung transplant on forced expiratory volume in one year after transplant using an observational registry. © 2017, The International Biometric Society.

A collaborative approach for estimating terrestrial wildlife abundance

USGS Publications Warehouse

Ransom, Jason I.; Kaczensky, Petra; Lubow, Bruce C.; Ganbaatar, Oyunsaikhan; Altansukh, Nanjid

2012-01-01

Accurately estimating abundance of wildlife is critical for establishing effective conservation and management strategies. Aerial methodologies for estimating abundance are common in developed countries, but they are often impractical for remote areas of developing countries where many of the world's endangered and threatened fauna exist. The alternative terrestrial methodologies can be constrained by limitations on access, technology, and human resources, and have rarely been comprehensively conducted for large terrestrial mammals at landscape scales. We attempted to overcome these problems by incorporating local peoples into a simultaneous point count of Asiatic wild ass (Equus hemionus) and goitered gazelle (Gazella subgutturosa) across the Great Gobi B Strictly Protected Area, Mongolia. Paired observers collected abundance and covariate metrics at 50 observation points and we estimated population sizes using distance sampling theory, but also assessed individual observer error to examine potential bias introduced by the large number of minimally trained observers. We estimated 5671 (95% CI = 3611–8907) wild asses and 5909 (95% CI = 3762–9279) gazelle inhabited the 11,027 km2 study area at the time of our survey and found that the methodology developed was robust at absorbing the logistical challenges and wide range of observer abilities. This initiative serves as a functional model for estimating terrestrial wildlife abundance while integrating local people into scientific and conservation projects. This, in turn, creates vested interest in conservation by the people who are most influential in, and most affected by, the outcomes.

Using Robust Variance Estimation to Combine Multiple Regression Estimates with Meta-Analysis

ERIC Educational Resources Information Center

Williams, Ryan

2013-01-01

The purpose of this study was to explore the use of robust variance estimation for combining commonly specified multiple regression models and for combining sample-dependent focal slope estimates from diversely specified models. The proposed estimator obviates traditionally required information about the covariance structure of the dependent…

Motor vehicle traffic crash fatality counts and estimates of people injured for 2005

DOT National Transportation Integrated Search

2006-08-22

This report updates the 2005 Projections released in April 2006, which : were based on a statistical procedure using incomplete/partial data. : This report also compares fatality counts and estimates of people : injured resulting from motor vehicle t...

Graphical Evaluation of the Ridge-Type Robust Regression Estimators in Mixture Experiments

PubMed Central

Erkoc, Ali; Emiroglu, Esra

2014-01-01

In mixture experiments, estimation of the parameters is generally based on ordinary least squares (OLS). However, in the presence of multicollinearity and outliers, OLS can result in very poor estimates. In this case, effects due to the combined outlier-multicollinearity problem can be reduced to certain extent by using alternative approaches. One of these approaches is to use biased-robust regression techniques for the estimation of parameters. In this paper, we evaluate various ridge-type robust estimators in the cases where there are multicollinearity and outliers during the analysis of mixture experiments. Also, for selection of biasing parameter, we use fraction of design space plots for evaluating the effect of the ridge-type robust estimators with respect to the scaled mean squared error of prediction. The suggested graphical approach is illustrated on Hald cement data set. PMID:25202738

Graphical evaluation of the ridge-type robust regression estimators in mixture experiments.

PubMed

Erkoc, Ali; Emiroglu, Esra; Akay, Kadri Ulas

2014-01-01

In mixture experiments, estimation of the parameters is generally based on ordinary least squares (OLS). However, in the presence of multicollinearity and outliers, OLS can result in very poor estimates. In this case, effects due to the combined outlier-multicollinearity problem can be reduced to certain extent by using alternative approaches. One of these approaches is to use biased-robust regression techniques for the estimation of parameters. In this paper, we evaluate various ridge-type robust estimators in the cases where there are multicollinearity and outliers during the analysis of mixture experiments. Also, for selection of biasing parameter, we use fraction of design space plots for evaluating the effect of the ridge-type robust estimators with respect to the scaled mean squared error of prediction. The suggested graphical approach is illustrated on Hald cement data set.

The single water-surface sweep estimation method accurately estimates very low (n = 4) to low-moderate (n = 25-100) and high (n > 100) Aedes aegypti (Diptera: Culicidae) pupae numbers in large water containers up to 13 times faster than the exhaustive sweep and total count method and without any sediment contamination.

PubMed

Romero-Vivas, C M; Llinás, H; Falconar, A K

2015-03-01

To confirm that a single water-surface sweep-net collection coupled with three calibration factors (2.6, 3.0 and 3.5 for 1/3, 2/3 and 3/3 water levels, respectively) (WSCF) could accurately estimate very low to high Aedes aegypti pupae numbers in water containers more rapidly than the exhaustive 5-sweep and total count (ESTC) method recommended by WHO. Both methods were compared in semi-field trials using low (n = 25) to moderate (n = 50-100) pupae numbers in a 250-l drum at 1/3, 2/3 and 3/3 water levels, and by their mean-time determinations using 200 pupae in three 220- to 1024-l water containers at these water levels. Accuracy was further assessed using 69.1% (393/569) of the field-based drums and tanks which contained <100 pupae. The WSCF method accurately estimated total populations in the semi-field trials up to 13.0 times faster than the ESTC method (all P < 0.001); no significant differences (all P-values ≥ 0.05) were obtained between the methods for very low (n = 4) to low-moderate (n = 25-100) and high (n > 100) pupae numbers/container and without sediment disturbance. The simple WSCF method sensitively, accurately and robustly estimated total pupae numbers in their principal breeding sites worldwide, containers with >20 l water volumes, significantly (2.7- to 13.0-fold: all P-values <0.001) faster than the ESTC method for very low to high pupae numbers/container without contaminating the clean water by sediment disturbance which is generated using the WHO-recommended ESTC method. The WSCF method seems ideal for global community-based surveillance and control programmes. © 2014 John Wiley & Sons Ltd.

Time to burn: Modeling wildland arson as an autoregressive crime function

Treesearch

Jeffrey P. Prestemon; David T. Butry

2005-01-01

Six Poisson autoregressive models of order p [PAR(p)] of daily wildland arson ignition counts are estimated for five locations in Florida (1994-2001). In addition, a fixed effects time-series Poisson model of annual arson counts is estimated for all Florida counties (1995-2001). PAR(p) model estimates reveal highly significant arson ignition autocorrelation, lasting up...

Estimated allele substitution effects underlying genomic evaluation models depend on the scaling of allele counts.

PubMed

Bouwman, Aniek C; Hayes, Ben J; Calus, Mario P L

2017-10-30

Genomic evaluation is used to predict direct genomic values (DGV) for selection candidates in breeding programs, but also to estimate allele substitution effects (ASE) of single nucleotide polymorphisms (SNPs). Scaling of allele counts influences the estimated ASE, because scaling of allele counts results in less shrinkage towards the mean for low minor allele frequency (MAF) variants. Scaling may become relevant for estimating ASE as more low MAF variants will be used in genomic evaluations. We show the impact of scaling on estimates of ASE using real data and a theoretical framework, and in terms of power, model fit and predictive performance. In a dairy cattle dataset with 630 K SNP genotypes, the correlation between DGV for stature from a random regression model using centered allele counts (RRc) and centered and scaled allele counts (RRcs) was 0.9988, whereas the overall correlation between ASE using RRc and RRcs was 0.27. The main difference in ASE between both methods was found for SNPs with a MAF lower than 0.01. Both the ratio (ASE from RRcs/ASE from RRc) and the regression coefficient (regression of ASE from RRcs on ASE from RRc) were much higher than 1 for low MAF SNPs. Derived equations showed that scenarios with a high heritability, a large number of individuals and a small number of variants have lower ratios between ASE from RRc and RRcs. We also investigated the optimal scaling parameter [from - 1 (RRcs) to 0 (RRc) in steps of 0.1] in the bovine stature dataset. We found that the log-likelihood was maximized with a scaling parameter of - 0.8, while the mean squared error of prediction was minimized with a scaling parameter of - 1, i.e., RRcs. Large differences in estimated ASE were observed for low MAF SNPs when allele counts were scaled or not scaled because there is less shrinkage towards the mean for scaled allele counts. We derived a theoretical framework that shows that the difference in ASE due to shrinkage is heavily influenced by the power of the data. Increasing the power results in smaller differences in ASE whether allele counts are scaled or not.

Waveguide-Coupled Superconducting Nanowire Single-Photon Detectors

NASA Technical Reports Server (NTRS)

Beyer, Andrew D.; Briggs, Ryan M.; Marsili, Francesco; Cohen, Justin D.; Meenehan, Sean M.; Painter, Oskar J.; Shaw, Matthew D.

2015-01-01

We have demonstrated WSi-based superconducting nanowire single-photon detectors coupled to SiNx waveguides with integrated ring resonators. This photonics platform enables the implementation of robust and efficient photon-counting detectors with fine spectral resolution near 1550 nm.

Evaluating call-count procedures for measuring local mourning dove populations

USGS Publications Warehouse

Armbruster, M.J.; Baskett, T.S.; Goforth, W.R.; Sadler, K.C.

1978-01-01

Seventy-nine mourning dove call-count runs were made on a 32-km route in Osage County, Missouri, May 1-August 31, 1971 and 1972. Circular study areas, each 61 ha, surrounding stop numbers 4 and 5, were delineated for intensive nest searches and population estimates. Tallies of cooing male doves along the entire call-count route were quite variable in repeated runs, fluctuating as much as 50 percent on consecutive days. There were no consistent relationships between numbers of cooing males tallied at stops 4 and 5 and the numbers of current nests or doves estimated to be present in the surrounding study areas. We doubt the suitability of call-count procedures to estimate precisely the densities of breeding pairs, nests or production of doves on small areas. Our findings do not dispute the usefulness of the national call-count survey as an index to relative densities of mourning doves during the breeding season over large portions of the United States, or as an index to annual population trends.

An evaluation of the utility and limitations of counting motor unit action potentials in the surface electromyogram

NASA Astrophysics Data System (ADS)

Zhou, Ping; Zev Rymer, William

2004-12-01

The number of motor unit action potentials (MUAPs) appearing in the surface electromyogram (EMG) signal is directly related to motor unit recruitment and firing rates and therefore offers potentially valuable information about the level of activation of the motoneuron pool. In this paper, based on morphological features of the surface MUAPs, we try to estimate the number of MUAPs present in the surface EMG by counting the negative peaks in the signal. Several signal processing procedures are applied to the surface EMG to facilitate this peak counting process. The MUAP number estimation performance by this approach is first illustrated using the surface EMG simulations. Then, by evaluating the peak counting results from the EMG records detected by a very selective surface electrode, at different contraction levels of the first dorsal interosseous (FDI) muscles, the utility and limitations of such direct peak counts for MUAP number estimation in surface EMG are further explored.

Observer error structure in bull trout redd counts in Montana streams: Implications for inference on true redd numbers

USGS Publications Warehouse

Muhlfeld, Clint C.; Taper, Mark L.; Staples, David F.; Shepard, Bradley B.

2006-01-01

Despite the widespread use of redd counts to monitor trends in salmonid populations, few studies have evaluated the uncertainties in observed counts. We assessed the variability in redd counts for migratory bull trout Salvelinus confluentus among experienced observers in Lion and Goat creeks, which are tributaries to the Swan River, Montana. We documented substantially lower observer variability in bull trout redd counts than did previous studies. Observer counts ranged from 78% to 107% of our best estimates of true redd numbers in Lion Creek and from 90% to 130% of our best estimates in Goat Creek. Observers made both errors of omission and errors of false identification, and we modeled this combination by use of a binomial probability of detection and a Poisson count distribution of false identifications. Redd detection probabilities were high (mean = 83%) and exhibited no significant variation among observers (SD = 8%). We applied this error structure to annual redd counts in the Swan River basin (1982–2004) to correct for observer error and thus derived more accurate estimates of redd numbers and associated confidence intervals. Our results indicate that bias in redd counts can be reduced if experienced observers are used to conduct annual redd counts. Future studies should assess both sources of observer error to increase the validity of using redd counts for inferring true redd numbers in different basins. This information will help fisheries biologists to more precisely monitor population trends, identify recovery and extinction thresholds for conservation and recovery programs, ascertain and predict how management actions influence distribution and abundance, and examine effects of recovery and restoration activities.

On robust parameter estimation in brain-computer interfacing

NASA Astrophysics Data System (ADS)

Samek, Wojciech; Nakajima, Shinichi; Kawanabe, Motoaki; Müller, Klaus-Robert

2017-12-01

Objective. The reliable estimation of parameters such as mean or covariance matrix from noisy and high-dimensional observations is a prerequisite for successful application of signal processing and machine learning algorithms in brain-computer interfacing (BCI). This challenging task becomes significantly more difficult if the data set contains outliers, e.g. due to subject movements, eye blinks or loose electrodes, as they may heavily bias the estimation and the subsequent statistical analysis. Although various robust estimators have been developed to tackle the outlier problem, they ignore important structural information in the data and thus may not be optimal. Typical structural elements in BCI data are the trials consisting of a few hundred EEG samples and indicating the start and end of a task. Approach. This work discusses the parameter estimation problem in BCI and introduces a novel hierarchical view on robustness which naturally comprises different types of outlierness occurring in structured data. Furthermore, the class of minimum divergence estimators is reviewed and a robust mean and covariance estimator for structured data is derived and evaluated with simulations and on a benchmark data set. Main results. The results show that state-of-the-art BCI algorithms benefit from robustly estimated parameters. Significance. Since parameter estimation is an integral part of various machine learning algorithms, the presented techniques are applicable to many problems beyond BCI.

Enumerating Sparse Organisms in Ships’ Ballast Water: Why Counting to 10 Is Not So Easy

PubMed Central

2011-01-01

To reduce ballast water-borne aquatic invasions worldwide, the International Maritime Organization and United States Coast Guard have each proposed discharge standards specifying maximum concentrations of living biota that may be released in ships’ ballast water (BW), but these regulations still lack guidance for standardized type approval and compliance testing of treatment systems. Verifying whether BW meets a discharge standard poses significant challenges. Properly treated BW will contain extremely sparse numbers of live organisms, and robust estimates of rare events require extensive sampling efforts. A balance of analytical rigor and practicality is essential to determine the volume of BW that can be reasonably sampled and processed, yet yield accurate live counts. We applied statistical modeling to a range of sample volumes, plankton concentrations, and regulatory scenarios (i.e., levels of type I and type II errors), and calculated the statistical power of each combination to detect noncompliant discharge concentrations. The model expressly addresses the roles of sampling error, BW volume, and burden of proof on the detection of noncompliant discharges in order to establish a rigorous lower limit of sampling volume. The potential effects of recovery errors (i.e., incomplete recovery and detection of live biota) in relation to sample volume are also discussed. PMID:21434685

Enumerating sparse organisms in ships' ballast water: why counting to 10 is not so easy.

PubMed

Miller, A Whitman; Frazier, Melanie; Smith, George E; Perry, Elgin S; Ruiz, Gregory M; Tamburri, Mario N

2011-04-15

To reduce ballast water-borne aquatic invasions worldwide, the International Maritime Organization and United States Coast Guard have each proposed discharge standards specifying maximum concentrations of living biota that may be released in ships' ballast water (BW), but these regulations still lack guidance for standardized type approval and compliance testing of treatment systems. Verifying whether BW meets a discharge standard poses significant challenges. Properly treated BW will contain extremely sparse numbers of live organisms, and robust estimates of rare events require extensive sampling efforts. A balance of analytical rigor and practicality is essential to determine the volume of BW that can be reasonably sampled and processed, yet yield accurate live counts. We applied statistical modeling to a range of sample volumes, plankton concentrations, and regulatory scenarios (i.e., levels of type I and type II errors), and calculated the statistical power of each combination to detect noncompliant discharge concentrations. The model expressly addresses the roles of sampling error, BW volume, and burden of proof on the detection of noncompliant discharges in order to establish a rigorous lower limit of sampling volume. The potential effects of recovery errors (i.e., incomplete recovery and detection of live biota) in relation to sample volume are also discussed.

A Bayesian Method for Identifying Contaminated Detectors in Low-Level Alpha Spectrometers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maclellan, Jay A.; Strom, Daniel J.; Joyce, Kevin E.

2011-11-02

Analyses used for radiobioassay and other radiochemical tests are normally designed to meet specified quality objectives, such relative bias, precision, and minimum detectable activity (MDA). In the case of radiobioassay analyses for alpha emitting radionuclides, a major determiner of the process MDA is the instrument background. Alpha spectrometry detectors are often restricted to only a few counts over multi-day periods in order to meet required MDAs for nuclides such as plutonium-239 and americium-241. A detector background criterion is often set empirically based on experience, or frequentist or classical statistics are applied to the calculated background count necessary to meet amore » required MDA. An acceptance criterion for the detector background is set at the multiple of the estimated background standard deviation above the assumed mean that provides an acceptably small probability of observation if the mean and standard deviation estimate are correct. The major problem with this method is that the observed background counts used to estimate the mean, and thereby the standard deviation when a Poisson distribution is assumed, are often in the range of zero to three counts. At those expected count levels it is impossible to obtain a good estimate of the true mean from a single measurement. As an alternative, Bayesian statistical methods allow calculation of the expected detector background count distribution based on historical counts from new, uncontaminated detectors. This distribution can then be used to identify detectors showing an increased probability of contamination. The effect of varying the assumed range of background counts (i.e., the prior probability distribution) from new, uncontaminated detectors will be is discussed.« less

Monitoring planktivorous seabird populations: Validating surface counts of crevice-nesting auklets using mark-resight techniques

USGS Publications Warehouse

Sheffield, L.M.; Gall, Adrian E.; Roby, D.D.; Irons, D.B.; Dugger, K.M.

2006-01-01

Least Auklets (Aethia pusilla (Pallas, 1811)) are the most abundant species of seabird in the Bering Sea and offer a relatively efficient means of monitoring secondary productivity in the marine environment. Counting auklets on surface plots is the primary method used to track changes in numbers of these crevice-nesters, but counts can be highly variable and may not be representative of the number of nesting individuals. We compared average maximum counts of Least Auklets on surface plots with density estimates based on mark–resight data at a colony on St. Lawrence Island, Alaska, during 2001–2004. Estimates of breeding auklet abundance from mark–resight averaged 8 times greater than those from maximum surface counts. Our results also indicate that average maximum surface counts are poor indicators of breeding auklet abundance and do not vary consistently with auklet nesting density across the breeding colony. Estimates of Least Auklet abundance from mark–resight were sufficiently precise to meet management goals for tracking changes in seabird populations. We recommend establishing multiple permanent banding plots for mark–resight studies on colonies selected for intensive long-term monitoring. Mark–resight is more likely to detect biologically significant changes in size of auklet breeding colonies than traditional surface count techniques.

Structured pedigree information for distributed fusion systems

NASA Astrophysics Data System (ADS)

Arambel, Pablo O.

2008-04-01

One of the most critical challenges in distributed data fusion is the avoidance of information double counting (also called "data incest" or "rumor propagation"). This occurs when a node in a network incorporates information into an estimate - e.g. the position of an object - and the estimate is injected into the network. Other nodes fuse this estimate with their own estimates, and continue to propagate estimates through the network. When the first node receives a fused estimate from the network, it does not know if it already contains its own contributions or not. Since the correlation between its own estimate and the estimate received from the network is not known, the node can not fuse the estimates in an optimal way. If it assumes that both estimates are independent from each other, it unknowingly double counts the information that has already being used to obtain the two estimates. This leads to overoptimistic error covariance matrices. If the double-counting is not kept under control, it may lead to serious performance degradation. Double counting can be avoided by propagating uniquely tagged raw measurements; however, that forces each node to process all the measurements and precludes the propagation of derived information. Another approach is to fuse the information using the Covariance Intersection (CI) equations, which maintain consistent estimates irrespective of the cross-correlation among estimates. However, CI does not exploit pedigree information of any kind. In this paper we present an approach that propagates multiple covariance matrices, one for each uncorrelated source in the network. This is a way to compress the pedigree information and avoids the need to propagate raw measurements. The approach uses a generalized version of the Split CI to fuse different estimates with appropriate weights to guarantee the consistency of the estimates.

Adaptive torque estimation of robot joint with harmonic drive transmission

NASA Astrophysics Data System (ADS)

Shi, Zhiguo; Li, Yuankai; Liu, Guangjun

2017-11-01

Robot joint torque estimation using input and output position measurements is a promising technique, but the result may be affected by the load variation of the joint. In this paper, a torque estimation method with adaptive robustness and optimality adjustment according to load variation is proposed for robot joint with harmonic drive transmission. Based on a harmonic drive model and a redundant adaptive robust Kalman filter (RARKF), the proposed approach can adapt torque estimation filtering optimality and robustness to the load variation by self-tuning the filtering gain and self-switching the filtering mode between optimal and robust. The redundant factor of RARKF is designed as a function of the motor current for tolerating the modeling error and load-dependent filtering mode switching. The proposed joint torque estimation method has been experimentally studied in comparison with a commercial torque sensor and two representative filtering methods. The results have demonstrated the effectiveness of the proposed torque estimation technique.

Robust estimation for ordinary differential equation models.

PubMed

Cao, J; Wang, L; Xu, J

2011-12-01

Applied scientists often like to use ordinary differential equations (ODEs) to model complex dynamic processes that arise in biology, engineering, medicine, and many other areas. It is interesting but challenging to estimate ODE parameters from noisy data, especially when the data have some outliers. We propose a robust method to address this problem. The dynamic process is represented with a nonparametric function, which is a linear combination of basis functions. The nonparametric function is estimated by a robust penalized smoothing method. The penalty term is defined with the parametric ODE model, which controls the roughness of the nonparametric function and maintains the fidelity of the nonparametric function to the ODE model. The basis coefficients and ODE parameters are estimated in two nested levels of optimization. The coefficient estimates are treated as an implicit function of ODE parameters, which enables one to derive the analytic gradients for optimization using the implicit function theorem. Simulation studies show that the robust method gives satisfactory estimates for the ODE parameters from noisy data with outliers. The robust method is demonstrated by estimating a predator-prey ODE model from real ecological data. © 2011, The International Biometric Society.

Validation of State Counts of Handicapped Children. Volume II--Estimation of the Number of Handicapped Children in Each State.

ERIC Educational Resources Information Center

Kaskowitz, David H.

The booklet provides detailed estimates on handicapping conditions for school aged populations. The figures are intended to help the federal government validate state child count data as required by P.L. 94-142, the Education for All Handicapped Children. Section I uncovers the methodology used to arrive at the estimates, and it identifies the…

Serum insulin-like growth factor (IGF)-I and IGF binding protein-3 in relation to terminal duct lobular unit involution of the normal breast in Caucasian and African American women: The Susan G. Komen Tissue Bank.

PubMed

Oh, Hannah; Pfeiffer, Ruth M; Falk, Roni T; Horne, Hisani N; Xiang, Jackie; Pollak, Michael; Brinton, Louise A; Storniolo, Anna Maria V; Sherman, Mark E; Gierach, Gretchen L; Figueroa, Jonine D

2018-08-01

Lesser degrees of terminal duct lobular unit (TDLU) involution, as reflected by higher numbers of TDLUs and acini/TDLU, are associated with elevated breast cancer risk. In rodent models, the insulin-like growth factor (IGF) system regulates involution of the mammary gland. We examined associations of circulating IGF measures with TDLU involution in normal breast tissues among women without precancerous lesions. Among 715 Caucasian and 283 African American (AA) women who donated normal breast tissue samples to the Komen Tissue Bank between 2009 and 2012 (75% premenopausal), serum concentrations of IGF-I and binding protein (IGFBP)-3 were quantified using enzyme-linked immunosorbent assay. Hematoxilyn and eosin-stained tissue sections were assessed for numbers of TDLUs ("TDLU count"). Zero-inflated Poisson regression models with a robust variance estimator were used to estimate relative risks (RRs) for association of IGF measures (tertiles) with TDLU count by race and menopausal status, adjusting for potential confounders. AA (vs. Caucasian) women had higher age-adjusted mean levels of serum IGF-I (137 vs. 131 ng/mL, p = 0.07) and lower levels of IGFBP-3 (4165 vs. 4684 ng/mL, p < 0.0001). Postmenopausal IGFBP-3 was inversely associated with TDLU count among AA (RR T3vs.T1  = 0.49, 95% CI = 0.28-0.84, p-trend = 0.04) and Caucasian (RR T3vs.T1 =0.64, 95% CI = 0.42-0.98, p-trend = 0.04) women. In premenopausal women, higher IGF-I:IGFBP-3 ratios were associated with higher TDLU count in Caucasian (RR T3vs.T1 =1.33, 95% CI = 1.02-1.75, p-trend = 0.04), but not in AA (RR T3vs.T1 =0.65, 95% CI = 0.42-1.00, p-trend = 0.05), women. Our data suggest a role of the IGF system, particularly IGFBP-3, in TDLU involution of the normal breast, a breast cancer risk factor, among Caucasian and AA women. © 2018 UICC.

State traffic volume systems council estimation process.

DOT National Transportation Integrated Search

2004-10-01

The Kentucky Transportation Cabinet has an immense traffic data collection program that is an essential source for many other programs. The Division of Planning processes traffic volume counts annually. These counts are maintained in the Counts Datab...

Robust geostatistical analysis of spatial data

NASA Astrophysics Data System (ADS)

Papritz, A.; Künsch, H. R.; Schwierz, C.; Stahel, W. A.

2012-04-01

Most of the geostatistical software tools rely on non-robust algorithms. This is unfortunate, because outlying observations are rather the rule than the exception, in particular in environmental data sets. Outlying observations may results from errors (e.g. in data transcription) or from local perturbations in the processes that are responsible for a given pattern of spatial variation. As an example, the spatial distribution of some trace metal in the soils of a region may be distorted by emissions of local anthropogenic sources. Outliers affect the modelling of the large-scale spatial variation, the so-called external drift or trend, the estimation of the spatial dependence of the residual variation and the predictions by kriging. Identifying outliers manually is cumbersome and requires expertise because one needs parameter estimates to decide which observation is a potential outlier. Moreover, inference after the rejection of some observations is problematic. A better approach is to use robust algorithms that prevent automatically that outlying observations have undue influence. Former studies on robust geostatistics focused on robust estimation of the sample variogram and ordinary kriging without external drift. Furthermore, Richardson and Welsh (1995) [2] proposed a robustified version of (restricted) maximum likelihood ([RE]ML) estimation for the variance components of a linear mixed model, which was later used by Marchant and Lark (2007) [1] for robust REML estimation of the variogram. We propose here a novel method for robust REML estimation of the variogram of a Gaussian random field that is possibly contaminated by independent errors from a long-tailed distribution. It is based on robustification of estimating equations for the Gaussian REML estimation. Besides robust estimates of the parameters of the external drift and of the variogram, the method also provides standard errors for the estimated parameters, robustified kriging predictions at both sampled and unsampled locations and kriging variances. The method has been implemented in an R package. Apart from presenting our modelling framework, we shall present selected simulation results by which we explored the properties of the new method. This will be complemented by an analysis of the Tarrawarra soil moisture data set [3].

Poisson and negative binomial item count techniques for surveys with sensitive question.

PubMed

Tian, Guo-Liang; Tang, Man-Lai; Wu, Qin; Liu, Yin

2017-04-01

Although the item count technique is useful in surveys with sensitive questions, privacy of those respondents who possess the sensitive characteristic of interest may not be well protected due to a defect in its original design. In this article, we propose two new survey designs (namely the Poisson item count technique and negative binomial item count technique) which replace several independent Bernoulli random variables required by the original item count technique with a single Poisson or negative binomial random variable, respectively. The proposed models not only provide closed form variance estimate and confidence interval within [0, 1] for the sensitive proportion, but also simplify the survey design of the original item count technique. Most importantly, the new designs do not leak respondents' privacy. Empirical results show that the proposed techniques perform satisfactorily in the sense that it yields accurate parameter estimate and confidence interval.

Improved Doubly Robust Estimation when Data are Monotonely Coarsened, with Application to Longitudinal Studies with Dropout

PubMed Central

Tsiatis, Anastasios A.; Davidian, Marie; Cao, Weihua

2010-01-01

Summary A routine challenge is that of making inference on parameters in a statistical model of interest from longitudinal data subject to drop out, which are a special case of the more general setting of monotonely coarsened data. Considerable recent attention has focused on doubly robust estimators, which in this context involve positing models for both the missingness (more generally, coarsening) mechanism and aspects of the distribution of the full data, that have the appealing property of yielding consistent inferences if only one of these models is correctly specified. Doubly robust estimators have been criticized for potentially disastrous performance when both of these models are even only mildly misspecified. We propose a doubly robust estimator applicable in general monotone coarsening problems that achieves comparable or improved performance relative to existing doubly robust methods, which we demonstrate via simulation studies and by application to data from an AIDS clinical trial. PMID:20731640

Integrated direct/indirect adaptive robust motion trajectory tracking control of pneumatic cylinders

NASA Astrophysics Data System (ADS)

Meng, Deyuan; Tao, Guoliang; Zhu, Xiaocong

2013-09-01

This paper studies the precision motion trajectory tracking control of a pneumatic cylinder driven by a proportional-directional control valve. An integrated direct/indirect adaptive robust controller is proposed. The controller employs a physical model based indirect-type parameter estimation to obtain reliable estimates of unknown model parameters, and utilises a robust control method with dynamic compensation type fast adaptation to attenuate the effects of parameter estimation errors, unmodelled dynamics and disturbances. Due to the use of projection mapping, the robust control law and the parameter adaption algorithm can be designed separately. Since the system model uncertainties are unmatched, the recursive backstepping technology is adopted to design the robust control law. Extensive comparative experimental results are presented to illustrate the effectiveness of the proposed controller and its performance robustness to parameter variations and sudden disturbances.

The effectiveness of robust RMCD control chart as outliers’ detector

NASA Astrophysics Data System (ADS)

Darmanto; Astutik, Suci

2017-12-01

A well-known control chart to monitor a multivariate process is Hotelling’s T 2 which its parameters are estimated classically, very sensitive and also marred by masking and swamping of outliers data effect. To overcome these situation, robust estimators are strongly recommended. One of robust estimators is re-weighted minimum covariance determinant (RMCD) which has robust characteristics as same as MCD. In this paper, the effectiveness term is accuracy of the RMCD control chart in detecting outliers as real outliers. In other word, how effectively this control chart can identify and remove masking and swamping effects of outliers. We assessed the effectiveness the robust control chart based on simulation by considering different scenarios: n sample sizes, proportion of outliers, number of p quality characteristics. We found that in some scenarios, this RMCD robust control chart works effectively.

Progress in the development of the neutron flux monitoring system of the French GEN-IV SFR: simulations and experimental validations [ANIMMA--2015-IO-392

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jammes, C.; Filliatre, P.; Izarra, G. de

France has a long experience of about 50 years in designing, building and operating sodium-cooled fast reactors (SFR) such as RAPSODIE, PHENIX and SUPER PHENIX. Fast reactors feature the double capability of reducing nuclear waste and saving nuclear energy resources by burning actinides. Since this reactor type is one of those selected by the Generation IV International Forum, the French government asked, in the year 2006, CEA, namely the French Alternative Energies and Atomic Energy Commission, to lead the development of an innovative GEN-IV nuclear- fission power demonstrator. The major objective is to improve the safety and availability of anmore » SFR. The neutron flux monitoring (NFM) system of any reactor must, in any situation, permit both reactivity control and power level monitoring from startup to full power. It also has to monitor possible changes in neutron flux distribution within the core region in order to prevent any local melting accident. The neutron detectors will have to be installed inside the reactor vessel because locations outside the vessel will suffer from severe disadvantages; radially the neutron shield that is also contained in the reactor vessel will cause unacceptable losses in neutron flux; below the core the presence of a core-catcher prevents from inserting neutron guides; and above the core the distance is too large to obtain decent neutron signals outside the vessel. Another important point is to limit the number of detectors placed in the vessel in order to alleviate their installation into the vessel. In this paper, we show that the architecture of the NFM system will rely on high-temperature fission chambers (HTFC) featuring wide-range flux monitoring capability. The definition of such a system is presented and the justifications of technological options are brought with the use of simulation and experimental results. Firstly, neutron-transport calculations allow us to propose two in-vessel regions, namely the above-core and under-core structures. We verify that they comply with the main objective, that is the neutron power and flux distribution monitoring. HTFC placed in these two regions can detect an inadvertent control rod withdrawal that is a postulated initiating event for safety demonstration. Secondly, we show that the HTFC reliability is enhanced thanks to a more robust physical design and the fact that it has been justified that the mineral insulation is insensitive to any increase in temperature. Indeed, the HTFC insulation is subject to partial discharges at high temperature when the electric field between their electrodes is greater than about 200 V/mm or so. These discharges give rise to signals similar to the neutron pulses generated by a fission chamber itself, which may bias the HTFC count rate at start-up only. However, as displayed in Figure 1, we have experimentally verified that one can discriminate neutron pulses from partial discharges using online estimation of pulse width. Thirdly, we propose to estimate the count rate of a HTFC using the third order cumulant of its signal that is described by a filtered Poisson process. For such a statistic process, it is known that any cumulant, also called cumulative moment, is proportional to the process intensity that is here the count rate of a fission chamber. One recalls that the so-called Campbelling mode of such a detector is actually based on the signal variance, which is the second-order cumulant as well. The use of this extended Campbelling mode based on the third-order cumulant will permit to ensure the HTFC response linearity over the entire neutron flux range using a signal processing technique that is simple enough to satisfy design constraints on electric devices important for nuclear safety. We also show that this technique, named high order Campbelling method (HOC), is significantly more robust than another technique based on the change in the HTFC filling gas, which consists in adding a few percent of nitrogen. Finally, we also present an experimental campaign devoted to the required calibration process of the so-called HOC method. The Campbelling results show a good agreement with the simple pulse counting estimation at low count rates. It is also shown that the HOC technique provides a linear estimation of the count rates at higher power levels as well.« less

Incorporating precision, accuracy and alternative sampling designs into a continental monitoring program for colonial waterbirds

USGS Publications Warehouse

Steinkamp, Melanie J.; Peterjohn, B.G.; Keisman, J.L.

2003-01-01

A comprehensive monitoring program for colonial waterbirds in North America has never existed. At smaller geographic scales, many states and provinces conduct surveys of colonial waterbird populations. Periodic regional surveys are conducted at varying times during the breeding season using a variety of survey methods, which complicates attempts to estimate population trends for most species. The US Geological Survey Patuxent Wildlife Research Center has recently started to coordinate colonial waterbird monitoring efforts throughout North America. A centralized database has been developed with an Internet-based data entry and retrieval page. The extent of existing colonial waterbird surveys has been defined, allowing gaps in coverage to be identified and basic inventories completed where desirable. To enable analyses of comparable data at regional or larger geographic scales, sampling populations through statistically sound sampling designs should supersede obtaining counts at every colony. Standardized breeding season survey techniques have been agreed upon and documented in a monitoring manual. Each survey in the manual has associated with it recommendations for bias estimation, and includes specific instructions on measuring detectability. The methods proposed in the manual are for developing reliable, comparable indices of population size to establish trend information at multiple spatial and temporal scales, but they will not result in robust estimates of total population numbers.

DNA methylation-based measures of biological age: meta-analysis predicting time to death.

PubMed

Chen, Brian H; Marioni, Riccardo E; Colicino, Elena; Peters, Marjolein J; Ward-Caviness, Cavin K; Tsai, Pei-Chien; Roetker, Nicholas S; Just, Allan C; Demerath, Ellen W; Guan, Weihua; Bressler, Jan; Fornage, Myriam; Studenski, Stephanie; Vandiver, Amy R; Moore, Ann Zenobia; Tanaka, Toshiko; Kiel, Douglas P; Liang, Liming; Vokonas, Pantel; Schwartz, Joel; Lunetta, Kathryn L; Murabito, Joanne M; Bandinelli, Stefania; Hernandez, Dena G; Melzer, David; Nalls, Michael; Pilling, Luke C; Price, Timothy R; Singleton, Andrew B; Gieger, Christian; Holle, Rolf; Kretschmer, Anja; Kronenberg, Florian; Kunze, Sonja; Linseisen, Jakob; Meisinger, Christine; Rathmann, Wolfgang; Waldenberger, Melanie; Visscher, Peter M; Shah, Sonia; Wray, Naomi R; McRae, Allan F; Franco, Oscar H; Hofman, Albert; Uitterlinden, André G; Absher, Devin; Assimes, Themistocles; Levine, Morgan E; Lu, Ake T; Tsao, Philip S; Hou, Lifang; Manson, JoAnn E; Carty, Cara L; LaCroix, Andrea Z; Reiner, Alexander P; Spector, Tim D; Feinberg, Andrew P; Levy, Daniel; Baccarelli, Andrea; van Meurs, Joyce; Bell, Jordana T; Peters, Annette; Deary, Ian J; Pankow, James S; Ferrucci, Luigi; Horvath, Steve

2016-09-28

Estimates of biological age based on DNA methylation patterns, often referred to as "epigenetic age", "DNAm age", have been shown to be robust biomarkers of age in humans. We previously demonstrated that independent of chronological age, epigenetic age assessed in blood predicted all-cause mortality in four human cohorts. Here, we expanded our original observation to 13 different cohorts for a total sample size of 13,089 individuals, including three racial/ethnic groups. In addition, we examined whether incorporating information on blood cell composition into the epigenetic age metrics improves their predictive power for mortality. All considered measures of epigenetic age acceleration were predictive of mortality (p≤8.2x10 -9 ) , independent of chronological age, even after adjusting for additional risk factors (p<5.4x10 -4 ) , and within the racial/ethnic groups that we examined (non-Hispanic whites, Hispanics, African Americans). Epigenetic age estimates that incorporated information on blood cell composition led to the smallest p-values for time to death (p=7.5x10 -43 ). Overall, this study a) strengthens the evidence that epigenetic age predicts all-cause mortality above and beyond chronological age and traditional risk factors, and b) demonstrates that epigenetic age estimates that incorporate information on blood cell counts lead to highly significant associations with all-cause mortality.

The Fifth Cell: Correlation Bias in U.S. Census Adjustment.

ERIC Educational Resources Information Center

Wachter, Kenneth W.; Freedman, David A.

2000-01-01

Presents a method for estimating the total national number of doubly missing people (missing from Census counts and adjusted counts as well) and their distribution by race and sex. Application to the 1990 U.S. Census yields an estimate of three million doubly-missing people. (SLD)

Efficient Robust Regression via Two-Stage Generalized Empirical Likelihood

PubMed Central

Bondell, Howard D.; Stefanski, Leonard A.

2013-01-01

Large- and finite-sample efficiency and resistance to outliers are the key goals of robust statistics. Although often not simultaneously attainable, we develop and study a linear regression estimator that comes close. Efficiency obtains from the estimator’s close connection to generalized empirical likelihood, and its favorable robustness properties are obtained by constraining the associated sum of (weighted) squared residuals. We prove maximum attainable finite-sample replacement breakdown point, and full asymptotic efficiency for normal errors. Simulation evidence shows that compared to existing robust regression estimators, the new estimator has relatively high efficiency for small sample sizes, and comparable outlier resistance. The estimator is further illustrated and compared to existing methods via application to a real data set with purported outliers. PMID:23976805

The Burden of Pulmonary Nontuberculous Mycobacterial Disease in the United States

PubMed Central

Strollo, Sara E.; Adjemian, Jennifer; Adjemian, Michael K.

2015-01-01

Rationale: State-specific case numbers and costs are critical for quantifying the burden of pulmonary nontuberculous mycobacterial disease in the United States. Objectives: To estimate and project national and state annual cases of nontuberculous mycobacterial disease and associated direct medical costs. Methods: Available direct cost estimates of nontuberculous mycobacterial disease medical encounters were applied to nontuberculous mycobacterial disease prevalence estimates derived from Medicare beneficiary data (2003–2007). Prevalence was adjusted for International Classification of Diseases, 9th Revision, undercoding and the inclusion of persons younger than 65 years of age. U.S. Census Bureau data identified 2010 and 2014 population counts and 2012 primary insurance-type distribution. Medical costs were reported in constant 2014 dollars. Projected 2014 estimates were adjusted for population growth and assumed a previously published 8% annual growth rate of nontuberculous mycobacterial disease prevalence. Measurements and Main Results: In 2010, we estimated 86,244 national cases, totaling to $815 million, of which 87% were inpatient related ($709 million) and 13% were outpatient related ($106 million). Annual state estimates varied from 48 to 12,544 cases ($503,000–$111 million), with a median of 1,208 cases ($11.5 million). Oceanic coastline states and Gulf States comprised 70% of nontuberculous mycobacterial disease cases but 60% of the U.S. population. Medical encounters among individuals aged 65 years and older ($562 million) were twofold higher than those younger than 65 years of age ($253 million). Of all costs incurred, medications comprised 76% of nontuberculous mycobacterial disease expenditures. Projected 2014 estimates resulted in 181,037 national annual cases ($1.7 billion). Conclusions: For a relatively rare disease, the financial cost of nontuberculous mycobacterial disease is substantial, particularly among older adults. Better data on disease dynamics and more recent prevalence estimates will generate more robust estimates. PMID:26214350

Direct and Absolute Quantification of over 1800 Yeast Proteins via Selected Reaction Monitoring*

PubMed Central

Lawless, Craig; Holman, Stephen W.; Brownridge, Philip; Lanthaler, Karin; Harman, Victoria M.; Watkins, Rachel; Hammond, Dean E.; Miller, Rebecca L.; Sims, Paul F. G.; Grant, Christopher M.; Eyers, Claire E.; Beynon, Robert J.

2016-01-01

Defining intracellular protein concentration is critical in molecular systems biology. Although strategies for determining relative protein changes are available, defining robust absolute values in copies per cell has proven significantly more challenging. Here we present a reference data set quantifying over 1800 Saccharomyces cerevisiae proteins by direct means using protein-specific stable-isotope labeled internal standards and selected reaction monitoring (SRM) mass spectrometry, far exceeding any previous study. This was achieved by careful design of over 100 QconCAT recombinant proteins as standards, defining 1167 proteins in terms of copies per cell and upper limits on a further 668, with robust CVs routinely less than 20%. The selected reaction monitoring-derived proteome is compared with existing quantitative data sets, highlighting the disparities between methodologies. Coupled with a quantification of the transcriptome by RNA-seq taken from the same cells, these data support revised estimates of several fundamental molecular parameters: a total protein count of ∼100 million molecules-per-cell, a median of ∼1000 proteins-per-transcript, and a linear model of protein translation explaining 70% of the variance in translation rate. This work contributes a “gold-standard” reference yeast proteome (including 532 values based on high quality, dual peptide quantification) that can be widely used in systems models and for other comparative studies. PMID:26750110

Uncertainty of quantitative microbiological methods of pharmaceutical analysis.

PubMed

Gunar, O V; Sakhno, N G

2015-12-30

The total uncertainty of quantitative microbiological methods, used in pharmaceutical analysis, consists of several components. The analysis of the most important sources of the quantitative microbiological methods variability demonstrated no effect of culture media and plate-count techniques in the estimation of microbial count while the highly significant effect of other factors (type of microorganism, pharmaceutical product and individual reading and interpreting errors) was established. The most appropriate method of statistical analysis of such data was ANOVA which enabled not only the effect of individual factors to be estimated but also their interactions. Considering all the elements of uncertainty and combining them mathematically the combined relative uncertainty of the test results was estimated both for method of quantitative examination of non-sterile pharmaceuticals and microbial count technique without any product. These data did not exceed 35%, appropriated for a traditional plate count methods. Copyright © 2015 Elsevier B.V. All rights reserved.

New method for estimating bacterial cell abundances in natural samples by use of sublimation

NASA Technical Reports Server (NTRS)

Glavin, Daniel P.; Cleaves, H. James; Schubert, Michael; Aubrey, Andrew; Bada, Jeffrey L.

2004-01-01

We have developed a new method based on the sublimation of adenine from Escherichia coli to estimate bacterial cell counts in natural samples. To demonstrate this technique, several types of natural samples, including beach sand, seawater, deep-sea sediment, and two soil samples from the Atacama Desert, were heated to a temperature of 500 degrees C for several seconds under reduced pressure. The sublimate was collected on a cold finger, and the amount of adenine released from the samples was then determined by high-performance liquid chromatography with UV absorbance detection. Based on the total amount of adenine recovered from DNA and RNA in these samples, we estimated bacterial cell counts ranging from approximately 10(5) to 10(9) E. coli cell equivalents per gram. For most of these samples, the sublimation-based cell counts were in agreement with total bacterial counts obtained by traditional DAPI (4,6-diamidino-2-phenylindole) staining.

Retrospective determination of the contamination in the HML's counting chambers.

PubMed

Kramer, Gary H; Hauck, Barry; Capello, Kevin; Phan, Quoc

2008-09-01

The original documentation surrounding the purchase of the Human Monitoring Laboratory's (HML) counting chambers clearly showed that the steel contained low levels of radioactivity, presumably as a result of A-bomb fallout or perhaps to the inadvertent mixing of radioactive sources with scrap steel. Monte Carlo simulations have been combined with experimental measurements to estimate the level of contamination in the steel of the HML's whole body counting chamber. A 24-h empty chamber background count showed the presence of 137Cs and 60Co. The estimated activity of 137Cs in the 51 tons of steel was 2.7 kBq in 2007 (51.3 microBq g(-1) steel) which would have been 8 kBq at the time of manufacture. The 60Co that was found in the background spectrum is postulated to be contained in the bed-frame. The estimated amount in 2007 was 5 Bq and its origin is likely to be contaminated scrap metal entering the steel production cycle sometime in the past. The estimated activities are 10 to 25 times higher than the estimated minimum detectable activity for this measurement. These amounts have no impact on the usefulness of the whole body counter.

A robust background regression based score estimation algorithm for hyperspectral anomaly detection

NASA Astrophysics Data System (ADS)

Zhao, Rui; Du, Bo; Zhang, Liangpei; Zhang, Lefei

2016-12-01

Anomaly detection has become a hot topic in the hyperspectral image analysis and processing fields in recent years. The most important issue for hyperspectral anomaly detection is the background estimation and suppression. Unreasonable or non-robust background estimation usually leads to unsatisfactory anomaly detection results. Furthermore, the inherent nonlinearity of hyperspectral images may cover up the intrinsic data structure in the anomaly detection. In order to implement robust background estimation, as well as to explore the intrinsic data structure of the hyperspectral image, we propose a robust background regression based score estimation algorithm (RBRSE) for hyperspectral anomaly detection. The Robust Background Regression (RBR) is actually a label assignment procedure which segments the hyperspectral data into a robust background dataset and a potential anomaly dataset with an intersection boundary. In the RBR, a kernel expansion technique, which explores the nonlinear structure of the hyperspectral data in a reproducing kernel Hilbert space, is utilized to formulate the data as a density feature representation. A minimum squared loss relationship is constructed between the data density feature and the corresponding assigned labels of the hyperspectral data, to formulate the foundation of the regression. Furthermore, a manifold regularization term which explores the manifold smoothness of the hyperspectral data, and a maximization term of the robust background average density, which suppresses the bias caused by the potential anomalies, are jointly appended in the RBR procedure. After this, a paired-dataset based k-nn score estimation method is undertaken on the robust background and potential anomaly datasets, to implement the detection output. The experimental results show that RBRSE achieves superior ROC curves, AUC values, and background-anomaly separation than some of the other state-of-the-art anomaly detection methods, and is easy to implement in practice.

Performance in population models for count data, part II: a new SAEM algorithm

PubMed Central

Savic, Radojka; Lavielle, Marc

2009-01-01

Analysis of count data from clinical trials using mixed effect analysis has recently become widely used. However, algorithms available for the parameter estimation, including LAPLACE and Gaussian quadrature (GQ), are associated with certain limitations, including bias in parameter estimates and the long analysis runtime. The stochastic approximation expectation maximization (SAEM) algorithm has proven to be a very efficient and powerful tool in the analysis of continuous data. The aim of this study was to implement and investigate the performance of a new SAEM algorithm for application to count data. A new SAEM algorithm was implemented in MATLAB for estimation of both, parameters and the Fisher information matrix. Stochastic Monte Carlo simulations followed by re-estimation were performed according to scenarios used in previous studies (part I) to investigate properties of alternative algorithms (1). A single scenario was used to explore six probability distribution models. For parameter estimation, the relative bias was less than 0.92% and 4.13 % for fixed and random effects, for all models studied including ones accounting for over- or under-dispersion. Empirical and estimated relative standard errors were similar, with distance between them being <1.7 % for all explored scenarios. The longest CPU time was 95s for parameter estimation and 56s for SE estimation. The SAEM algorithm was extended for analysis of count data. It provides accurate estimates of both, parameters and standard errors. The estimation is significantly faster compared to LAPLACE and GQ. The algorithm is implemented in Monolix 3.1, (beta-version available in July 2009). PMID:19680795

Regression analysis of mixed recurrent-event and panel-count data

PubMed Central

Zhu, Liang; Tong, Xinwei; Sun, Jianguo; Chen, Manhua; Srivastava, Deo Kumar; Leisenring, Wendy; Robison, Leslie L.

2014-01-01

In event history studies concerning recurrent events, two types of data have been extensively discussed. One is recurrent-event data (Cook and Lawless, 2007. The Analysis of Recurrent Event Data. New York: Springer), and the other is panel-count data (Zhao and others, 2010. Nonparametric inference based on panel-count data. Test 20, 1–42). In the former case, all study subjects are monitored continuously; thus, complete information is available for the underlying recurrent-event processes of interest. In the latter case, study subjects are monitored periodically; thus, only incomplete information is available for the processes of interest. In reality, however, a third type of data could occur in which some study subjects are monitored continuously, but others are monitored periodically. When this occurs, we have mixed recurrent-event and panel-count data. This paper discusses regression analysis of such mixed data and presents two estimation procedures for the problem. One is a maximum likelihood estimation procedure, and the other is an estimating equation procedure. The asymptotic properties of both resulting estimators of regression parameters are established. Also, the methods are applied to a set of mixed recurrent-event and panel-count data that arose from a Childhood Cancer Survivor Study and motivated this investigation. PMID:24648408

Zero-inflated count models for longitudinal measurements with heterogeneous random effects.

PubMed

Zhu, Huirong; Luo, Sheng; DeSantis, Stacia M

2017-08-01

Longitudinal zero-inflated count data arise frequently in substance use research when assessing the effects of behavioral and pharmacological interventions. Zero-inflated count models (e.g. zero-inflated Poisson or zero-inflated negative binomial) with random effects have been developed to analyze this type of data. In random effects zero-inflated count models, the random effects covariance matrix is typically assumed to be homogeneous (constant across subjects). However, in many situations this matrix may be heterogeneous (differ by measured covariates). In this paper, we extend zero-inflated count models to account for random effects heterogeneity by modeling their variance as a function of covariates. We show via simulation that ignoring intervention and covariate-specific heterogeneity can produce biased estimates of covariate and random effect estimates. Moreover, those biased estimates can be rectified by correctly modeling the random effects covariance structure. The methodological development is motivated by and applied to the Combined Pharmacotherapies and Behavioral Interventions for Alcohol Dependence (COMBINE) study, the largest clinical trial of alcohol dependence performed in United States with 1383 individuals.

Point Count Length and Detection of Forest Neotropical Migrant Birds

Treesearch

Deanna K. Dawson; David R. Smith; Chandler S. Robbins

1995-01-01

Comparisons of bird abundances among years or among habitats assume that the rates at which birds are detected and counted are constant within species. We use point count data collected in forests of the Mid-Atlantic states to estimate detection probabilities for Neotropical migrant bird species as a function of count length. For some species, significant differences...

Use of simulation tools to illustrate the effect of data management practices for low and negative plate counts on the estimated parameters of microbial reduction models.

PubMed

Garcés-Vega, Francisco; Marks, Bradley P

2014-08-01

In the last 20 years, the use of microbial reduction models has expanded significantly, including inactivation (linear and nonlinear), survival, and transfer models. However, a major constraint for model development is the impossibility to directly quantify the number of viable microorganisms below the limit of detection (LOD) for a given study. Different approaches have been used to manage this challenge, including ignoring negative plate counts, using statistical estimations, or applying data transformations. Our objective was to illustrate and quantify the effect of negative plate count data management approaches on parameter estimation for microbial reduction models. Because it is impossible to obtain accurate plate counts below the LOD, we performed simulated experiments to generate synthetic data for both log-linear and Weibull-type microbial reductions. We then applied five different, previously reported data management practices and fit log-linear and Weibull models to the resulting data. The results indicated a significant effect (α = 0.05) of the data management practices on the estimated model parameters and performance indicators. For example, when the negative plate counts were replaced by the LOD for log-linear data sets, the slope of the subsequent log-linear model was, on average, 22% smaller than for the original data, the resulting model underpredicted lethality by up to 2.0 log, and the Weibull model was erroneously selected as the most likely correct model for those data. The results demonstrate that it is important to explicitly report LODs and related data management protocols, which can significantly affect model results, interpretation, and utility. Ultimately, we recommend using only the positive plate counts to estimate model parameters for microbial reduction curves and avoiding any data value substitutions or transformations when managing negative plate counts to yield the most accurate model parameters.

Robust guaranteed-cost adaptive quantum phase estimation

NASA Astrophysics Data System (ADS)

Roy, Shibdas; Berry, Dominic W.; Petersen, Ian R.; Huntington, Elanor H.

2017-05-01

Quantum parameter estimation plays a key role in many fields like quantum computation, communication, and metrology. Optimal estimation allows one to achieve the most precise parameter estimates, but requires accurate knowledge of the model. Any inevitable uncertainty in the model parameters may heavily degrade the quality of the estimate. It is therefore desired to make the estimation process robust to such uncertainties. Robust estimation was previously studied for a varying phase, where the goal was to estimate the phase at some time in the past, using the measurement results from both before and after that time within a fixed time interval up to current time. Here, we consider a robust guaranteed-cost filter yielding robust estimates of a varying phase in real time, where the current phase is estimated using only past measurements. Our filter minimizes the largest (worst-case) variance in the allowable range of the uncertain model parameter(s) and this determines its guaranteed cost. It outperforms in the worst case the optimal Kalman filter designed for the model with no uncertainty, which corresponds to the center of the possible range of the uncertain parameter(s). Moreover, unlike the Kalman filter, our filter in the worst case always performs better than the best achievable variance for heterodyne measurements, which we consider as the tolerable threshold for our system. Furthermore, we consider effective quantum efficiency and effective noise power, and show that our filter provides the best results by these measures in the worst case.

Application of a hybrid model to reduce bias and improve precision in population estimates for elk (Cervus elaphus) inhabiting a cold desert ecosystem

USGS Publications Warehouse

Schoenecker, Kathryn A.; Lubow, Bruce C.

2016-01-01

Accurately estimating the size of wildlife populations is critical to wildlife management and conservation of species. Raw counts or “minimum counts” are still used as a basis for wildlife management decisions. Uncorrected raw counts are not only negatively biased due to failure to account for undetected animals, but also provide no estimate of precision on which to judge the utility of counts. We applied a hybrid population estimation technique that combined sightability modeling, radio collar-based mark-resight, and simultaneous double count (double-observer) modeling to estimate the population size of elk in a high elevation desert ecosystem. Combining several models maximizes the strengths of each individual model while minimizing their singular weaknesses. We collected data with aerial helicopter surveys of the elk population in the San Luis Valley and adjacent mountains in Colorado State, USA in 2005 and 2007. We present estimates from 7 alternative analyses: 3 based on different methods for obtaining a raw count and 4 based on different statistical models to correct for sighting probability bias. The most reliable of these approaches is a hybrid double-observer sightability model (model MH), which uses detection patterns of 2 independent observers in a helicopter plus telemetry-based detections of radio collared elk groups. Data were fit to customized mark-resight models with individual sighting covariates. Error estimates were obtained by a bootstrapping procedure. The hybrid method was an improvement over commonly used alternatives, with improved precision compared to sightability modeling and reduced bias compared to double-observer modeling. The resulting population estimate corrected for multiple sources of undercount bias that, if left uncorrected, would have underestimated the true population size by as much as 22.9%. Our comparison of these alternative methods demonstrates how various components of our method contribute to improving the final estimate and demonstrates why each is necessary.

A Robust Approach to Risk Assessment Based on Species Sensitivity Distributions.

PubMed

Monti, Gianna S; Filzmoser, Peter; Deutsch, Roland C

2018-05-03

The guidelines for setting environmental quality standards are increasingly based on probabilistic risk assessment due to a growing general awareness of the need for probabilistic procedures. One of the commonly used tools in probabilistic risk assessment is the species sensitivity distribution (SSD), which represents the proportion of species affected belonging to a biological assemblage as a function of exposure to a specific toxicant. Our focus is on the inverse use of the SSD curve with the aim of estimating the concentration, HCp, of a toxic compound that is hazardous to p% of the biological community under study. Toward this end, we propose the use of robust statistical methods in order to take into account the presence of outliers or apparent skew in the data, which may occur without any ecological basis. A robust approach exploits the full neighborhood of a parametric model, enabling the analyst to account for the typical real-world deviations from ideal models. We examine two classic HCp estimation approaches and consider robust versions of these estimators. In addition, we also use data transformations in conjunction with robust estimation methods in case of heteroscedasticity. Different scenarios using real data sets as well as simulated data are presented in order to illustrate and compare the proposed approaches. These scenarios illustrate that the use of robust estimation methods enhances HCp estimation. © 2018 Society for Risk Analysis.

Temporal variation in bird counts within a Hawaiian rainforest

USGS Publications Warehouse

Simon, John C.; Pratt, T.K.; Berlin, Kim E.; Kowalsky, James R.; Fancy, S.G.; Hatfield, J.S.

2002-01-01

We studied monthly and annual variation in density estimates of nine forest bird species along an elevational gradient in an east Maui rainforest. We conducted monthly variable circular-plot counts for 36 consecutive months along transects running downhill from timberline. Density estimates were compared by month, year, and station for all resident bird species with sizeable populations, including four native nectarivores, two native insectivores, a non-native insectivore, and two non-native generalists. We compared densities among three elevational strata and between breeding and nonbreeding seasons. All species showed significant differences in density estimates among months and years. Three native nectarivores had higher density estimates within their breeding season (December-May) and showed decreases during periods of low nectar production following the breeding season. All insectivore and generalist species except one had higher density estimates within their March-August breeding season. Density estimates also varied with elevation for all species, and for four species a seasonal shift in population was indicated. Our data show that the best time to conduct counts for native forest birds on Maui is January-February, when birds are breeding or preparing to breed, counts are typically high, variability in density estimates is low, and the likelihood for fair weather is best. Temporal variations in density estimates documented in our study site emphasize the need for consistent, well-researched survey regimens and for caution when drawing conclusions from, or basing management decisions on, survey data.

EVALUATING PROBABILITY SAMPLING STRATEGIES FOR ESTIMATING REDD COUNTS: AN EXAMPLE WITH CHINOOK SALMON (Oncorhynchus tshawytscha)

EPA Science Inventory

Precise, unbiased estimates of population size are an essential tool for fisheries management. For a wide variety of salmonid fishes, redd counts from a sample of reaches are commonly used to monitor annual trends in abundance. Using a 9-year time series of georeferenced censuses...

Partial-Interval Estimation of Count: Uncorrected and Poisson-Corrected Error Levels

ERIC Educational Resources Information Center

Yoder, Paul J.; Ledford, Jennifer R.; Harbison, Amy L.; Tapp, Jon T.

2018-01-01

A simulation study that used 3,000 computer-generated event streams with known behavior rates, interval durations, and session durations was conducted to test whether the main and interaction effects of true rate and interval duration affect the error level of uncorrected and Poisson-transformed (i.e., "corrected") count as estimated by…

9C spectral-index distributions and source-count estimates from 15 to 93 GHz - a re-assessment

NASA Astrophysics Data System (ADS)

Waldram, E. M.; Bolton, R. C.; Riley, J. M.; Pooley, G. G.

2018-01-01

In an earlier paper (2007), we used follow-up observations of a sample of sources from the 9C survey at 15.2 GHz to derive a set of spectral-index distributions up to a frequency of 90 GHz. These were based on simultaneous measurements made at 15.2 GHz with the Ryle telescope and at 22 and 43 GHz with the Karl G. Jansky Very Large Array (VLA). We used these distributions to make empirical estimates of source counts at 22, 30, 43, 70 and 90 GHz. In a later paper (2013), we took data at 15.7 GHz from the Arcminute Microkelvin Imager (AMI) and data at 93.2 GHz from the Combined Array for Research in Millimetre-wave Astronomy (CARMA) and estimated the source count at 93.2 GHz. In this paper, we re-examine the data used in both papers and now believe that the VLA flux densities we measured at 43 GHz were significantly in error, being on average only about 70 per cent of their correct values. Here, we present strong evidence for this conclusion and discuss the effect on the source-count estimates made in the 2007 paper. The source-count prediction in the 2013 paper is also revised. We make comparisons with spectral-index distributions and source counts from other telescopes, in particular with a recent deep 95 GHz source count measured by the South Pole Telescope. We investigate reasons for the problem of the low VLA 43-GHz values and find a number of possible contributory factors, but none is sufficient on its own to account for such a large deficit.

Equivalence of truncated count mixture distributions and mixtures of truncated count distributions.

PubMed

Böhning, Dankmar; Kuhnert, Ronny

2006-12-01

This article is about modeling count data with zero truncation. A parametric count density family is considered. The truncated mixture of densities from this family is different from the mixture of truncated densities from the same family. Whereas the former model is more natural to formulate and to interpret, the latter model is theoretically easier to treat. It is shown that for any mixing distribution leading to a truncated mixture, a (usually different) mixing distribution can be found so that the associated mixture of truncated densities equals the truncated mixture, and vice versa. This implies that the likelihood surfaces for both situations agree, and in this sense both models are equivalent. Zero-truncated count data models are used frequently in the capture-recapture setting to estimate population size, and it can be shown that the two Horvitz-Thompson estimators, associated with the two models, agree. In particular, it is possible to achieve strong results for mixtures of truncated Poisson densities, including reliable, global construction of the unique NPMLE (nonparametric maximum likelihood estimator) of the mixing distribution, implying a unique estimator for the population size. The benefit of these results lies in the fact that it is valid to work with the mixture of truncated count densities, which is less appealing for the practitioner but theoretically easier. Mixtures of truncated count densities form a convex linear model, for which a developed theory exists, including global maximum likelihood theory as well as algorithmic approaches. Once the problem has been solved in this class, it might readily be transformed back to the original problem by means of an explicitly given mapping. Applications of these ideas are given, particularly in the case of the truncated Poisson family.

Evaluating and improving count-based population inference: A case study from 31 years of monitoring Sandhill Cranes

USGS Publications Warehouse

Gerber, Brian D.; Kendall, William L.

2017-01-01

Monitoring animal populations can be difficult. Limited resources often force monitoring programs to rely on unadjusted or smoothed counts as an index of abundance. Smoothing counts is commonly done using a moving-average estimator to dampen sampling variation. These indices are commonly used to inform management decisions, although their reliability is often unknown. We outline a process to evaluate the biological plausibility of annual changes in population counts and indices from a typical monitoring scenario and compare results with a hierarchical Bayesian time series (HBTS) model. We evaluated spring and fall counts, fall indices, and model-based predictions for the Rocky Mountain population (RMP) of Sandhill Cranes (Antigone canadensis) by integrating juvenile recruitment, harvest, and survival into a stochastic stage-based population model. We used simulation to evaluate population indices from the HBTS model and the commonly used 3-yr moving average estimator. We found counts of the RMP to exhibit biologically unrealistic annual change, while the fall population index was largely biologically realistic. HBTS model predictions suggested that the RMP changed little over 31 yr of monitoring, but the pattern depended on assumptions about the observational process. The HBTS model fall population predictions were biologically plausible if observed crane harvest mortality was compensatory up to natural mortality, as empirical evidence suggests. Simulations indicated that the predicted mean of the HBTS model was generally a more reliable estimate of the true population than population indices derived using a moving 3-yr average estimator. Practitioners could gain considerable advantages from modeling population counts using a hierarchical Bayesian autoregressive approach. Advantages would include: (1) obtaining measures of uncertainty; (2) incorporating direct knowledge of the observational and population processes; (3) accommodating missing years of data; and (4) forecasting population size.

Robust image modeling techniques with an image restoration application

NASA Astrophysics Data System (ADS)

Kashyap, Rangasami L.; Eom, Kie-Bum

1988-08-01

A robust parameter-estimation algorithm for a nonsymmetric half-plane (NSHP) autoregressive model, where the driving noise is a mixture of a Gaussian and an outlier process, is presented. The convergence of the estimation algorithm is proved. An algorithm to estimate parameters and original image intensity simultaneously from the impulse-noise-corrupted image, where the model governing the image is not available, is also presented. The robustness of the parameter estimates is demonstrated by simulation. Finally, an algorithm to restore realistic images is presented. The entire image generally does not obey a simple image model, but a small portion (e.g., 8 x 8) of the image is assumed to obey an NSHP model. The original image is divided into windows and the robust estimation algorithm is applied for each window. The restoration algorithm is tested by comparing it to traditional methods on several different images.

A robust ridge regression approach in the presence of both multicollinearity and outliers in the data

NASA Astrophysics Data System (ADS)

Shariff, Nurul Sima Mohamad; Ferdaos, Nur Aqilah

2017-08-01

Multicollinearity often leads to inconsistent and unreliable parameter estimates in regression analysis. This situation will be more severe in the presence of outliers it will cause fatter tails in the error distributions than the normal distributions. The well-known procedure that is robust to multicollinearity problem is the ridge regression method. This method however is expected to be affected by the presence of outliers due to some assumptions imposed in the modeling procedure. Thus, the robust version of existing ridge method with some modification in the inverse matrix and the estimated response value is introduced. The performance of the proposed method is discussed and comparisons are made with several existing estimators namely, Ordinary Least Squares (OLS), ridge regression and robust ridge regression based on GM-estimates. The finding of this study is able to produce reliable parameter estimates in the presence of both multicollinearity and outliers in the data.

Perfect count: a novel approach for the single platform enumeration of absolute CD4+ T-lymphocytes.

PubMed

Storie, Ian; Sawle, Alex; Goodfellow, Karen; Whitby, Liam; Granger, Vivian; Ward, Rosalie Y; Peel, Janet; Smart, Theresa; Reilly, John T; Barnett, David

2004-01-01

The derivation of reliable CD4(+) T lymphocyte counts is vital for the monitoring of disease progression and therapeutic effectiveness in HIV(+) individuals. Flow cytometry has emerged as the method of choice for CD4(+) T lymphocyte enumeration, with single-platform technology, coupled with reference counting beads, fast becoming the "gold standard." However, although single-platform, bead-based, sample acquisition requires the ratio of beads to cells to remain unchanged, there is no available method, until recently, to monitor this. Perfect Count beads have been developed to address this issue and to incorporate two bead populations, with different densities, to allow the detection of inadequate mixing. Comparison of the relative proportions of both beads with the manufacture's defined limits enables an internal QC check during sample acquisition. In this study, we have compared CD4(+) T lymphocyte counts, obtained from 104 HIV(+) patients, using TruCount beads with MultiSet software (defined as the predicated method) and the new Perfect Count beads, incorporating an in house sequential gating strategy. We have demonstrated an excellent degree of correlation between the predicate method and the Perfect Count system (r(2) = 0.9955; Bland Altman bias +27 CD4(+) T lymphocytes/microl). The Perfect Count system is a robust method for performing single platform absolute counts and has the added advantage of having internal QC checks. Such an approach enables the operator to identify potential problems during sample preparation, acquisition and analysis. Copyright 2003 Wiley-Liss, Inc.

Development of a new time domain-based algorithm for train detection and axle counting

NASA Astrophysics Data System (ADS)

Allotta, B.; D'Adamio, P.; Meli, E.; Pugi, L.

2015-12-01

This paper presents an innovative train detection algorithm, able to perform the train localisation and, at the same time, to estimate its speed, the crossing times on a fixed point of the track and the axle number. The proposed solution uses the same approach to evaluate all these quantities, starting from the knowledge of generic track inputs directly measured on the track (for example, the vertical forces on the sleepers, the rail deformation and the rail stress). More particularly, all the inputs are processed through cross-correlation operations to extract the required information in terms of speed, crossing time instants and axle counter. This approach has the advantage to be simple and less invasive than the standard ones (it requires less equipment) and represents a more reliable and robust solution against numerical noise because it exploits the whole shape of the input signal and not only the peak values. A suitable and accurate multibody model of railway vehicle and flexible track has also been developed by the authors to test the algorithm when experimental data are not available and in general, under any operating conditions (fundamental to verify the algorithm accuracy and robustness). The railway vehicle chosen as benchmark is the Manchester Wagon, modelled in the Adams VI-Rail environment. The physical model of the flexible track has been implemented in the Matlab and Comsol Multiphysics environments. A simulation campaign has been performed to verify the performance and the robustness of the proposed algorithm, and the results are quite promising. The research has been carried out in cooperation with Ansaldo STS and ECM Spa.

Estimating nest detection probabilities for white-winged dove nest transects in Tamaulipas, Mexico

USGS Publications Warehouse

Nichols, J.D.; Tomlinson, R.E.; Waggerman, G.

1986-01-01

Nest transects in nesting colonies provide one source of information on White-winged Dove (Zenaida asiatica asiatica) population status and reproduction. Nests are counted along transects using standardized field methods each year in Texas and northeastern Mexico by personnel associated with Mexico's Office of Flora and Fauna, the Texas Parks and Wildlife Department, and the U.S. Fish and Wildlife Service. Nest counts on transects are combined with information on the size of nesting colonies to estimate total numbers of nests in sampled colonies. Historically, these estimates have been based on the actual nest counts on transects and thus have required the assumption that all nests lying within transect boundaries are detected (seen) with a probability of one. Our objectives were to test the hypothesis that nest detection probability is one and, if rejected, to estimate this probability.

Novel approaches to address spectral distortions in photon counting x-ray CT using artificial neural networks

NASA Astrophysics Data System (ADS)

Touch, M.; Clark, D. P.; Barber, W.; Badea, C. T.

2016-04-01

Spectral CT using a photon-counting x-ray detector (PCXD) can potentially increase accuracy of measuring tissue composition. However, PCXD spectral measurements suffer from distortion due to charge sharing, pulse pileup, and Kescape energy loss. This study proposes two novel artificial neural network (ANN)-based algorithms: one to model and compensate for the distortion, and another one to directly correct for the distortion. The ANN-based distortion model was obtained by training to learn the distortion from a set of projections with a calibration scan. The ANN distortion was then applied in the forward statistical model to compensate for distortion in the projection decomposition. ANN was also used to learn to correct distortions directly in projections. The resulting corrected projections were used for reconstructing the image, denoising via joint bilateral filtration, and decomposition into three-material basis functions: Compton scattering, the photoelectric effect, and iodine. The ANN-based distortion model proved to be more robust to noise and worked better compared to using an imperfect parametric distortion model. In the presence of noise, the mean relative errors in iodine concentration estimation were 11.82% (ANN distortion model) and 16.72% (parametric model). With distortion correction, the mean relative error in iodine concentration estimation was improved by 50% over direct decomposition from distorted data. With our joint bilateral filtration, the resulting material image quality and iodine detectability as defined by the contrast-to-noise ratio were greatly enhanced allowing iodine concentrations as low as 2 mg/ml to be detected. Future work will be dedicated to experimental evaluation of our ANN-based methods using 3D-printed phantoms.

Aerial estimation of the size of gull breeding colonies

USGS Publications Warehouse

Kadlec, J.A.; Drury, W.H.

1968-01-01

Counts on photographs and visual estimates of the numbers of territorial gulls are usually reliable indicators of the number of gull nests, but single visual estimates are not adequate to measure the number of nests in individual colonies. To properly interpret gull counts requires that several islands with known numbers of nests be photographed to establish the ratio of gulls to nests applicable for a given local census. Visual estimates are adequate to determine total breeding gull numbers by regions. Neither visual estimates nor photography will reliably detect annual changes of less than about 2.5 percent.

Ageing and long-term CD4 cell count trends in HIV-positive patients with 5 years or more combination antiretroviral therapy experience.

PubMed

Wright, S T; Petoumenos, K; Boyd, M; Carr, A; Downing, S; O'Connor, C C; Grotowski, M; Law, M G

2013-04-01

The aim of this study was to describe the long-term changes in CD4 cell counts beyond 5 years of combination antiretroviral therapy (cART). If natural ageing leads to a long-term decline in the immune system via low-grade chronic immune activation/inflammation, then one might expect to see a greater or earlier decline in CD4 counts in older HIV-positive patients with increasing duration of cART. Retrospective and prospective data were examined from long-term virologically stable HIV-positive adults from the Australian HIV Observational Database. We estimated mean CD4 cell count changes following the completion of 5 years of cART using linear mixed models. A total of 37 916 CD4 measurements were observed for 892 patients over a combined total of 9753 patient-years. Older patients (> 50 years old) at cART initiation had estimated mean (95% confidence interval) changes in CD4 counts by year-5 CD4 count strata (< 500, 500-750 and > 750 cells/μL) of 14 (7 to 21), 3 (-5 to 11) and -6 (-17 to 4) cells/μL/year. Of the CD4 cell count rates of change estimated, none were indicative of long-term declines in CD4 cell counts. Our results suggest that duration of cART and increasing age do not result in decreasing mean changes in CD4 cell counts for long-term virologically suppressed patients, indicating that the level of immune recovery achieved during the first 5 years of treatment is sustained through long-term cART. © 2012 British HIV Association.

Ageing & long-term CD4 cell count trends in HIV-positive patients with 5 years or more combination antiretroviral therapy experience

PubMed Central

WRIGHT, ST; PETOUMENOS, K; BOYD, M; CARR, A; DOWNING, S; O’CONNOR, CC; GROTOWSKI, M; LAW, MG

2012-01-01

Background The aim of this analysis is to describe the long-term changes in CD4 cell counts beyond 5 years of combination antiretroviral therapy (cART). If natural ageing leads to a long-term decline in the immune system via low-grade chronic immune activation/inflammation, then one might expect to see a greater or earlier decline in CD4 counts in older HIV-positive patients with increasing duration of cART. Methods Retrospective and prospective data were examined from long-term virologically stable HIV-positive adults from the Australian HIV Observational Database. We estimated mean CD4 cell counts changes following the completion of 5 years of cART using linear mixed models. Results A total of 37,916 CD4 measurements were observed for 892 patients over a combined total of 9,753 patient years. Older patients (>50 years) at cART initiation had estimated mean(95% confidence interval) change in CD4 counts by Year-5 CD4 count strata (<500, 501–750 and >750 cells/μL) of 14(7 to 21), 3(−5 to 11) and −6(−17 to 4) cells/μL/year. Of the CD4 cell count rates of change estimated, none were indicative of long-term declines in CD4 cell counts. Conclusions Our results suggest that duration of cART and increasing age does not result in decreasing mean changes in CD4 cell counts for long-term virologically suppressed patients. Indicating that level of immune recovery achieved during the first 5 years of treatment are sustained through long-term cART. PMID:23036045

Minimum number of days required for a reliable estimate of daily step count and energy expenditure, in people with MS who walk unaided.

PubMed

Norris, Michelle; Anderson, Ross; Motl, Robert W; Hayes, Sara; Coote, Susan

2017-03-01

The purpose of this study was to examine the minimum number of days needed to reliably estimate daily step count and energy expenditure (EE), in people with multiple sclerosis (MS) who walked unaided. Seven days of activity monitor data were collected for 26 participants with MS (age=44.5±11.9years; time since diagnosis=6.5±6.2years; Patient Determined Disease Steps=≤3). Mean daily step count and mean daily EE (kcal) were calculated for all combinations of days (127 combinations), and compared to the respective 7-day mean daily step count or mean daily EE using intra-class correlations (ICC), the Generalizability Theory and Bland-Altman. For step count, ICC values of 0.94-0.98 and a G-coefficient of 0.81 indicate a minimum of any random 2-day combination is required to reliably calculate mean daily step count. For EE, ICC values of 0.96-0.99 and a G-coefficient of 0.83 indicate a minimum of any random 4-day combination is required to reliably calculate mean daily EE. For Bland-Altman analyses all combinations of days, bar single day combinations, resulted in a mean bias within ±10%, when expressed as a percentage of the 7-day mean daily step count or mean daily EE. A minimum of 2days for step count and 4days for EE, regardless of day type, is needed to reliably estimate daily step count and daily EE, in people with MS who walk unaided. Copyright © 2017 Elsevier B.V. All rights reserved.

Zero-state Markov switching count-data models: an empirical assessment.

PubMed

Malyshkina, Nataliya V; Mannering, Fred L

2010-01-01

In this study, a two-state Markov switching count-data model is proposed as an alternative to zero-inflated models to account for the preponderance of zeros sometimes observed in transportation count data, such as the number of accidents occurring on a roadway segment over some period of time. For this accident-frequency case, zero-inflated models assume the existence of two states: one of the states is a zero-accident count state, which has accident probabilities that are so low that they cannot be statistically distinguished from zero, and the other state is a normal-count state, in which counts can be non-negative integers that are generated by some counting process, for example, a Poisson or negative binomial. While zero-inflated models have come under some criticism with regard to accident-frequency applications - one fact is undeniable - in many applications they provide a statistically superior fit to the data. The Markov switching approach we propose seeks to overcome some of the criticism associated with the zero-accident state of the zero-inflated model by allowing individual roadway segments to switch between zero and normal-count states over time. An important advantage of this Markov switching approach is that it allows for the direct statistical estimation of the specific roadway-segment state (i.e., zero-accident or normal-count state) whereas traditional zero-inflated models do not. To demonstrate the applicability of this approach, a two-state Markov switching negative binomial model (estimated with Bayesian inference) and standard zero-inflated negative binomial models are estimated using five-year accident frequencies on Indiana interstate highway segments. It is shown that the Markov switching model is a viable alternative and results in a superior statistical fit relative to the zero-inflated models.

Traffic effects on bird counts on North American Breeding Bird Survey routes

USGS Publications Warehouse

Griffith, Emily H.; Sauer, John R.; Royle, J. Andrew

2010-01-01

The North American Breeding Bird Survey (BBS) is an annual roadside survey used to estimate population change in >420 species of birds that breed in North America. Roadside sampling has been criticized, in part because traffic noise can interfere with bird counts. Since 1997, data have been collected on the numbers of vehicles that pass during counts at each stop. We assessed the effect of traffic by modeling total vehicles as a covariate of counts in hierarchical Poisson regression models used to estimate population change. We selected species for analysis that represent birds detected at low and high abundance and birds with songs of low and high frequencies. Increases in vehicle counts were associated with decreases in bird counts in most of the species examined. The size and direction of these effects remained relatively constant between two alternative models that we analyzed. Although this analysis indicated only a small effect of incorporating traffic effects when modeling roadside counts of birds, we suggest that continued evaluation of changes in traffic at BBS stops should be a component of future BBS analyses.

Robustness enhancement of neurocontroller and state estimator

NASA Technical Reports Server (NTRS)

Troudet, Terry

1993-01-01

The feasibility of enhancing neurocontrol robustness, through training of the neurocontroller and state estimator in the presence of system uncertainties, is investigated on the example of a multivariable aircraft control problem. The performance and robustness of the newly trained neurocontroller are compared to those for an existing neurocontrol design scheme. The newly designed dynamic neurocontroller exhibits a better trade-off between phase and gain stability margins, and it is significantly more robust to degradations of the plant dynamics.

Detection ratios on winter surveys of Rocky Mountain Trumpeter Swans Cygnus buccinator

USGS Publications Warehouse

Bart, J.; Mitchell, C.D.; Fisher, M.N.; Dubovsky, J.A.

2007-01-01

We estimated the detection ratio for Rocky Mountain Trumpeter Swans Cygnus buccinator that were counted during aerial surveys made in winter. The standard survey involved counting white or grey birds on snow and ice and thus might be expected to have had low detection ratios. On the other hand, observers were permitted to circle areas where the birds were concentrated multiple times to obtain accurate counts. Actual numbers present were estimated by conducting additional intensive aerial counts either immediately before or immediately after the standard count. Surveyors continued the intensive surveys at each area until consecutive counts were identical. The surveys were made at 10 locations in 2006 and at 19 locations in 2007. A total of 2,452 swans were counted on the intensive surveys. Detection ratios did not vary detectably with year, observer, which survey was conducted first, age of the swans, or the number of swans present. The overall detection ratio was 0.93 (90% confidence interval 0.82-1.04), indicating that the counts were quite accurate. Results are used to depict changes in population size for Rocky Mountain Trumpeter Swans from 1974-2007. ?? Wildfowl & Wetlands Trust.

Can Detectability Analysis Improve the Utility of Point Counts for Temperate Forest Raptors?

EPA Science Inventory

Temperate forest breeding raptors are poorly represented in typical point count surveys because these birds are cryptic and typically breed at low densities. In recent years, many new methods for estimating detectability during point counts have been developed, including distanc...

32-channel single photon counting module for ultrasensitive detection of DNA sequences

NASA Astrophysics Data System (ADS)

Gudkov, Georgiy; Dhulla, Vinit; Borodin, Anatoly; Gavrilov, Dmitri; Stepukhovich, Andrey; Tsupryk, Andrey; Gorbovitski, Boris; Gorfinkel, Vera

2006-10-01

We continue our work on the design and implementation of multi-channel single photon detection systems for highly sensitive detection of ultra-weak fluorescence signals, for high-performance, multi-lane DNA sequencing instruments. A fiberized, 32-channel single photon detection (SPD) module based on single photon avalanche diode (SPAD), model C30902S-DTC, from Perkin Elmer Optoelectronics (PKI) has been designed and implemented. Unavailability of high performance, large area SPAD arrays and our desire to design high performance photon counting systems drives us to use individual diodes. Slight modifications in our quenching circuit has doubled the linear range of our system from 1MHz to 2MHz, which is the upper limit for these devices and the maximum saturation count rate has increased to 14 MHz. The detector module comprises of a single board computer PC-104 that enables data visualization, recording, processing, and transfer. Very low dark count (300-1000 counts/s), robust, efficient, simple data collection and processing, ease of connectivity to any other application demanding similar requirements and similar performance results to the best commercially available single photon counting module (SPCM from PKI) are some of the features of this system.

Statistical approaches to the analysis of point count data: A little extra information can go a long way

USGS Publications Warehouse

Farnsworth, G.L.; Nichols, J.D.; Sauer, J.R.; Fancy, S.G.; Pollock, K.H.; Shriner, S.A.; Simons, T.R.; Ralph, C. John; Rich, Terrell D.

2005-01-01

Point counts are a standard sampling procedure for many bird species, but lingering concerns still exist about the quality of information produced from the method. It is well known that variation in observer ability and environmental conditions can influence the detection probability of birds in point counts, but many biologists have been reluctant to abandon point counts in favor of more intensive approaches to counting. However, over the past few years a variety of statistical and methodological developments have begun to provide practical ways of overcoming some of the problems with point counts. We describe some of these approaches, and show how they can be integrated into standard point count protocols to greatly enhance the quality of the information. Several tools now exist for estimation of detection probability of birds during counts, including distance sampling, double observer methods, time-depletion (removal) methods, and hybrid methods that combine these approaches. Many counts are conducted in habitats that make auditory detection of birds much more likely than visual detection. As a framework for understanding detection probability during such counts, we propose separating two components of the probability a bird is detected during a count into (1) the probability a bird vocalizes during the count and (2) the probability this vocalization is detected by an observer. In addition, we propose that some measure of the area sampled during a count is necessary for valid inferences about bird populations. This can be done by employing fixed-radius counts or more sophisticated distance-sampling models. We recommend any studies employing point counts be designed to estimate detection probability and to include a measure of the area sampled.

A variable circular-plot method for estimating bird numbers

Treesearch

R. T. Reynolds; J. M. Scott; R. A. Nussbaum

1980-01-01

A bird census method is presented that is designed for tall, structurally complex vegetation types, and rugged terrain. With this method the observer counts all birds seen or heard around a station, and estimates the horizontal distance from the station to each bird. Count periods at stations vary according to the avian community and structural complexity of the...

Field evaluation of distance-estimation error during wetland-dependent bird surveys

USGS Publications Warehouse

Nadeau, Christopher P.; Conway, Courtney J.

2012-01-01

Context: The most common methods to estimate detection probability during avian point-count surveys involve recording a distance between the survey point and individual birds detected during the survey period. Accurately measuring or estimating distance is an important assumption of these methods; however, this assumption is rarely tested in the context of aural avian point-count surveys. Aims: We expand on recent bird-simulation studies to document the error associated with estimating distance to calling birds in a wetland ecosystem. Methods: We used two approaches to estimate the error associated with five surveyor's distance estimates between the survey point and calling birds, and to determine the factors that affect a surveyor's ability to estimate distance. Key results: We observed biased and imprecise distance estimates when estimating distance to simulated birds in a point-count scenario (x̄error = -9 m, s.d.error = 47 m) and when estimating distances to real birds during field trials (x̄error = 39 m, s.d.error = 79 m). The amount of bias and precision in distance estimates differed among surveyors; surveyors with more training and experience were less biased and more precise when estimating distance to both real and simulated birds. Three environmental factors were important in explaining the error associated with distance estimates, including the measured distance from the bird to the surveyor, the volume of the call and the species of bird. Surveyors tended to make large overestimations to birds close to the survey point, which is an especially serious error in distance sampling. Conclusions: Our results suggest that distance-estimation error is prevalent, but surveyor training may be the easiest way to reduce distance-estimation error. Implications: The present study has demonstrated how relatively simple field trials can be used to estimate the error associated with distance estimates used to estimate detection probability during avian point-count surveys. Evaluating distance-estimation errors will allow investigators to better evaluate the accuracy of avian density and trend estimates. Moreover, investigators who evaluate distance-estimation errors could employ recently developed models to incorporate distance-estimation error into analyses. We encourage further development of such models, including the inclusion of such models into distance-analysis software.

Robust versus consistent variance estimators in marginal structural Cox models.

PubMed

Enders, Dirk; Engel, Susanne; Linder, Roland; Pigeot, Iris

2018-06-11

In survival analyses, inverse-probability-of-treatment (IPT) and inverse-probability-of-censoring (IPC) weighted estimators of parameters in marginal structural Cox models are often used to estimate treatment effects in the presence of time-dependent confounding and censoring. In most applications, a robust variance estimator of the IPT and IPC weighted estimator is calculated leading to conservative confidence intervals. This estimator assumes that the weights are known rather than estimated from the data. Although a consistent estimator of the asymptotic variance of the IPT and IPC weighted estimator is generally available, applications and thus information on the performance of the consistent estimator are lacking. Reasons might be a cumbersome implementation in statistical software, which is further complicated by missing details on the variance formula. In this paper, we therefore provide a detailed derivation of the variance of the asymptotic distribution of the IPT and IPC weighted estimator and explicitly state the necessary terms to calculate a consistent estimator of this variance. We compare the performance of the robust and consistent variance estimators in an application based on routine health care data and in a simulation study. The simulation reveals no substantial differences between the 2 estimators in medium and large data sets with no unmeasured confounding, but the consistent variance estimator performs poorly in small samples or under unmeasured confounding, if the number of confounders is large. We thus conclude that the robust estimator is more appropriate for all practical purposes. Copyright © 2018 John Wiley & Sons, Ltd.

Cryptographic robustness of a quantum cryptography system using phase-time coding

DOE Office of Scientific and Technical Information (OSTI.GOV)

Molotkov, S. N.

2008-01-15

A cryptographic analysis is presented of a new quantum key distribution protocol using phase-time coding. An upper bound is obtained for the error rate that guarantees secure key distribution. It is shown that the maximum tolerable error rate for this protocol depends on the counting rate in the control time slot. When no counts are detected in the control time slot, the protocol guarantees secure key distribution if the bit error rate in the sifted key does not exceed 50%. This protocol partially discriminates between errors due to system defects (e.g., imbalance of a fiber-optic interferometer) and eavesdropping. In themore » absence of eavesdropping, the counts detected in the control time slot are not caused by interferometer imbalance, which reduces the requirements for interferometer stability.« less

Robust Modal Filtering and Control of the X-56A Model with Simulated Fiber Optic Sensor Failures

NASA Technical Reports Server (NTRS)

Suh, Peter M.; Chin, Alexander W.; Marvis, Dimitri N.

2014-01-01

The X-56A aircraft is a remotely-piloted aircraft with flutter modes intentionally designed into the flight envelope. The X-56A program must demonstrate flight control while suppressing all unstable modes. A previous X-56A model study demonstrated a distributed-sensing-based active shape and active flutter suppression controller. The controller relies on an estimator which is sensitive to bias. This estimator is improved herein, and a real-time robust estimator is derived and demonstrated on 1530 fiber optic sensors. It is shown in simulation that the estimator can simultaneously reject 230 worst-case fiber optic sensor failures automatically. These sensor failures include locations with high leverage (or importance). To reduce the impact of leverage outliers, concentration based on a Mahalanobis trim criterion is introduced. A redescending M-estimator with Tukey bisquare weights is used to improve location and dispersion estimates within each concentration step in the presence of asymmetry (or leverage). A dynamic simulation is used to compare the concentrated robust estimator to a state-of-the-art real-time robust multivariate estimator. The estimators support a previously-derived mu-optimal shape controller. It is found that during the failure scenario, the concentrated modal estimator keeps the system stable.

Robust Modal Filtering and Control of the X-56A Model with Simulated Fiber Optic Sensor Failures

NASA Technical Reports Server (NTRS)

Suh, Peter M.; Chin, Alexander W.; Mavris, Dimitri N.

2016-01-01

The X-56A aircraft is a remotely-piloted aircraft with flutter modes intentionally designed into the flight envelope. The X-56A program must demonstrate flight control while suppressing all unstable modes. A previous X-56A model study demonstrated a distributed-sensing-based active shape and active flutter suppression controller. The controller relies on an estimator which is sensitive to bias. This estimator is improved herein, and a real-time robust estimator is derived and demonstrated on 1530 fiber optic sensors. It is shown in simulation that the estimator can simultaneously reject 230 worst-case fiber optic sensor failures automatically. These sensor failures include locations with high leverage (or importance). To reduce the impact of leverage outliers, concentration based on a Mahalanobis trim criterion is introduced. A redescending M-estimator with Tukey bisquare weights is used to improve location and dispersion estimates within each concentration step in the presence of asymmetry (or leverage). A dynamic simulation is used to compare the concentrated robust estimator to a state-of-the-art real-time robust multivariate estimator. The estimators support a previously-derived mu-optimal shape controller. It is found that during the failure scenario, the concentrated modal estimator keeps the system stable.

The Robustness of LISREL Estimates in Structural Equation Models with Categorical Variables.

ERIC Educational Resources Information Center

Ethington, Corinna A.

1987-01-01

This study examined the effect of type of correlation matrix on the robustness of LISREL maximum likelihood and unweighted least squares structural parameter estimates for models with categorical variables. The analysis of mixed matrices produced estimates that closely approximated the model parameters except where dichotomous variables were…

Quantitation of tumor uptake with molecular breast imaging.

PubMed

Bache, Steven T; Kappadath, S Cheenu

2017-09-01

We developed scatter and attenuation-correction techniques for quantifying images obtained with Molecular Breast Imaging (MBI) systems. To investigate scatter correction, energy spectra of a 99m Tc point source were acquired with 0-7-cm-thick acrylic to simulate scatter between the detector heads. System-specific scatter correction factor, k, was calculated as a function of thickness using a dual energy window technique. To investigate attenuation correction, a 7-cm-thick rectangular phantom containing 99m Tc-water simulating breast tissue and fillable spheres simulating tumors was imaged. Six spheres 10-27 mm in diameter were imaged with sphere-to-background ratios (SBRs) of 3.5, 2.6, and 1.7 and located at depths of 0.5, 1.5, and 2.5 cm from the center of the water bath for 54 unique tumor scenarios (3 SBRs × 6 sphere sizes × 3 depths). Phantom images were also acquired in-air under scatter- and attenuation-free conditions, which provided ground truth counts. To estimate true counts, T, from each tumor, the geometric mean (GM) of the counts within a prescribed region of interest (ROI) from the two projection images was calculated as T=C1C2eμtF, where C are counts within the square ROI circumscribing each sphere on detectors 1 and 2, μ is the linear attenuation coefficient of water, t is detector separation, and the factor F accounts for background activity. Four unique F definitions-standard GM, background-subtraction GM, MIRD Primer 16 GM, and a novel "volumetric GM"-were investigated. Error in T was calculated as the percentage difference with respect to in-air. Quantitative accuracy using the different GM definitions was calculated as a function of SBR, depth, and sphere size. Sensitivity of quantitative accuracy to ROI size was investigated. We developed an MBI simulation to investigate the robustness of our corrections for various ellipsoidal tumor shapes and detector separations. Scatter correction factor k varied slightly (0.80-0.95) over a compressed breast thickness range of 6-9 cm. Corrected energy spectra recovered general characteristics of scatter-free spectra. Quantitatively, photopeak counts were recovered to <10% compared to in-air conditions after scatter correction. After GM attenuation correction, mean errors (95% confidence interval, CI) for all 54 imaging scenarios were 149% (-154% to +455%), -14.0% (-38.4% to +10.4%), 16.8% (-14.7% to +48.2%), and 2.0% (-14.3 to +18.3%) for the standard GM, background-subtraction GM, MIRD 16 GM, and volumetric GM, respectively. Volumetric GM was less sensitive to SBR and sphere size, while all GM methods were insensitive to sphere depth. Simulation results showed that Volumetric GM method produced a mean error within 5% over all compressed breast thicknesses (3-14 cm), and that the use of an estimated radius for nonspherical tumors increases the 95% CI to at most ±23%, compared with ±16% for spherical tumors. Using DEW scatter- and our Volumetric GM attenuation-correction methodology yielded accurate estimates of tumor counts in MBI over various tumor sizes, shapes, depths, background uptake, and compressed breast thicknesses. Accurate tumor uptake can be converted to radiotracer uptake concentration, allowing three patient-specific metrics to be calculated for quantifying absolute uptake and relative uptake change for assessment of treatment response. © 2017 American Association of Physicists in Medicine.

Mount Rainier National Park and Olympic National Park Elk Monitoring Program Annual Report 2010

USGS Publications Warehouse

Griffin, Paul; Happe, Patricia J.; Jenkins, Kurt J.; Reid, Mason; Vales, David J.; Moeller, Barbara J.; Tirhi, Michelle; McCorquodale, Scott; Miller, Pat

2010-01-01

Fiscal year 2010 was the third year of gathering data needed for protocol development while simultaneously implementing what is expected to be the elk monitoring protocol at Mount Rainier (MORA) and Olympic (OLYM) national parks in the North Coast and Cascades Network (NCCN). Elk monitoring in these large wilderness parks relies on aerial surveys from a helicopter. Summer surveys are planned for both parks and are intended to provide quantitative estimates of abundance, sex and age composition, and distribution of migratory elk in high elevation trend count areas. Spring surveys are planned at Olympic National Park and are intended to provide quantitative estimates of abundance of resident and migratory elk on low-elevation winter ranges within surveyed trend count areas. An unknown number of elk is not detected during surveys. The protocol under development aims to estimate the number of missed elk by applying a model that accounts for detection bias. Detection bias in elk surveys in MORA will be estimated using a double-observer sightability model that was developed based on data from surveys conducted in 2008-2010. The model was developed using elk that were previously equipped with radio collars by cooperating tribes. That model is currently in peer review. At the onset of protocol development in OLYM there were no existing radio- collars on elk. Consequently double-observer sightability models have not yet been developed for elk surveys in OLYM; the majority of the effort in OLYM has been focused on capturing and radio collaring elk to permit the development of sightability models for application in OLYM. As a result, no estimates of abundance or composition are included in this annual report, only raw counts of the numbers of elk seen in surveys. At MORA each of the two trend count areas (North Rainier herd, and South Rainier herd) were surveyed twice. 290 and 380 elk were counted on the two replicates in the North Rainier herd, and 621 and 327 elk counted on the two replicate South Rainier counts. At Olympic National Park, each of three spring trend count areas was surveyed once in March 2010. 27 elk were observed in the South Fork Hoh trend count area, 137 elk were observed in the Hoh trend count area, and 131 elk were observed in the Queets trend count area. In September 2010, 18 elk were captured and fitted with radio collars as part of a contracted animal capture, eradication and tagging of animals (ACETA) operation. These animals will be available to contribute double-observer sightability data in future spring and summer surveys. There were no summer surveys for elk in OLYM in 2010.

Bayesian inference on multiscale models for poisson intensity estimation: applications to photon-limited image denoising.

PubMed

Lefkimmiatis, Stamatios; Maragos, Petros; Papandreou, George

2009-08-01

We present an improved statistical model for analyzing Poisson processes, with applications to photon-limited imaging. We build on previous work, adopting a multiscale representation of the Poisson process in which the ratios of the underlying Poisson intensities (rates) in adjacent scales are modeled as mixtures of conjugate parametric distributions. Our main contributions include: 1) a rigorous and robust regularized expectation-maximization (EM) algorithm for maximum-likelihood estimation of the rate-ratio density parameters directly from the noisy observed Poisson data (counts); 2) extension of the method to work under a multiscale hidden Markov tree model (HMT) which couples the mixture label assignments in consecutive scales, thus modeling interscale coefficient dependencies in the vicinity of image edges; 3) exploration of a 2-D recursive quad-tree image representation, involving Dirichlet-mixture rate-ratio densities, instead of the conventional separable binary-tree image representation involving beta-mixture rate-ratio densities; and 4) a novel multiscale image representation, which we term Poisson-Haar decomposition, that better models the image edge structure, thus yielding improved performance. Experimental results on standard images with artificially simulated Poisson noise and on real photon-limited images demonstrate the effectiveness of the proposed techniques.

Optimizing the design of a reproduction toxicity test with the pond snail Lymnaea stagnalis.

PubMed

Charles, Sandrine; Ducrot, Virginie; Azam, Didier; Benstead, Rachel; Brettschneider, Denise; De Schamphelaere, Karel; Filipe Goncalves, Sandra; Green, John W; Holbech, Henrik; Hutchinson, Thomas H; Faber, Daniel; Laranjeiro, Filipe; Matthiessen, Peter; Norrgren, Leif; Oehlmann, Jörg; Reategui-Zirena, Evelyn; Seeland-Fremer, Anne; Teigeler, Matthias; Thome, Jean-Pierre; Tobor Kaplon, Marysia; Weltje, Lennart; Lagadic, Laurent

2016-11-01

This paper presents the results from two ring-tests addressing the feasibility, robustness and reproducibility of a reproduction toxicity test with the freshwater gastropod Lymnaea stagnalis (RENILYS strain). Sixteen laboratories (from inexperienced to expert laboratories in mollusc testing) from nine countries participated in these ring-tests. Survival and reproduction were evaluated in L. stagnalis exposed to cadmium, tributyltin, prochloraz and trenbolone according to an OECD draft Test Guideline. In total, 49 datasets were analysed to assess the practicability of the proposed experimental protocol, and to estimate the between-laboratory reproducibility of toxicity endpoint values. The statistical analysis of count data (number of clutches or eggs per individual-day) leading to ECx estimation was specifically developed and automated through a free web-interface. Based on a complementary statistical analysis, the optimal test duration was established and the most sensitive and cost-effective reproduction toxicity endpoint was identified, to be used as the core endpoint. This validation process and the resulting optimized protocol were used to consolidate the OECD Test Guideline for the evaluation of reproductive effects of chemicals in L. stagnalis. Copyright © 2016 Elsevier Inc. All rights reserved.

Turbulence characterization by studying laser beam wandering in a differential tracking motion setup

NASA Astrophysics Data System (ADS)

Pérez, Darío G.; Zunino, Luciano; Gulich, Damián; Funes, Gustavo; Garavaglia, Mario

2009-09-01

The Differential Image Motion Monitor (DIMM) is a standard and widely used instrument for astronomical seeing measurements. The seeing values are estimated from the variance of the differential image motion over two equal small pupils some distance apart. The twin pupils are usually cut in a mask on the entrance pupil of the telescope. As a differential method, it has the advantage of being immune to tracking errors, eliminating erratic motion of the telescope. The Differential Laser Tracking Motion (DLTM) is introduced here inspired by the same idea. Two identical laser beams are propagated through a path of air in turbulent motion, at the end of it their wander is registered by two position sensitive detectors-at a count of 800 samples per second. Time series generated from the difference of the pair of centroid laser beam coordinates is then analyzed using the multifractal detrended fluctuation analysis. Measurements were performed at the laboratory with synthetic turbulence: changing the relative separation of the beams for different turbulent regimes. The dependence, with respect to these parameters, and the robustness of our estimators is compared with the non-differential method. This method is an improvement with respect to previous approaches that study the beam wandering.

A Spatio-Temporally Explicit Random Encounter Model for Large-Scale Population Surveys

PubMed Central

Jousimo, Jussi; Ovaskainen, Otso

2016-01-01

Random encounter models can be used to estimate population abundance from indirect data collected by non-invasive sampling methods, such as track counts or camera-trap data. The classical Formozov–Malyshev–Pereleshin (FMP) estimator converts track counts into an estimate of mean population density, assuming that data on the daily movement distances of the animals are available. We utilize generalized linear models with spatio-temporal error structures to extend the FMP estimator into a flexible Bayesian modelling approach that estimates not only total population size, but also spatio-temporal variation in population density. We also introduce a weighting scheme to estimate density on habitats that are not covered by survey transects, assuming that movement data on a subset of individuals is available. We test the performance of spatio-temporal and temporal approaches by a simulation study mimicking the Finnish winter track count survey. The results illustrate how the spatio-temporal modelling approach is able to borrow information from observations made on neighboring locations and times when estimating population density, and that spatio-temporal and temporal smoothing models can provide improved estimates of total population size compared to the FMP method. PMID:27611683

Unbiased estimation of chloroplast number in mesophyll cells: advantage of a genuine three-dimensional approach

PubMed Central

Kubínová, Zuzana

2014-01-01

Chloroplast number per cell is a frequently examined quantitative anatomical parameter, often estimated by counting chloroplast profiles in two-dimensional (2D) sections of mesophyll cells. However, a mesophyll cell is a three-dimensional (3D) structure and this has to be taken into account when quantifying its internal structure. We compared 2D and 3D approaches to chloroplast counting from different points of view: (i) in practical measurements of mesophyll cells of Norway spruce needles, (ii) in a 3D model of a mesophyll cell with chloroplasts, and (iii) using a theoretical analysis. We applied, for the first time, the stereological method of an optical disector based on counting chloroplasts in stacks of spruce needle optical cross-sections acquired by confocal laser-scanning microscopy. This estimate was compared with counting chloroplast profiles in 2D sections from the same stacks of sections. Comparing practical measurements of mesophyll cells, calculations performed in a 3D model of a cell with chloroplasts as well as a theoretical analysis showed that the 2D approach yielded biased results, while the underestimation could be up to 10-fold. We proved that the frequently used method for counting chloroplasts in a mesophyll cell by counting their profiles in 2D sections did not give correct results. We concluded that the present disector method can be efficiently used for unbiased estimation of chloroplast number per mesophyll cell. This should be the method of choice, especially in coniferous needles and leaves with mesophyll cells with lignified cell walls where maceration methods are difficult or impossible to use. PMID:24336344

Nuclear counting filter based on a centered Skellam test and a double exponential smoothing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Coulon, Romain; Kondrasovs, Vladimir; Dumazert, Jonathan

2015-07-01

Online nuclear counting represents a challenge due to the stochastic nature of radioactivity. The count data have to be filtered in order to provide a precise and accurate estimation of the count rate, this with a response time compatible with the application in view. An innovative filter is presented in this paper addressing this issue. It is a nonlinear filter based on a Centered Skellam Test (CST) giving a local maximum likelihood estimation of the signal based on a Poisson distribution assumption. This nonlinear approach allows to smooth the counting signal while maintaining a fast response when brutal change activitymore » occur. The filter has been improved by the implementation of a Brown's double Exponential Smoothing (BES). The filter has been validated and compared to other state of the art smoothing filters. The CST-BES filter shows a significant improvement compared to all tested smoothing filters. (authors)« less

A comparison of observation-level random effect and Beta-Binomial models for modelling overdispersion in Binomial data in ecology & evolution.

PubMed

Harrison, Xavier A

2015-01-01

Overdispersion is a common feature of models of biological data, but researchers often fail to model the excess variation driving the overdispersion, resulting in biased parameter estimates and standard errors. Quantifying and modeling overdispersion when it is present is therefore critical for robust biological inference. One means to account for overdispersion is to add an observation-level random effect (OLRE) to a model, where each data point receives a unique level of a random effect that can absorb the extra-parametric variation in the data. Although some studies have investigated the utility of OLRE to model overdispersion in Poisson count data, studies doing so for Binomial proportion data are scarce. Here I use a simulation approach to investigate the ability of both OLRE models and Beta-Binomial models to recover unbiased parameter estimates in mixed effects models of Binomial data under various degrees of overdispersion. In addition, as ecologists often fit random intercept terms to models when the random effect sample size is low (<5 levels), I investigate the performance of both model types under a range of random effect sample sizes when overdispersion is present. Simulation results revealed that the efficacy of OLRE depends on the process that generated the overdispersion; OLRE failed to cope with overdispersion generated from a Beta-Binomial mixture model, leading to biased slope and intercept estimates, but performed well for overdispersion generated by adding random noise to the linear predictor. Comparison of parameter estimates from an OLRE model with those from its corresponding Beta-Binomial model readily identified when OLRE were performing poorly due to disagreement between effect sizes, and this strategy should be employed whenever OLRE are used for Binomial data to assess their reliability. Beta-Binomial models performed well across all contexts, but showed a tendency to underestimate effect sizes when modelling non-Beta-Binomial data. Finally, both OLRE and Beta-Binomial models performed poorly when models contained <5 levels of the random intercept term, especially for estimating variance components, and this effect appeared independent of total sample size. These results suggest that OLRE are a useful tool for modelling overdispersion in Binomial data, but that they do not perform well in all circumstances and researchers should take care to verify the robustness of parameter estimates of OLRE models.

Estimation method for serial dilution experiments.

PubMed

Ben-David, Avishai; Davidson, Charles E

2014-12-01

Titration of microorganisms in infectious or environmental samples is a corner stone of quantitative microbiology. A simple method is presented to estimate the microbial counts obtained with the serial dilution technique for microorganisms that can grow on bacteriological media and develop into a colony. The number (concentration) of viable microbial organisms is estimated from a single dilution plate (assay) without a need for replicate plates. Our method selects the best agar plate with which to estimate the microbial counts, and takes into account the colony size and plate area that both contribute to the likelihood of miscounting the number of colonies on a plate. The estimate of the optimal count given by our method can be used to narrow the search for the best (optimal) dilution plate and saves time. The required inputs are the plate size, the microbial colony size, and the serial dilution factors. The proposed approach shows relative accuracy well within ±0.1log10 from data produced by computer simulations. The method maintains this accuracy even in the presence of dilution errors of up to 10% (for both the aliquot and diluent volumes), microbial counts between 10(4) and 10(12) colony-forming units, dilution ratios from 2 to 100, and plate size to colony size ratios between 6.25 to 200. Published by Elsevier B.V.

Automated detection and enumeration of marine wildlife using unmanned aircraft systems (UAS) and thermal imagery

PubMed Central

Seymour, A. C.; Dale, J.; Hammill, M.; Halpin, P. N.; Johnston, D. W.

2017-01-01

Estimating animal populations is critical for wildlife management. Aerial surveys are used for generating population estimates, but can be hampered by cost, logistical complexity, and human risk. Additionally, human counts of organisms in aerial imagery can be tedious and subjective. Automated approaches show promise, but can be constrained by long setup times and difficulty discriminating animals in aggregations. We combine unmanned aircraft systems (UAS), thermal imagery and computer vision to improve traditional wildlife survey methods. During spring 2015, we flew fixed-wing UAS equipped with thermal sensors, imaging two grey seal (Halichoerus grypus) breeding colonies in eastern Canada. Human analysts counted and classified individual seals in imagery manually. Concurrently, an automated classification and detection algorithm discriminated seals based upon temperature, size, and shape of thermal signatures. Automated counts were within 95–98% of human estimates; at Saddle Island, the model estimated 894 seals compared to analyst counts of 913, and at Hay Island estimated 2188 seals compared to analysts’ 2311. The algorithm improves upon shortcomings of computer vision by effectively recognizing seals in aggregations while keeping model setup time minimal. Our study illustrates how UAS, thermal imagery, and automated detection can be combined to efficiently collect population data critical to wildlife management. PMID:28338047

Automated detection and enumeration of marine wildlife using unmanned aircraft systems (UAS) and thermal imagery

NASA Astrophysics Data System (ADS)

Seymour, A. C.; Dale, J.; Hammill, M.; Halpin, P. N.; Johnston, D. W.

2017-03-01

Estimating animal populations is critical for wildlife management. Aerial surveys are used for generating population estimates, but can be hampered by cost, logistical complexity, and human risk. Additionally, human counts of organisms in aerial imagery can be tedious and subjective. Automated approaches show promise, but can be constrained by long setup times and difficulty discriminating animals in aggregations. We combine unmanned aircraft systems (UAS), thermal imagery and computer vision to improve traditional wildlife survey methods. During spring 2015, we flew fixed-wing UAS equipped with thermal sensors, imaging two grey seal (Halichoerus grypus) breeding colonies in eastern Canada. Human analysts counted and classified individual seals in imagery manually. Concurrently, an automated classification and detection algorithm discriminated seals based upon temperature, size, and shape of thermal signatures. Automated counts were within 95-98% of human estimates; at Saddle Island, the model estimated 894 seals compared to analyst counts of 913, and at Hay Island estimated 2188 seals compared to analysts’ 2311. The algorithm improves upon shortcomings of computer vision by effectively recognizing seals in aggregations while keeping model setup time minimal. Our study illustrates how UAS, thermal imagery, and automated detection can be combined to efficiently collect population data critical to wildlife management.

Measuring the Social Recreation Per-Day Net Benefit of the Wildlife Amenities of a National Park: A Count-Data Travel-Cost Approach

NASA Astrophysics Data System (ADS)

Mendes, Isabel; Proença, Isabel

2011-11-01

In this article, we apply count-data travel-cost methods to a truncated sample of visitors to estimate the Peneda-Gerês National Park (PGNP) average consumer surplus (CS) for each day of visit. The measurement of recreation demand is highly specific because it is calculated by number of days of stay per visit. We therefore propose the application of altered truncated count-data models or truncated count-data models on grouped data to estimate a single, on-site individual recreation demand function, with the price (cost) of each recreation day per trip equal to out-of-pocket and time travel plus out-of-pocket and on-site time costs. We further check the sensitivity of coefficient estimations to alternative models and analyse the welfare measure precision by using the delta and simulation methods by Creel and Loomis. With simulated limits, CS is estimated to be €194 (range €116 to €448). This information is of use in the quest to improve government policy and PNPG management and conservation as well as promote nature-based tourism. To our knowledge, this is the first attempt to measure the average recreation net benefits of each day of stay generated by a national park by using truncated altered and truncated grouped count-data travel-cost models based on observing the individual number of days of stay.

Measuring the social recreation per-day net benefit of the wildlife amenities of a national park: a count-data travel-cost approach.

PubMed

Mendes, Isabel; Proença, Isabel

2011-11-01

In this article, we apply count-data travel-cost methods to a truncated sample of visitors to estimate the Peneda-Gerês National Park (PGNP) average consumer surplus (CS) for each day of visit. The measurement of recreation demand is highly specific because it is calculated by number of days of stay per visit. We therefore propose the application of altered truncated count-data models or truncated count-data models on grouped data to estimate a single, on-site individual recreation demand function, with the price (cost) of each recreation day per trip equal to out-of-pocket and time travel plus out-of-pocket and on-site time costs. We further check the sensitivity of coefficient estimations to alternative models and analyse the welfare measure precision by using the delta and simulation methods by Creel and Loomis. With simulated limits, CS is estimated to be 194 (range 116 to 448). This information is of use in the quest to improve government policy and PNPG management and conservation as well as promote nature-based tourism. To our knowledge, this is the first attempt to measure the average recreation net benefits of each day of stay generated by a national park by using truncated altered and truncated grouped count-data travel-cost models based on observing the individual number of days of stay.

Regression analysis of mixed recurrent-event and panel-count data.

PubMed

Zhu, Liang; Tong, Xinwei; Sun, Jianguo; Chen, Manhua; Srivastava, Deo Kumar; Leisenring, Wendy; Robison, Leslie L

2014-07-01

In event history studies concerning recurrent events, two types of data have been extensively discussed. One is recurrent-event data (Cook and Lawless, 2007. The Analysis of Recurrent Event Data. New York: Springer), and the other is panel-count data (Zhao and others, 2010. Nonparametric inference based on panel-count data. Test 20: , 1-42). In the former case, all study subjects are monitored continuously; thus, complete information is available for the underlying recurrent-event processes of interest. In the latter case, study subjects are monitored periodically; thus, only incomplete information is available for the processes of interest. In reality, however, a third type of data could occur in which some study subjects are monitored continuously, but others are monitored periodically. When this occurs, we have mixed recurrent-event and panel-count data. This paper discusses regression analysis of such mixed data and presents two estimation procedures for the problem. One is a maximum likelihood estimation procedure, and the other is an estimating equation procedure. The asymptotic properties of both resulting estimators of regression parameters are established. Also, the methods are applied to a set of mixed recurrent-event and panel-count data that arose from a Childhood Cancer Survivor Study and motivated this investigation. © The Author 2014. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Automated biodosimetry using digital image analysis of fluorescence in situ hybridization specimens.

PubMed

Castleman, K R; Schulze, M; Wu, Q

1997-11-01

Fluorescence in situ hybridization (FISH) of metaphase chromosome spreads is valuable for monitoring the radiation dose to circulating lymphocytes. At low dose levels, the number of cells that must be examined to estimate aberration frequencies is quite large. An automated microscope that can perform this analysis autonomously on suitably prepared specimens promises to make practical the large-scale studies that will be required for biodosimetry in the future. This paper describes such an instrument that is currently under development. We use metaphase specimens in which the five largest chromosomes have been hybridized with different-colored whole-chromosome painting probes. An automated multiband fluorescence microscope locates the spreads and counts the number of chromosome components of each color. Digital image analysis is used to locate and isolate the cells, count chromosome components, and estimate the proportions of abnormal cells. Cells exhibiting more than two chromosomal fragments in any color correspond to a clastogenic event. These automatically derived counts are corrected for statistical bias and used to estimate the overall rate of chromosome breakage. Overlap of fluorophore emission spectra prohibits isolation of the different chromosomes into separate color channels. Image processing effectively isolates each fluorophore to a single monochrome image, simplifying the task of counting chromosome fragments and reducing the error in the algorithm. Using proportion estimation, we remove the bias introduced by counting errors, leaving accuracy restricted by sample size considerations alone.

Estimating trace-suspect match probabilities for singleton Y-STR haplotypes using coalescent theory.

PubMed

Andersen, Mikkel Meyer; Caliebe, Amke; Jochens, Arne; Willuweit, Sascha; Krawczak, Michael

2013-02-01

Estimation of match probabilities for singleton haplotypes of lineage markers, i.e. for haplotypes observed only once in a reference database augmented by a suspect profile, is an important problem in forensic genetics. We compared the performance of four estimators of singleton match probabilities for Y-STRs, namely the count estimate, both with and without Brenner's so-called 'kappa correction', the surveying estimate, and a previously proposed, but rarely used, coalescent-based approach implemented in the BATWING software. Extensive simulation with BATWING of the underlying population history, haplotype evolution and subsequent database sampling revealed that the coalescent-based approach is characterized by lower bias and lower mean squared error than the uncorrected count estimator and the surveying estimator. Moreover, in contrast to the two count estimators, both the surveying and the coalescent-based approach exhibited a good correlation between the estimated and true match probabilities. However, although its overall performance is thus better than that of any other recognized method, the coalescent-based estimator is still computation-intense on the verge of general impracticability. Its application in forensic practice therefore will have to be limited to small reference databases, or to isolated cases of particular interest, until more powerful algorithms for coalescent simulation have become available. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

A note on variance estimation in random effects meta-regression.

PubMed

Sidik, Kurex; Jonkman, Jeffrey N

2005-01-01

For random effects meta-regression inference, variance estimation for the parameter estimates is discussed. Because estimated weights are used for meta-regression analysis in practice, the assumed or estimated covariance matrix used in meta-regression is not strictly correct, due to possible errors in estimating the weights. Therefore, this note investigates the use of a robust variance estimation approach for obtaining variances of the parameter estimates in random effects meta-regression inference. This method treats the assumed covariance matrix of the effect measure variables as a working covariance matrix. Using an example of meta-analysis data from clinical trials of a vaccine, the robust variance estimation approach is illustrated in comparison with two other methods of variance estimation. A simulation study is presented, comparing the three methods of variance estimation in terms of bias and coverage probability. We find that, despite the seeming suitability of the robust estimator for random effects meta-regression, the improved variance estimator of Knapp and Hartung (2003) yields the best performance among the three estimators, and thus may provide the best protection against errors in the estimated weights.

Evaluating point count efficiency relative to territory mapping in cropland birds

Treesearch

Andre Cyr; Denis Lepage; Kathryn Freemark

1995-01-01

Species richness, composition, and abundance of farmland birds were compared between point counts (50-m, 100-m, and 150-m radius half circles) and territory mapping on three 40-ha plots in Québec, Canada. Point counts of smaller radii tended to have larger density estimates than counts of larger radii. Territory mapping detected 10 species more than 150-m...

Estimating pore and cement volumes in thin section

USGS Publications Warehouse

Halley, R.B.

1978-01-01

Point count estimates of pore, grain and cement volumes from thin sections are inaccurate, often by more than 100 percent, even though they may be surprisingly precise (reproducibility + or - 3 percent). Errors are produced by: 1) inclusion of submicroscopic pore space within solid volume and 2) edge effects caused by grain curvature within a 30-micron thick thin section. Submicroscopic porosity may be measured by various physical tests or may be visually estimated from scanning electron micrographs. Edge error takes the form of an envelope around grains and increases with decreasing grain size and sorting, increasing grain irregularity and tighter grain packing. Cements are greatly involved in edge error because of their position at grain peripheries and their generally small grain size. Edge error is minimized by methods which reduce the thickness of the sample viewed during point counting. Methods which effectively reduce thickness include use of ultra-thin thin sections or acetate peels, point counting in reflected light, or carefully focusing and counting on the upper surface of the thin section.

Towards sensitive, high-throughput, biomolecular assays based on fluorescence lifetime

NASA Astrophysics Data System (ADS)

Ioanna Skilitsi, Anastasia; Turko, Timothé; Cianfarani, Damien; Barre, Sophie; Uhring, Wilfried; Hassiepen, Ulrich; Léonard, Jérémie

2017-09-01

Time-resolved fluorescence detection for robust sensing of biomolecular interactions is developed by implementing time-correlated single photon counting in high-throughput conditions. Droplet microfluidics is used as a promising platform for the very fast handling of low-volume samples. We illustrate the potential of this very sensitive and cost-effective technology in the context of an enzymatic activity assay based on fluorescently-labeled biomolecules. Fluorescence lifetime detection by time-correlated single photon counting is shown to enable reliable discrimination between positive and negative control samples at a throughput as high as several hundred samples per second.

Determination of fetal DNA fraction from the plasma of pregnant women using sequence read counts.

PubMed

Kim, Sung K; Hannum, Gregory; Geis, Jennifer; Tynan, John; Hogg, Grant; Zhao, Chen; Jensen, Taylor J; Mazloom, Amin R; Oeth, Paul; Ehrich, Mathias; van den Boom, Dirk; Deciu, Cosmin

2015-08-01

This study introduces a novel method, referred to as SeqFF, for estimating the fetal DNA fraction in the plasma of pregnant women and to infer the underlying mechanism that allows for such statistical modeling. Autosomal regional read counts from whole-genome massively parallel single-end sequencing of circulating cell-free DNA (ccfDNA) from the plasma of 25 312 pregnant women were used to train a multivariate model. The pretrained model was then applied to 505 pregnant samples to assess the performance of SeqFF against known methodologies for fetal DNA fraction calculations. Pearson's correlation between chromosome Y and SeqFF for pregnancies with male fetuses from two independent cohorts ranged from 0.932 to 0.938. Comparison between a single-nucleotide polymorphism-based approach and SeqFF yielded a Pearson's correlation of 0.921. Paired-end sequencing suggests that shorter ccfDNA, that is, less than 150 bp in length, is nonuniformly distributed across the genome. Regions exhibiting an increased proportion of short ccfDNA, which are more likely of fetal origin, tend to provide more information in the SeqFF calculations. SeqFF is a robust and direct method to determine fetal DNA fraction. Furthermore, the method is applicable to both male and female pregnancies and can greatly improve the accuracy of noninvasive prenatal testing for fetal copy number variation. © 2015 John Wiley & Sons, Ltd.

Evaluation of cyanobacteria cell count detection derived from ...

EPA Pesticide Factsheets

Inland waters across the United States (US) are at potential risk for increased outbreaks of toxic cyanobacteria (Cyano) harmful algal bloom (HAB) events resulting from elevated water temperatures and extreme hydrologic events attributable to climate change and increased nutrient loadings associated with intensive agricultural practices. Current monitoring efforts are limited in scope due to resource limitations, analytical complexity, and data integration efforts. The goals of this study were to validate a new ocean color algorithm for satellite imagery that could potentially be used to monitor CyanoHAB events in near real-time to provide a compressive monitoring capability for freshwater lakes (>100 ha). The algorithm incorporated narrow spectral bands specific to the European Space Agency’s (ESA’s) MEdium Resolution Imaging Spectrometer (MERIS) instrument that were optimally oriented at phytoplankton pigment absorption features including phycocyanin at 620 nm. A validation of derived Cyano cell counts was performed using available in situ data assembled from existing monitoring programs across eight states in the eastern US over a 39-month period (2009–2012). Results indicated that MERIS provided robust estimates for Low (10,000–109,000 cells/mL) and Very High (>1,000,000 cells/mL) cell enumeration ranges (approximately 90% and 83%, respectively). However, the results for two intermediate ranges (110,000–299,000 and 300,000–1,000,000 cells/mL)

New approach for the quantification of processed animal proteins in feed using light microscopy.

PubMed

Veys, P; Baeten, V

2010-07-01

A revision of European Union's total feed ban on animal proteins in feed will need robust quantification methods, especially for control analyses, if tolerance levels are to be introduced, as for fishmeal in ruminant feed. In 2006, a study conducted by the Community Reference Laboratory for Animal Proteins in feedstuffs (CRL-AP) demonstrated the deficiency of the official quantification method based on light microscopy. The study concluded that the method had to be revised. This paper puts forward an improved quantification method based on three elements: (1) the preparation of permanent slides with an optical adhesive preserving all morphological markers of bones necessary for accurate identification and precision counting; (2) the use of a counting grid eyepiece reticle; and (3) new definitions for correction factors for the estimated portions of animal particles in the sediment. This revised quantification method was tested on feeds adulterated at different levels with bovine meat and bone meal (MBM) and fishmeal, and it proved to be effortless to apply. The results obtained were very close to the expected values of contamination levels for both types of adulteration (MBM or fishmeal). Calculated values were not only replicable, but also reproducible. The advantages of the new approach, including the benefits of the optical adhesive used for permanent slide mounting and the experimental conditions that need to be met to implement the new method correctly, are discussed.

Experimental estimation of snare detectability for robust threat monitoring.

PubMed

O'Kelly, Hannah J; Rowcliffe, J Marcus; Durant, Sarah; Milner-Gulland, E J

2018-02-01

Hunting with wire snares is rife within many tropical forest systems, and constitutes one of the severest threats to a wide range of vertebrate taxa. As for all threats, reliable monitoring of snaring levels is critical for assessing the relative effectiveness of management interventions. However, snares pose a particular challenge in terms of tracking spatial or temporal trends in their prevalence because they are extremely difficult to detect, and are typically spread across large, inaccessible areas. As with cryptic animal targets, any approach used to monitor snaring levels must address the issue of imperfect detection, but no standard method exists to do so. We carried out a field experiment in Keo Seima Wildlife Reserve in eastern Cambodia with the following objectives: (1) To estimate the detection probably of wire snares within a tropical forest context, and to investigate how detectability might be affected by habitat type, snare type, or observer. (2) To trial two sets of sampling protocols feasible to implement in a range of challenging field conditions. (3) To conduct a preliminary assessment of two potential analytical approaches to dealing with the resulting snare encounter data. We found that although different observers had no discernible effect on detection probability, detectability did vary between habitat type and snare type. We contend that simple repeated counts carried out at multiple sites and analyzed using binomial mixture models could represent a practical yet robust solution to the problem of monitoring snaring levels both inside and outside of protected areas. This experiment represents an important first step in developing improved methods of threat monitoring, and such methods are greatly needed in southeast Asia, as well as in as many other regions.

Modeling the Impact and Costs of Semiannual Mass Drug Administration for Accelerated Elimination of Lymphatic Filariasis

PubMed Central

de Vlas, Sake J.; Fischer, Peter U.; Weil, Gary J.; Goldman, Ann S.

2013-01-01

The Global Program to Eliminate Lymphatic Filariasis (LF) has a target date of 2020. This program is progressing well in many countries. However, progress has been slow in some countries, and others have not yet started their mass drug administration (MDA) programs. Acceleration is needed. We studied how increasing MDA frequency from once to twice per year would affect program duration and costs by using computer simulation modeling and cost projections. We used the LYMFASIM simulation model to estimate how many annual or semiannual MDA rounds would be required to eliminate LF for Indian and West African scenarios with varied pre-control endemicity and coverage levels. Results were used to estimate total program costs assuming a target population of 100,000 eligibles, a 3% discount rate, and not counting the costs of donated drugs. A sensitivity analysis was done to investigate the robustness of these results with varied assumptions for key parameters. Model predictions suggested that semiannual MDA will require the same number of MDA rounds to achieve LF elimination as annual MDA in most scenarios. Thus semiannual MDA programs should achieve this goal in half of the time required for annual programs. Due to efficiency gains, total program costs for semiannual MDA programs are projected to be lower than those for annual MDA programs in most scenarios. A sensitivity analysis showed that this conclusion is robust. Semiannual MDA is likely to shorten the time and lower the cost required for LF elimination in countries where it can be implemented. This strategy may improve prospects for global elimination of LF by the target year 2020. PMID:23301115

Robust Statistical Approaches for RSS-Based Floor Detection in Indoor Localization.

PubMed

Razavi, Alireza; Valkama, Mikko; Lohan, Elena Simona

2016-05-31

Floor detection for indoor 3D localization of mobile devices is currently an important challenge in the wireless world. Many approaches currently exist, but usually the robustness of such approaches is not addressed or investigated. The goal of this paper is to show how to robustify the floor estimation when probabilistic approaches with a low number of parameters are employed. Indeed, such an approach would allow a building-independent estimation and a lower computing power at the mobile side. Four robustified algorithms are to be presented: a robust weighted centroid localization method, a robust linear trilateration method, a robust nonlinear trilateration method, and a robust deconvolution method. The proposed approaches use the received signal strengths (RSS) measured by the Mobile Station (MS) from various heard WiFi access points (APs) and provide an estimate of the vertical position of the MS, which can be used for floor detection. We will show that robustification can indeed increase the performance of the RSS-based floor detection algorithms.

Multi-Parameter Linear Least-Squares Fitting to Poisson Data One Count at a Time

NASA Technical Reports Server (NTRS)

Wheaton, W.; Dunklee, A.; Jacobson, A.; Ling, J.; Mahoney, W.; Radocinski, R.

1993-01-01

A standard problem in gamma-ray astronomy data analysis is the decomposition of a set of observed counts, described by Poisson statistics, according to a given multi-component linear model, with underlying physical count rates or fluxes which are to be estimated from the data.

The use of a robust capture-recapture design in small mammal population studies: A field example with Microtus pennsylvanicus

USGS Publications Warehouse

Nichols, James D.; Pollock, Kenneth H.; Hines, James E.

1984-01-01

The robust design of Pollock (1982) was used to estimate parameters of a Maryland M. pennsylvanicus population. Closed model tests provided strong evidence of heterogeneity of capture probability, and model M eta (Otis et al., 1978) was selected as the most appropriate model for estimating population size. The Jolly-Seber model goodness-of-fit test indicated rejection of the model for this data set, and the M eta estimates of population size were all higher than the Jolly-Seber estimates. Both of these results are consistent with the evidence of heterogeneous capture probabilities. The authors thus used M eta estimates of population size, Jolly-Seber estimates of survival rate, and estimates of birth-immigration based on a combination of the population size and survival rate estimates. Advantages of the robust design estimates for certain inference procedures are discussed, and the design is recommended for future small mammal capture-recapture studies directed at estimation.

A robust vision-based sensor fusion approach for real-time pose estimation.

PubMed

Assa, Akbar; Janabi-Sharifi, Farrokh

2014-02-01

Object pose estimation is of great importance to many applications, such as augmented reality, localization and mapping, motion capture, and visual servoing. Although many approaches based on a monocular camera have been proposed, only a few works have concentrated on applying multicamera sensor fusion techniques to pose estimation. Higher accuracy and enhanced robustness toward sensor defects or failures are some of the advantages of these schemes. This paper presents a new Kalman-based sensor fusion approach for pose estimation that offers higher accuracy and precision, and is robust to camera motion and image occlusion, compared to its predecessors. Extensive experiments are conducted to validate the superiority of this fusion method over currently employed vision-based pose estimation algorithms.

Robust Coefficients Alpha and Omega and Confidence Intervals With Outlying Observations and Missing Data: Methods and Software.

PubMed

Zhang, Zhiyong; Yuan, Ke-Hai

2016-06-01

Cronbach's coefficient alpha is a widely used reliability measure in social, behavioral, and education sciences. It is reported in nearly every study that involves measuring a construct through multiple items. With non-tau-equivalent items, McDonald's omega has been used as a popular alternative to alpha in the literature. Traditional estimation methods for alpha and omega often implicitly assume that data are complete and normally distributed. This study proposes robust procedures to estimate both alpha and omega as well as corresponding standard errors and confidence intervals from samples that may contain potential outlying observations and missing values. The influence of outlying observations and missing data on the estimates of alpha and omega is investigated through two simulation studies. Results show that the newly developed robust method yields substantially improved alpha and omega estimates as well as better coverage rates of confidence intervals than the conventional nonrobust method. An R package coefficientalpha is developed and demonstrated to obtain robust estimates of alpha and omega.

Robust Coefficients Alpha and Omega and Confidence Intervals With Outlying Observations and Missing Data

PubMed Central

Zhang, Zhiyong; Yuan, Ke-Hai

2015-01-01

Cronbach’s coefficient alpha is a widely used reliability measure in social, behavioral, and education sciences. It is reported in nearly every study that involves measuring a construct through multiple items. With non-tau-equivalent items, McDonald’s omega has been used as a popular alternative to alpha in the literature. Traditional estimation methods for alpha and omega often implicitly assume that data are complete and normally distributed. This study proposes robust procedures to estimate both alpha and omega as well as corresponding standard errors and confidence intervals from samples that may contain potential outlying observations and missing values. The influence of outlying observations and missing data on the estimates of alpha and omega is investigated through two simulation studies. Results show that the newly developed robust method yields substantially improved alpha and omega estimates as well as better coverage rates of confidence intervals than the conventional nonrobust method. An R package coefficientalpha is developed and demonstrated to obtain robust estimates of alpha and omega. PMID:29795870

Robustness of location estimators under t-distributions: a literature review

NASA Astrophysics Data System (ADS)

Sumarni, C.; Sadik, K.; Notodiputro, K. A.; Sartono, B.

2017-03-01

The assumption of normality is commonly used in estimation of parameters in statistical modelling, but this assumption is very sensitive to outliers. The t-distribution is more robust than the normal distribution since the t-distributions have longer tails. The robustness measures of location estimators under t-distributions are reviewed and discussed in this paper. For the purpose of illustration we use the onion yield data which includes outliers as a case study and showed that the t model produces better fit than the normal model.

Evaluating probability sampling strategies for estimating redd counts: an example with Chinook salmon (Oncorhynchus tshawytscha)

Treesearch

Jean-Yves Courbois; Stephen L. Katz; Daniel J. Isaak; E. Ashley Steel; Russell F. Thurow; A. Michelle Wargo Rub; Tony Olsen; Chris E. Jordan

2008-01-01

Precise, unbiased estimates of population size are an essential tool for fisheries management. For a wide variety of salmonid fishes, redd counts from a sample of reaches are commonly used to monitor annual trends in abundance. Using a 9-year time series of georeferenced censuses of Chinook salmon (Oncorhynchus tshawytscha) redds from central Idaho,...

Estimation of U content in coffee samples by fission-track counting

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sharma, P.K.; Lal, N.; Nagpaul, K.K.

1985-06-01

Because coffee is consumed in large quantities by humans, the authors undertook the study of the uranium content of coffee as a continuation of earlier work to estimate the U content of foodstuffs. Since literature on this subject is scarce, they decided to use the well-established fission-track-counting technique to determine the U content of coffee.

Comparison of methods for estimating bird abundance and trends from historical count data

Treesearch

Frank R. Thompson; Frank A. La Sorte

2008-01-01

The use of bird counts as indices has come under increasing scrutiny because assumptions concerning detection probabilities may not be met, but there also seems to be some resistance to use of model-based approaches to estimating abundance. We used data from the United States Forest Service, Southern Region bird monitoring program to compare several common approaches...

Robust Regression for Slope Estimation in Curriculum-Based Measurement Progress Monitoring

ERIC Educational Resources Information Center

Mercer, Sterett H.; Lyons, Alina F.; Johnston, Lauren E.; Millhoff, Courtney L.

2015-01-01

Although ordinary least-squares (OLS) regression has been identified as a preferred method to calculate rates of improvement for individual students during curriculum-based measurement (CBM) progress monitoring, OLS slope estimates are sensitive to the presence of extreme values. Robust estimators have been developed that are less biased by…

Fast radio burst event rate counts - I. Interpreting the observations

NASA Astrophysics Data System (ADS)

Macquart, J.-P.; Ekers, R. D.

2018-02-01

The fluence distribution of the fast radio burst (FRB) population (the `source count' distribution, N (>F) ∝Fα), is a crucial diagnostic of its distance distribution, and hence the progenitor evolutionary history. We critically reanalyse current estimates of the FRB source count distribution. We demonstrate that the Lorimer burst (FRB 010724) is subject to discovery bias, and should be excluded from all statistical studies of the population. We re-examine the evidence for flat, α > -1, source count estimates based on the ratio of single-beam to multiple-beam detections with the Parkes multibeam receiver, and show that current data imply only a very weak constraint of α ≲ -1.3. A maximum-likelihood analysis applied to the portion of the Parkes FRB population detected above the observational completeness fluence of 2 Jy ms yields α = -2.6_{-1.3}^{+0.7 }. Uncertainties in the location of each FRB within the Parkes beam render estimates of the Parkes event rate uncertain in both normalizing survey area and the estimated post-beam-corrected completeness fluence; this uncertainty needs to be accounted for when comparing the event rate against event rates measured at other telescopes.

QuantiFly: Robust Trainable Software for Automated Drosophila Egg Counting.

PubMed

Waithe, Dominic; Rennert, Peter; Brostow, Gabriel; Piper, Matthew D W

2015-01-01

We report the development and testing of software called QuantiFly: an automated tool to quantify Drosophila egg laying. Many laboratories count Drosophila eggs as a marker of fitness. The existing method requires laboratory researchers to count eggs manually while looking down a microscope. This technique is both time-consuming and tedious, especially when experiments require daily counts of hundreds of vials. The basis of the QuantiFly software is an algorithm which applies and improves upon an existing advanced pattern recognition and machine-learning routine. The accuracy of the baseline algorithm is additionally increased in this study through correction of bias observed in the algorithm output. The QuantiFly software, which includes the refined algorithm, has been designed to be immediately accessible to scientists through an intuitive and responsive user-friendly graphical interface. The software is also open-source, self-contained, has no dependencies and is easily installed (https://github.com/dwaithe/quantifly). Compared to manual egg counts made from digital images, QuantiFly achieved average accuracies of 94% and 85% for eggs laid on transparent (defined) and opaque (yeast-based) fly media. Thus, the software is capable of detecting experimental differences in most experimental situations. Significantly, the advanced feature recognition capabilities of the software proved to be robust to food surface artefacts like bubbles and crevices. The user experience involves image acquisition, algorithm training by labelling a subset of eggs in images of some of the vials, followed by a batch analysis mode in which new images are automatically assessed for egg numbers. Initial training typically requires approximately 10 minutes, while subsequent image evaluation by the software is performed in just a few seconds. Given the average time per vial for manual counting is approximately 40 seconds, our software introduces a timesaving advantage for experiments starting with as few as 20 vials. We also describe an optional acrylic box to be used as a digital camera mount and to provide controlled lighting during image acquisition which will guarantee the conditions used in this study.

QuantiFly: Robust Trainable Software for Automated Drosophila Egg Counting

PubMed Central

Waithe, Dominic; Rennert, Peter; Brostow, Gabriel; Piper, Matthew D. W.

2015-01-01

We report the development and testing of software called QuantiFly: an automated tool to quantify Drosophila egg laying. Many laboratories count Drosophila eggs as a marker of fitness. The existing method requires laboratory researchers to count eggs manually while looking down a microscope. This technique is both time-consuming and tedious, especially when experiments require daily counts of hundreds of vials. The basis of the QuantiFly software is an algorithm which applies and improves upon an existing advanced pattern recognition and machine-learning routine. The accuracy of the baseline algorithm is additionally increased in this study through correction of bias observed in the algorithm output. The QuantiFly software, which includes the refined algorithm, has been designed to be immediately accessible to scientists through an intuitive and responsive user-friendly graphical interface. The software is also open-source, self-contained, has no dependencies and is easily installed (https://github.com/dwaithe/quantifly). Compared to manual egg counts made from digital images, QuantiFly achieved average accuracies of 94% and 85% for eggs laid on transparent (defined) and opaque (yeast-based) fly media. Thus, the software is capable of detecting experimental differences in most experimental situations. Significantly, the advanced feature recognition capabilities of the software proved to be robust to food surface artefacts like bubbles and crevices. The user experience involves image acquisition, algorithm training by labelling a subset of eggs in images of some of the vials, followed by a batch analysis mode in which new images are automatically assessed for egg numbers. Initial training typically requires approximately 10 minutes, while subsequent image evaluation by the software is performed in just a few seconds. Given the average time per vial for manual counting is approximately 40 seconds, our software introduces a timesaving advantage for experiments starting with as few as 20 vials. We also describe an optional acrylic box to be used as a digital camera mount and to provide controlled lighting during image acquisition which will guarantee the conditions used in this study. PMID:25992957

How many Laysan Teal Anas laysanensis are on Midway Atoll? Methods for monitoring abundance after reintroduction

USGS Publications Warehouse

Reynolds, Michelle H.; Courtot, Karen; Hatfield, Jeffrey

2017-01-01

Wildlife managers often request a simple approach to monitor the status of species of concern. In response to that need, we used eight years of monitoring data to estimate population size and test the validity of an index for monitoring accurately the abundance of reintroduced, endangered Laysan Teal Anas laysanensis. The population was established at Midway Atoll in the Hawaiian archipelago after 42 wild birds were translocated from Laysan Island during 2004–2005. We fitted 587 birds with unique markers during 2004–2015, recorded 21,309 sightings until March 2016, and conducted standardised survey counts during 2007–2015. A modified Lincoln-Petersen mark-resight estimator and ANCOVA models were used to test the relationship between survey counts, seasonal detectability, and population abundance. Differences were found between the breeding and non-breeding seasons in detection and how maximum counts recorded related to population estimates. The results showed strong, positive correlations between the seasonal maximum counts and population estimates. The ANCOVA models supported the use of standardised bi-monthly counts of unmarked birds as a valid index to monitor trends among years within a season at Midway Atoll. The translocated population increased to 661 adult and juvenile birds (95% CI = 608–714) by 2010, then declined by 38% between 2010 and 2012 after the Toˉhoku Japan earthquake-generated tsunami inundated 41% of the atoll and triggered an Avian Botulism type C Clostridium botulinum outbreak. Following another severe botulism outbreak during 2015, the population experienced a 37% decline. Data indicated that the Midway Atoll population, like the founding Laysan Island population, is susceptible to catastrophic population declines. Consistent standardised monitoring using simple counts, in place of mark-recapture and resightings surveys, can be used to evaluate population status over the long-term. We estimate there were 314–435 Laysan Teal (95% CI for population estimate; point estimate = 375 individuals) at Midway Atoll in 2015; c. 50% of the global population. In comparison, the most recent estimate for numbers on Laysan Island was of 339 individuals in 2012 (95% CI = 265–413). We suggest that this approach can be used to validate a survey index for any marked, reintroduced resident wildlife population.

Effect of timing of count events on estimates of sea lice abundance and interpretation of effectiveness following bath treatments.

PubMed

Gautam, R; Vanderstichel, R; Boerlage, A S; Revie, C W; Hammell, K L

2017-03-01

Effectiveness of sea lice bath treatment is often assessed by comparing pre- and post-treatment counts. However, in practice, the post-treatment counting window varies from the day of treatment to several days after treatment. In this study, we assess the effect of post-treatment lag time on sea lice abundance estimates after chemical bath treatment using data from the sea lice data management program (Fish-iTrends) between 2010 and 2014. Data on two life stages, (i) adult female (AF) and (ii) pre-adult and adult male (PAAM), were aggregated at the cage level and log-transformed. Average sea lice counts by post-treatment lag time were computed for AF and PAAM and compared relative to treatment day, using linear mixed models. There were 720 observations (treatment events) that uniquely matched pre- and post-treatment counts from 53 farms. Lag time had a significant effect on the estimated sea lice abundance, which was influenced by season and pre-treatment sea lice levels. During summer, sea lice were at a minimum when counted 1 day post-treatment irrespective of pre-treatment sea lice levels, whereas in the spring and autumn, low levels were observed for PAAM over a longer interval of time, provided the pre-treatment sea lice levels were >5-10. © 2016 John Wiley & Sons Ltd.

Linking reproduction and survival can improve model estimates of vital rates derived from limited time-series counts of pinnipeds and other species.

PubMed

Battaile, Brian C; Trites, Andrew W

2013-01-01

We propose a method to model the physiological link between somatic survival and reproductive output that reduces the number of parameters that need to be estimated by models designed to determine combinations of birth and death rates that produce historic counts of animal populations. We applied our Reproduction and Somatic Survival Linked (RSSL) method to the population counts of three species of North Pacific pinnipeds (harbor seals, Phoca vitulina richardii (Gray, 1864); northern fur seals, Callorhinus ursinus (L., 1758); and Steller sea lions, Eumetopias jubatus (Schreber, 1776))--and found our model outperformed traditional models when fitting vital rates to common types of limited datasets, such as those from counts of pups and adults. However, our model did not perform as well when these basic counts of animals were augmented with additional observations of ratios of juveniles to total non-pups. In this case, the failure of the ratios to improve model performance may indicate that the relationship between survival and reproduction is redefined or disassociated as populations change over time or that the ratio of juveniles to total non-pups is not a meaningful index of vital rates. Overall, our RSSL models show advantages to linking survival and reproduction within models to estimate the vital rates of pinnipeds and other species that have limited time-series of counts.

Interpreting surveys to estimate the size of the monarch butterfly population: Pitfalls and prospects

USGS Publications Warehouse

Pleasants, John M.; Zalucki, Myron P.; Oberhauser, Karen S.; Brower, Lincoln P.; Taylor, Orley R.; Thogmartin, Wayne E.

2017-01-01

To assess the change in the size of the eastern North American monarch butterfly summer population, studies have used long-term data sets of counts of adult butterflies or eggs per milkweed stem. Despite the observed decline in the monarch population as measured at overwintering sites in Mexico, these studies found no decline in summer counts in the Midwest, the core of the summer breeding range, leading to a suggestion that the cause of the monarch population decline is not the loss of Midwest agricultural milkweeds but increased mortality during the fall migration. Using these counts to estimate population size, however, does not account for the shift of monarch activity from agricultural fields to non-agricultural sites over the past 20 years, as a result of the loss of agricultural milkweeds due to the near-ubiquitous use of glyphosate herbicides. We present the counter-hypotheses that the proportion of the monarch population present in non-agricultural habitats, where counts are made, has increased and that counts reflect both population size and the proportion of the population observed. We use data on the historical change in the proportion of milkweeds, and thus monarch activity, in agricultural fields and non-agricultural habitats to show why using counts can produce misleading conclusions about population size. We then separate out the shifting proportion effect from the counts to estimate the population size and show that these corrected summer monarch counts show a decline over time and are correlated with the size of the overwintering population. In addition, we present evidence against the hypothesis of increased mortality during migration. The milkweed limitation hypothesis for monarch decline remains supported and conservation efforts focusing on adding milkweeds to the landscape in the summer breeding region have a sound scientific basis.

Validity of FitBit, Jawbone UP, Nike+ and other wearable devices for level and stair walking.

PubMed

Huang, Yangjian; Xu, Junkai; Yu, Bo; Shull, Peter B

2016-07-01

Increased physical activity can provide numerous health benefits. The relationship between physical activity and health assumes reliable activity measurements including step count and distance traveled. This study assessed step count and distance accuracy for Nike+ FuelBand, Jawbone UP 24, Fitbit One, Fitbit Flex, Fitbit Zip, Garmin Vivofit, Yamax CW-701, and Omron HJ-321 during level, upstairs, and downstairs walking in healthy adults. Forty subjects walked on flat ground (400m), upstairs (176 steps), and downstairs (176 steps), and a subset of 10 subjects performed treadmill walking trials to assess the influence of walking speed on accuracy. Activity monitor measured step count and distance values were compared with actual step count (determined from video recordings) and distance to determine accuracy. For level walking, step count errors in Yamax CW-701, Fitbit Zip, Fitbit One, Omron HJ-321, and Jawbone UP 24 were within 1% and distance errors in Fitbit Zip and Yamax CW-701 were within 5%. Garmin Vivofit and Omron HJ-321 were the most accurate in estimating step count for stairs with errors less than 4%. An important finding is that all activity monitors overestimated distance for stair walking by at least 45%. In general, there were not accuracy differences among activity monitors for stair walking. Accuracy did not change between moderate and fast walking speeds, though slow walking increased errors for some activity monitors. Nike+ FuelBand was the least accurate step count estimator during all walking tasks. Caution should be taken when interpreting step count and distance estimates for activities involving stairs. Copyright © 2016 Elsevier B.V. All rights reserved.

Quantitative basis for component factors of gas flow proportional counting efficiencies

NASA Astrophysics Data System (ADS)

Nichols, Michael C.

This dissertation investigates the counting efficiency calibration of a gas flow proportional counter with beta-particle emitters in order to (1) determine by measurements and simulation the values of the component factors of beta-particle counting efficiency for a proportional counter, (2) compare the simulation results and measured counting efficiencies, and (3) determine the uncertainty of the simulation and measurements. Monte Carlo simulation results by the MCNP5 code were compared with measured counting efficiencies as a function of sample thickness for 14C, 89Sr, 90Sr, and 90Y. The Monte Carlo model simulated strontium carbonate with areal thicknesses from 0.1 to 35 mg cm-2. The samples were precipitated as strontium carbonate with areal thicknesses from 3 to 33 mg cm-2 , mounted on membrane filters, and counted on a low background gas flow proportional counter. The estimated fractional standard deviation was 2--4% (except 6% for 14C) for efficiency measurements of the radionuclides. The Monte Carlo simulations have uncertainties estimated to be 5 to 6 percent for carbon-14 and 2.4 percent for strontium-89, strontium-90, and yttrium-90. The curves of simulated counting efficiency vs. sample areal thickness agreed within 3% of the curves of best fit drawn through the 25--49 measured points for each of the four radionuclides. Contributions from this research include development of uncertainty budgets for the analytical processes; evaluation of alternative methods for determining chemical yield critical to the measurement process; correcting a bias found in the MCNP normalization of beta spectra histogram; clarifying the interpretation of the commonly used ICRU beta-particle spectra for use by MCNP; and evaluation of instrument parameters as applied to the simulation model to obtain estimates of the counting efficiency from simulated pulse height tallies.

Interpreting surveys to estimate the size of the monarch butterfly population: Pitfalls and prospects.

PubMed

Pleasants, John M; Zalucki, Myron P; Oberhauser, Karen S; Brower, Lincoln P; Taylor, Orley R; Thogmartin, Wayne E

2017-01-01

To assess the change in the size of the eastern North American monarch butterfly summer population, studies have used long-term data sets of counts of adult butterflies or eggs per milkweed stem. Despite the observed decline in the monarch population as measured at overwintering sites in Mexico, these studies found no decline in summer counts in the Midwest, the core of the summer breeding range, leading to a suggestion that the cause of the monarch population decline is not the loss of Midwest agricultural milkweeds but increased mortality during the fall migration. Using these counts to estimate population size, however, does not account for the shift of monarch activity from agricultural fields to non-agricultural sites over the past 20 years, as a result of the loss of agricultural milkweeds due to the near-ubiquitous use of glyphosate herbicides. We present the counter-hypotheses that the proportion of the monarch population present in non-agricultural habitats, where counts are made, has increased and that counts reflect both population size and the proportion of the population observed. We use data on the historical change in the proportion of milkweeds, and thus monarch activity, in agricultural fields and non-agricultural habitats to show why using counts can produce misleading conclusions about population size. We then separate out the shifting proportion effect from the counts to estimate the population size and show that these corrected summer monarch counts show a decline over time and are correlated with the size of the overwintering population. In addition, we present evidence against the hypothesis of increased mortality during migration. The milkweed limitation hypothesis for monarch decline remains supported and conservation efforts focusing on adding milkweeds to the landscape in the summer breeding region have a sound scientific basis.

Using the Optical Fractionator to Estimate Total Cell Numbers in the Normal and Abnormal Developing Human Forebrain.

PubMed

Larsen, Karen B

2017-01-01

Human fetal brain development is a complex process which is vulnerable to disruption at many stages. Although histogenesis is well-documented, only a few studies have quantified cell numbers across normal human fetal brain growth. Due to the present lack of normative data it is difficult to gauge abnormal development. Furthermore, many studies of brain cell numbers have employed biased counting methods, whereas innovations in stereology during the past 20-30 years enable reliable and efficient estimates of cell numbers. However, estimates of cell volumes and densities in fetal brain samples are unreliable due to unpredictable shrinking artifacts, and the fragility of the fetal brain requires particular care in handling and processing. The optical fractionator design offers a direct and robust estimate of total cell numbers in the fetal brain with a minimum of handling of the tissue. Bearing this in mind, we have used the optical fractionator to quantify the growth of total cell numbers as a function of fetal age. We discovered a two-phased development in total cell numbers in the human fetal forebrain consisting of an initial steep rise in total cell numbers between 13 and 20 weeks of gestation, followed by a slower linear phase extending from mid-gestation to 40 weeks of gestation. Furthermore, we have demonstrated a reduced total cell number in the forebrain in fetuses with Down syndome at midgestation and in intrauterine growth-restricted fetuses during the third trimester.

Mark-resight superpopulation estimation of a wintering elk Cervus elaphus canadensis herd

USGS Publications Warehouse

Gould, W.R.; Smallidge, S.T.; Thompson, B.C.

2005-01-01

We executed four mark-resight helicopter surveys during the winter months January-February for each of the three years 1999-2001 at 7-10 day intervals to estimate population size of a wintering elk Cervus elaphus canadensis herd in northern New Mexico. We counted numbers of radio-collared and uncollared elk on a simple random sample of quadrats from the study area. Because we were unable to survey the entire study area, we adopted a superpopulation approach to estimating population size, in which the total number of collared animals within and proximate to the entire study area was determined from an independent fixed-wing aircraft. The total number of collared animals available on the quadrats surveyed was also determined and facilitated detectability estimation. We executed superpopulation estimation via the joint hypergeometric estimator using the ratio of marked elk counted to the known number extant as an estimate of effective detectability. Superpopulation size estimates were approximately four times larger than previously suspected in the vicinity of the study area. Despite consistent survey methodology, actual detection rates varied within winter periods, indicating that multiple resight flights are important for improved estimator performance. Variable detectability also suggests that reliance on mere counts of observed individuals in our area may not accurately reflect abundance. ?? Wildlife Biology (2005).

Count distribution for mixture of two exponentials as renewal process duration with applications

NASA Astrophysics Data System (ADS)

Low, Yeh Ching; Ong, Seng Huat

2016-06-01

A count distribution is presented by considering a renewal process where the distribution of the duration is a finite mixture of exponential distributions. This distribution is able to model over dispersion, a feature often found in observed count data. The computation of the probabilities and renewal function (expected number of renewals) are examined. Parameter estimation by the method of maximum likelihood is considered with applications of the count distribution to real frequency count data exhibiting over dispersion. It is shown that the mixture of exponentials count distribution fits over dispersed data better than the Poisson process and serves as an alternative to the gamma count distribution.

ROBUST: an interactive FORTRAN-77 package for exploratory data analysis using parametric, ROBUST and nonparametric location and scale estimates, data transformations, normality tests, and outlier assessment

NASA Astrophysics Data System (ADS)

Rock, N. M. S.

ROBUST calculates 53 statistics, plus significance levels for 6 hypothesis tests, on each of up to 52 variables. These together allow the following properties of the data distribution for each variable to be examined in detail: (1) Location. Three means (arithmetic, geometric, harmonic) are calculated, together with the midrange and 19 high-performance robust L-, M-, and W-estimates of location (combined, adaptive, trimmed estimates, etc.) (2) Scale. The standard deviation is calculated along with the H-spread/2 (≈ semi-interquartile range), the mean and median absolute deviations from both mean and median, and a biweight scale estimator. The 23 location and 6 scale estimators programmed cover all possible degrees of robustness. (3) Normality: Distributions are tested against the null hypothesis that they are normal, using the 3rd (√ h1) and 4th ( b 2) moments, Geary's ratio (mean deviation/standard deviation), Filliben's probability plot correlation coefficient, and a more robust test based on the biweight scale estimator. These statistics collectively are sensitive to most usual departures from normality. (4) Presence of outliers. The maximum and minimum values are assessed individually or jointly using Grubbs' maximum Studentized residuals, Harvey's and Dixon's criteria, and the Studentized range. For a single input variable, outliers can be either winsorized or eliminated and all estimates recalculated iteratively as desired. The following data-transformations also can be applied: linear, log 10, generalized Box Cox power (including log, reciprocal, and square root), exponentiation, and standardization. For more than one variable, all results are tabulated in a single run of ROBUST. Further options are incorporated to assess ratios (of two variables) as well as discrete variables, and be concerned with missing data. Cumulative S-plots (for assessing normality graphically) also can be generated. The mutual consistency or inconsistency of all these measures helps to detect errors in data as well as to assess data-distributions themselves.

Spitzer deep and wide legacy mid- and far-infrared number counts and lower limits of cosmic infrared background

NASA Astrophysics Data System (ADS)

Béthermin, M.; Dole, H.; Beelen, A.; Aussel, H.

2010-03-01

Aims: We aim to place stronger lower limits on the cosmic infrared background (CIB) brightness at 24 μm, 70 μm and 160 μm and measure the extragalactic number counts at these wavelengths in a homogeneous way from various surveys. Methods: Using Spitzer legacy data over 53.6 deg2 of various depths, we build catalogs with the same extraction method at each wavelength. Completeness and photometric accuracy are estimated with Monte-Carlo simulations. Number count uncertainties are estimated with a counts-in-cells moment method to take galaxy clustering into account. Furthermore, we use a stacking analysis to estimate number counts of sources not detected at 70 μm and 160 μm. This method is validated by simulations. The integration of the number counts gives new CIB lower limits. Results: Number counts reach 35 μJy, 3.5 mJy and 40 mJy at 24 μm, 70 μm, and 160 μm, respectively. We reach deeper flux densities of 0.38 mJy at 70, and 3.1 at 160 μm with a stacking analysis. We confirm the number count turnover at 24 μm and 70 μm, and observe it for the first time at 160 μm at about 20 mJy, together with a power-law behavior below 10 mJy. These mid- and far-infrared counts: 1) are homogeneously built by combining fields of different depths and sizes, providing a legacy over about three orders of magnitude in flux density; 2) are the deepest to date at 70 μm and 160 μm; 3) agree with previously published results in the common measured flux density range; 4) globally agree with the Lagache et al. (2004) model, except at 160 μm, where the model slightly overestimates the counts around 20 and 200 mJy. Conclusions: These counts are integrated to estimate new CIB firm lower limits of 2.29-0.09+0.09 nW m-2 sr-1, 5.4-0.4+0.4 nW m-2 sr-1, and 8.9-1.1+1.1 nW m-2 sr-1 at 24 μm, 70 μm, and 160 μm, respectively, and extrapolated to give new estimates of the CIB due to galaxies of 2.86-0.16+0.19 nW m-2 sr-1, 6.6-0.6+0.7 nW m-2 sr-1, and 14.6-2.9+7.1 nW m-2 sr-1, respectively. Products (point spread function, counts, CIB contributions, software) are publicly available for download at http://www.ias.u-psud.fr/irgalaxies/ Counts and CIB contributions are only available in electronic form at the CDS via anonymous ftp to cdsarc.u-strasbg.fr (130.79.128.5) or via http://cdsweb.u-strasbg.fr/cgi-bin/qcat?J/A+A/512/A78

When Can Categorical Variables Be Treated as Continuous? A Comparison of Robust Continuous and Categorical SEM Estimation Methods under Suboptimal Conditions

ERIC Educational Resources Information Center

Rhemtulla, Mijke; Brosseau-Liard, Patricia E.; Savalei, Victoria

2012-01-01

A simulation study compared the performance of robust normal theory maximum likelihood (ML) and robust categorical least squares (cat-LS) methodology for estimating confirmatory factor analysis models with ordinal variables. Data were generated from 2 models with 2-7 categories, 4 sample sizes, 2 latent distributions, and 5 patterns of category…

Methods for assessing long-term mean pathogen count in drinking water and risk management implications.

PubMed

Englehardt, James D; Ashbolt, Nicholas J; Loewenstine, Chad; Gadzinski, Erik R; Ayenu-Prah, Albert Y

2012-06-01

Recently pathogen counts in drinking and source waters were shown theoretically to have the discrete Weibull (DW) or closely related discrete growth distribution (DGD). The result was demonstrated versus nine short-term and three simulated long-term water quality datasets. These distributions are highly skewed such that available datasets seldom represent the rare but important high-count events, making estimation of the long-term mean difficult. In the current work the methods, and data record length, required to assess long-term mean microbial count were evaluated by simulation of representative DW and DGD waterborne pathogen count distributions. Also, microbial count data were analyzed spectrally for correlation and cycles. In general, longer data records were required for more highly skewed distributions, conceptually associated with more highly treated water. In particular, 500-1,000 random samples were required for reliable assessment of the population mean ±10%, though 50-100 samples produced an estimate within one log (45%) below. A simple correlated first order model was shown to produce count series with 1/f signal, and such periodicity over many scales was shown in empirical microbial count data, for consideration in sampling. A tiered management strategy is recommended, including a plan for rapid response to unusual levels of routinely-monitored water quality indicators.

Software For Least-Squares And Robust Estimation

NASA Technical Reports Server (NTRS)

Jeffreys, William H.; Fitzpatrick, Michael J.; Mcarthur, Barbara E.; Mccartney, James

1990-01-01

GAUSSFIT computer program includes full-featured programming language facilitating creation of mathematical models solving least-squares and robust-estimation problems. Programming language designed to make it easy to specify complex reduction models. Written in 100 percent C language.

Rank-preserving regression: a more robust rank regression model against outliers.

PubMed

Chen, Tian; Kowalski, Jeanne; Chen, Rui; Wu, Pan; Zhang, Hui; Feng, Changyong; Tu, Xin M

2016-08-30

Mean-based semi-parametric regression models such as the popular generalized estimating equations are widely used to improve robustness of inference over parametric models. Unfortunately, such models are quite sensitive to outlying observations. The Wilcoxon-score-based rank regression (RR) provides more robust estimates over generalized estimating equations against outliers. However, the RR and its extensions do not sufficiently address missing data arising in longitudinal studies. In this paper, we propose a new approach to address outliers under a different framework based on the functional response models. This functional-response-model-based alternative not only addresses limitations of the RR and its extensions for longitudinal data, but, with its rank-preserving property, even provides more robust estimates than these alternatives. The proposed approach is illustrated with both real and simulated data. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Aeroservoelastic Uncertainty Model Identification from Flight Data

NASA Technical Reports Server (NTRS)

Brenner, Martin J.

2001-01-01

Uncertainty modeling is a critical element in the estimation of robust stability margins for stability boundary prediction and robust flight control system development. There has been a serious deficiency to date in aeroservoelastic data analysis with attention to uncertainty modeling. Uncertainty can be estimated from flight data using both parametric and nonparametric identification techniques. The model validation problem addressed in this paper is to identify aeroservoelastic models with associated uncertainty structures from a limited amount of controlled excitation inputs over an extensive flight envelope. The challenge to this problem is to update analytical models from flight data estimates while also deriving non-conservative uncertainty descriptions consistent with the flight data. Multisine control surface command inputs and control system feedbacks are used as signals in a wavelet-based modal parameter estimation procedure for model updates. Transfer function estimates are incorporated in a robust minimax estimation scheme to get input-output parameters and error bounds consistent with the data and model structure. Uncertainty estimates derived from the data in this manner provide an appropriate and relevant representation for model development and robust stability analysis. This model-plus-uncertainty identification procedure is applied to aeroservoelastic flight data from the NASA Dryden Flight Research Center F-18 Systems Research Aircraft.

Logistic quantile regression provides improved estimates for bounded avian counts: A case study of California Spotted Owl fledgling production

USGS Publications Warehouse

Cade, Brian S.; Noon, Barry R.; Scherer, Rick D.; Keane, John J.

2017-01-01

Counts of avian fledglings, nestlings, or clutch size that are bounded below by zero and above by some small integer form a discrete random variable distribution that is not approximated well by conventional parametric count distributions such as the Poisson or negative binomial. We developed a logistic quantile regression model to provide estimates of the empirical conditional distribution of a bounded discrete random variable. The logistic quantile regression model requires that counts are randomly jittered to a continuous random variable, logit transformed to bound them between specified lower and upper values, then estimated in conventional linear quantile regression, repeating the 3 steps and averaging estimates. Back-transformation to the original discrete scale relies on the fact that quantiles are equivariant to monotonic transformations. We demonstrate this statistical procedure by modeling 20 years of California Spotted Owl fledgling production (0−3 per territory) on the Lassen National Forest, California, USA, as related to climate, demographic, and landscape habitat characteristics at territories. Spotted Owl fledgling counts increased nonlinearly with decreasing precipitation in the early nesting period, in the winter prior to nesting, and in the prior growing season; with increasing minimum temperatures in the early nesting period; with adult compared to subadult parents; when there was no fledgling production in the prior year; and when percentage of the landscape surrounding nesting sites (202 ha) with trees ≥25 m height increased. Changes in production were primarily driven by changes in the proportion of territories with 2 or 3 fledglings. Average variances of the discrete cumulative distributions of the estimated fledgling counts indicated that temporal changes in climate and parent age class explained 18% of the annual variance in owl fledgling production, which was 34% of the total variance. Prior fledgling production explained as much of the variance in the fledgling counts as climate, parent age class, and landscape habitat predictors. Our logistic quantile regression model can be used for any discrete response variables with fixed upper and lower bounds.

A new time-series methodology for estimating relationships between elderly frailty, remaining life expectancy, and ambient air quality.

PubMed

Murray, Christian J; Lipfert, Frederick W

2012-01-01

Many publications estimate short-term air pollution-mortality risks, but few estimate the associated changes in life-expectancies. We present a new methodology for analyzing time series of health effects, in which prior frailty is assumed to precede short-term elderly nontraumatic mortality. The model is based on a subpopulation of frail individuals whose entries and exits (deaths) are functions of daily and lagged environmental conditions: ambient temperature/season, airborne particles, and ozone. This frail susceptible population is unknown; its fluctuations cannot be observed but are estimated using maximum-likelihood methods with the Kalman filter. We used an existing 14-y set of daily data to illustrate the model and then tested the assumption of prior frailty with a new generalized model that estimates the portion of the daily death count allocated to nonfrail individuals. In this demonstration dataset, new entries into the high-risk pool are associated with lower ambient temperatures and higher concentrations of particulate matter and ozone. Accounting for these effects on antecedent frailty reduces this at-risk population, yielding frail life expectancies of 5-7 days. Associations between environmental factors and entries to the at-risk pool are about twice as strong as for mortality. Nonfrail elderly deaths are seen to make only small contributions. This new model predicts a small short-lived frail population-at-risk that is stable over a wide range of environmental conditions. The predicted effects of pollution on new entries and deaths are robust and consistent with conventional morbidity/mortality times-series studies. We recommend model verification using other suitable datasets.

Comparison of capture-recapture and visual count indices of prairie dog densities in black-footed ferret habitat

USGS Publications Warehouse

Fagerstone, Kathleen A.; Biggins, Dean E.

1986-01-01

Black-footed ferrets (Mustela nigripes) are dependent on prairie dogs (Cynomys spp.) for food and on their burrows for shelter and rearing young. A stable prairie dog population may therefore be the most important factor determining the survival of ferrets. A rapid method of determining prairie dog density would be useful for assessing prairie dog density in colonies currently occupied by ferrets and for selecting prairie dog colonies in other areas for ferret translocation. This study showed that visual counts can provide a rapid density estimate. Visual counts of white-tailed prairie dogs (Cynomys leucurus) were significantly correlated (r = 0.95) with mark-recapture population density estimates on two study areas near Meeteetse, Wyoming. Suggestions are given for use of visual counts.

Increasing point-count duration increases standard error

USGS Publications Warehouse

Smith, W.P.; Twedt, D.J.; Hamel, P.B.; Ford, R.P.; Wiedenfeld, D.A.; Cooper, R.J.

1998-01-01

We examined data from point counts of varying duration in bottomland forests of west Tennessee and the Mississippi Alluvial Valley to determine if counting interval influenced sampling efficiency. Estimates of standard error increased as point count duration increased both for cumulative number of individuals and species in both locations. Although point counts appear to yield data with standard errors proportional to means, a square root transformation of the data may stabilize the variance. Using long (>10 min) point counts may reduce sample size and increase sampling error, both of which diminish statistical power and thereby the ability to detect meaningful changes in avian populations.

Sampling characteristics and calibration of snorkel counts to estimate stream fish populations

USGS Publications Warehouse

Weaver, D.; Kwak, Thomas J.; Pollock, Kenneth

2014-01-01

Snorkeling is a versatile technique for estimating lotic fish population characteristics; however, few investigators have evaluated its accuracy at population or assemblage levels. We evaluated the accuracy of snorkeling using prepositioned areal electrofishing (PAE) for estimating fish populations in a medium-sized Appalachian Mountain river during fall 2008 and summer 2009. Strip-transect snorkel counts were calibrated with PAE counts in identical locations among macrohabitats, fish species or taxa, and seasons. Mean snorkeling efficiency (i.e., the proportion of individuals counted from the true population) among all taxa and seasons was 14.7% (SE, 2.5%), and the highest efficiencies were for River Chub Nocomis micropogon at 21.1% (SE, 5.9%), Central Stoneroller Campostoma anomalum at 20.3% (SE, 9.6%), and darters (Percidae) at 17.1% (SE, 3.7%), whereas efficiencies were lower for shiners (Notropis spp., Cyprinella spp., Luxilus spp.) at 8.2% (SE, 2.2%) and suckers (Catostomidae) at 6.6% (SE, 3.2%). Macrohabitat type, fish taxon, or sampling season did not significantly explain variance in snorkeling efficiency. Mean snorkeling detection probability (i.e., probability of detecting at least one individual of a taxon) among fish taxa and seasons was 58.4% (SE, 6.1%). We applied the efficiencies from our calibration study to adjust snorkel counts from an intensive snorkeling survey conducted in a nearby reach. Total fish density estimates from strip-transect counts adjusted for snorkeling efficiency were 7,288 fish/ha (SE, 1,564) during summer and 15,805 fish/ha (SE, 4,947) during fall. Precision of fish density estimates is influenced by variation in snorkeling efficiency and sample size and may be increased with additional sampling effort. These results demonstrate the sampling properties and utility of snorkeling to characterize lotic fish assemblages with acceptable efficiency and detection probability, less effort, and no mortality, compared with traditional sampling methods.

DNA methylation-based measures of biological age: meta-analysis predicting time to death

PubMed Central

Chen, Brian H.; Marioni, Riccardo E.; Colicino, Elena; Peters, Marjolein J.; Ward-Caviness, Cavin K.; Tsai, Pei-Chien; Roetker, Nicholas S.; Just, Allan C.; Demerath, Ellen W.; Guan, Weihua; Bressler, Jan; Fornage, Myriam; Studenski, Stephanie; Vandiver, Amy R.; Moore, Ann Zenobia; Tanaka, Toshiko; Kiel, Douglas P.; Liang, Liming; Vokonas, Pantel; Schwartz, Joel; Lunetta, Kathryn L.; Murabito, Joanne M.; Bandinelli, Stefania; Hernandez, Dena G.; Melzer, David; Nalls, Michael; Pilling, Luke C.; Price, Timothy R.; Singleton, Andrew B.; Gieger, Christian; Holle, Rolf; Kretschmer, Anja; Kronenberg, Florian; Kunze, Sonja; Linseisen, Jakob; Meisinger, Christine; Rathmann, Wolfgang; Waldenberger, Melanie; Visscher, Peter M.; Shah, Sonia; Wray, Naomi R.; McRae, Allan F.; Franco, Oscar H.; Hofman, Albert; Uitterlinden, André G.; Absher, Devin; Assimes, Themistocles; Levine, Morgan E.; Lu, Ake T.; Tsao, Philip S.; Hou, Lifang; Manson, JoAnn E.; Carty, Cara L.; LaCroix, Andrea Z.; Reiner, Alexander P.; Spector, Tim D.; Feinberg, Andrew P.; Levy, Daniel; Baccarelli, Andrea; van Meurs, Joyce; Bell, Jordana T.; Peters, Annette; Deary, Ian J.; Pankow, James S.; Ferrucci, Luigi; Horvath, Steve

2016-01-01

Estimates of biological age based on DNA methylation patterns, often referred to as “epigenetic age”, “DNAm age”, have been shown to be robust biomarkers of age in humans. We previously demonstrated that independent of chronological age, epigenetic age assessed in blood predicted all-cause mortality in four human cohorts. Here, we expanded our original observation to 13 different cohorts for a total sample size of 13,089 individuals, including three racial/ethnic groups. In addition, we examined whether incorporating information on blood cell composition into the epigenetic age metrics improves their predictive power for mortality. All considered measures of epigenetic age acceleration were predictive of mortality (p≤8.2×10−9), independent of chronological age, even after adjusting for additional risk factors (p<5.4×10−4), and within the racial/ethnic groups that we examined (non-Hispanic whites, Hispanics, African Americans). Epigenetic age estimates that incorporated information on blood cell composition led to the smallest p-values for time to death (p=7.5×10−43). Overall, this study a) strengthens the evidence that epigenetic age predicts all-cause mortality above and beyond chronological age and traditional risk factors, and b) demonstrates that epigenetic age estimates that incorporate information on blood cell counts lead to highly significant associations with all-cause mortality. PMID:27690265

ESTIMATION OF RADIOACTIVE CALCIUM-45 BY LIQUID SCINTILLATION COUNTING

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lutwak, L.

1959-03-01

A liquid sclntillation counting method is developed for determining radioactive calcium-45 in biological materials. The calcium-45 is extracted, concentrated, and dissolved in absolute ethyl alcohol to which is added 0.4% diphenyloxazol in toluene. Counting efficiency is about 65 percent with standard deviation of the J-57 engin 7.36 percent. (auth)

Automatic counting and classification of bacterial colonies using hyperspectral imaging

USDA-ARS?s Scientific Manuscript database

Detection and counting of bacterial colonies on agar plates is a routine microbiology practice to get a rough estimate of the number of viable cells in a sample. There have been a variety of different automatic colony counting systems and software algorithms mainly based on color or gray-scale pictu...

Monitoring gray wolf populations using multiple survey methods

USGS Publications Warehouse

Ausband, David E.; Rich, Lindsey N.; Glenn, Elizabeth M.; Mitchell, Michael S.; Zager, Pete; Miller, David A.W.; Waits, Lisette P.; Ackerman, Bruce B.; Mack, Curt M.

2013-01-01

The behavioral patterns and large territories of large carnivores make them challenging to monitor. Occupancy modeling provides a framework for monitoring population dynamics and distribution of territorial carnivores. We combined data from hunter surveys, howling and sign surveys conducted at predicted wolf rendezvous sites, and locations of radiocollared wolves to model occupancy and estimate the number of gray wolf (Canis lupus) packs and individuals in Idaho during 2009 and 2010. We explicitly accounted for potential misidentification of occupied cells (i.e., false positives) using an extension of the multi-state occupancy framework. We found agreement between model predictions and distribution and estimates of number of wolf packs and individual wolves reported by Idaho Department of Fish and Game and Nez Perce Tribe from intensive radiotelemetry-based monitoring. Estimates of individual wolves from occupancy models that excluded data from radiocollared wolves were within an average of 12.0% (SD = 6.0) of existing statewide minimum counts. Models using only hunter survey data generally estimated the lowest abundance, whereas models using all data generally provided the highest estimates of abundance, although only marginally higher. Precision across approaches ranged from 14% to 28% of mean estimates and models that used all data streams generally provided the most precise estimates. We demonstrated that an occupancy model based on different survey methods can yield estimates of the number and distribution of wolf packs and individual wolf abundance with reasonable measures of precision. Assumptions of the approach including that average territory size is known, average pack size is known, and territories do not overlap, must be evaluated periodically using independent field data to ensure occupancy estimates remain reliable. Use of multiple survey methods helps to ensure that occupancy estimates are robust to weaknesses or changes in any 1 survey method. Occupancy modeling may be useful for standardizing estimates across large landscapes, even if survey methods differ across regions, allowing for inferences about broad-scale population dynamics of wolves.

Potential errors in body composition as estimated by whole body scintillation counting

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lykken, G.I.; Lukaski, H.C.; Bolonchuk, W.W.

Vigorous exercise has been reported to increase the apparent potassium content of athletes measured by whole body gamma ray scintillation counting of /sup 40/K. The possibility that this phenomenon is an artifact was evaluated in three cyclists and one nonathlete after exercise on the road (cyclists) or in a room with a source of radon and radon progeny (nonathlete). The apparent /sup 40/K content of the thighs of the athletes and whole body of the nonathlete increased after exercise. Counts were also increased in both windows detecting /sup 214/Bi, a progeny of radon. /sup 40/K and /sup 214/Bi counts weremore » highly correlated (r . 0.87, p less than 0.001). The apparent increase in /sup 40/K was accounted for by an increase in counts associated with the 1.764 MeV gamma ray emissions from /sup 214/Bi. Thus a failure to correct for radon progeny would cause a significant error in the estimate of lean body mass by /sup 40/K counting.« less

Potential errors in body composition as estimated by whole body scintillation counting

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lykken, G.I.; Lukaski, H.C.; Bolonchuk, W.W.

Vigorous exercise has been reported to increase the apparent potassium content of athletes measured by whole body gamma ray scintillation counting of /sup 40/K. The possibility that this phenomenon is an artifact was evaluated in three cyclists and one nonathlete after exercise on the road (cyclists) or in a room with a source of radon and radon progeny (nonathlete). The apparent /sup 40/K content of the thighs of the athletes and whole body of the nonathlete increased after exercise. Counts were also increased in both windows detecting /sup 214/Bi, a progeny of radon. /sup 40/K and /sup 214/Bi counts weremore » highly correlated (r = 0.87, p < 0.001). The apparent increase in /sup 40/K was accounted for by an increase in counts associated with the 1.764 MeV gamma ray emissions from /sup 214/Bi. Thus a failure to correct for radon progeny would cause a significant error in the estimate of lean body mass by /sup 40/K counting.« less

State-space modeling of population sizes and trends in Nihoa Finch and Millerbird

USGS Publications Warehouse

Gorresen, P. Marcos; Brinck, Kevin W.; Camp, Richard J.; Farmer, Chris; Plentovich, Sheldon M.; Banko, Paul C.

2016-01-01

Both of the 2 passerines endemic to Nihoa Island, Hawai‘i, USA—the Nihoa Millerbird (Acrocephalus familiaris kingi) and Nihoa Finch (Telespiza ultima)—are listed as endangered by federal and state agencies. Their abundances have been estimated by irregularly implemented fixed-width strip-transect sampling from 1967 to 2012, from which area-based extrapolation of the raw counts produced highly variable abundance estimates for both species. To evaluate an alternative survey method and improve abundance estimates, we conducted variable-distance point-transect sampling between 2010 and 2014. We compared our results to those obtained from strip-transect samples. In addition, we applied state-space models to derive improved estimates of population size and trends from the legacy time series of strip-transect counts. Both species were fairly evenly distributed across Nihoa and occurred in all or nearly all available habitat. Population trends for Nihoa Millerbird were inconclusive because of high within-year variance. Trends for Nihoa Finch were positive, particularly since the early 1990s. Distance-based analysis of point-transect counts produced mean estimates of abundance similar to those from strip-transects but was generally more precise. However, both survey methods produced biologically unrealistic variability between years. State-space modeling of the long-term time series of abundances obtained from strip-transect counts effectively reduced uncertainty in both within- and between-year estimates of population size, and allowed short-term changes in abundance trajectories to be smoothed into a long-term trend.

Combining Breeding Bird Survey and distance sampling to estimate density of migrant and breeding birds

USGS Publications Warehouse

Somershoe, S.G.; Twedt, D.J.; Reid, B.

2006-01-01

We combined Breeding Bird Survey point count protocol and distance sampling to survey spring migrant and breeding birds in Vicksburg National Military Park on 33 days between March and June of 2003 and 2004. For 26 of 106 detected species, we used program DISTANCE to estimate detection probabilities and densities from 660 3-min point counts in which detections were recorded within four distance annuli. For most species, estimates of detection probability, and thereby density estimates, were improved through incorporation of the proportion of forest cover at point count locations as a covariate. Our results suggest Breeding Bird Surveys would benefit from the use of distance sampling and a quantitative characterization of habitat at point count locations. During spring migration, we estimated that the most common migrant species accounted for a population of 5000-9000 birds in Vicksburg National Military Park (636 ha). Species with average populations of 300 individuals during migration were: Blue-gray Gnatcatcher (Polioptila caerulea), Cedar Waxwing (Bombycilla cedrorum), White-eyed Vireo (Vireo griseus), Indigo Bunting (Passerina cyanea), and Ruby-crowned Kinglet (Regulus calendula). Of 56 species that bred in Vicksburg National Military Park, we estimated that the most common 18 species accounted for 8150 individuals. The six most abundant breeding species, Blue-gray Gnatcatcher, White-eyed Vireo, Summer Tanager (Piranga rubra), Northern Cardinal (Cardinalis cardinalis), Carolina Wren (Thryothorus ludovicianus), and Brown-headed Cowbird (Molothrus ater), accounted for 5800 individuals.

Sperm count as a surrogate endpoint for male fertility control.

PubMed

Benda, Norbert; Gerlinger, Christoph

2007-11-30

When assessing the effectiveness of a hormonal method of fertility control in men, the classical approach used for the assessment of hormonal contraceptives in women, by estimating the pregnancy rate or using a life-table analysis for the time to pregnancy, is difficult to apply in a clinical development program. The main reasons are the dissociation of the treated unit, i.e. the man, and the observed unit, i.e. his female partner, the high variability in the frequency of male intercourse, the logistical cost and ethical concerns related to the monitoring of the trial. A reasonable surrogate endpoint of the definite endpoint time to pregnancy is sperm count. In addition to the avoidance of the mentioned problems, trials that compare different treatments are possible with reasonable sample sizes, and study duration can be shorter. However, current products do not suppress sperm production to 100 per cent in all men and the sperm count is only observed with measurement error. Complete azoospermia might not be necessary in order to achieve an acceptable failure rate compared with other forms of male fertility control. Therefore, the use of sperm count as a surrogate endpoint must rely on the results of a previous trial in which both the definitive- and surrogate-endpoint results were assessed. The paper discusses different estimation functions of the mean pregnancy rate (corresponding to the cumulative hazard) that are based on the results of sperm count trial and a previous trial in which both sperm count and time to pregnancy were assessed, as well as the underlying assumptions. Sample size estimations are given for pregnancy rate estimation with a given precision.

Population trends, survival, and sampling methodologies for a population of Rana draytonii

USGS Publications Warehouse

Fellers, Gary M.; Kleeman, Patrick M.; Miller, David A.W.; Halstead, Brian J.

2017-01-01

Estimating population trends provides valuable information for resource managers, but monitoring programs face trade-offs between the quality and quantity of information gained and the number of sites surveyed. We compared the effectiveness of monitoring techniques for estimating population trends of Rana draytonii (California Red-legged Frog) at Point Reyes National Seashore, California, USA, over a 13-yr period. Our primary goals were to: 1) estimate trends for a focal pond at Point Reyes National Seashore, and 2) evaluate whether egg mass counts could reliably estimate an index of abundance relative to more-intensive capture–mark–recapture methods. Capture–mark–recapture (CMR) surveys of males indicated a stable population from 2005 to 2009, despite low annual apparent survival (26.3%). Egg mass counts from 2000 to 2012 indicated that despite some large fluctuations, the breeding female population was generally stable or increasing, with annual abundance varying between 26 and 130 individuals. Minor modifications to egg mass counts, such as marking egg masses, can allow estimation of egg mass detection probabilities necessary to convert counts to abundance estimates, even when closure of egg mass abundance cannot be assumed within a breeding season. High egg mass detection probabilities (mean per-survey detection probability = 0.98 [0.89–0.99]) indicate that egg mass surveys can be an efficient and reliable method for monitoring population trends of federally threatened R. draytonii. Combining egg mass surveys to estimate trends at many sites with CMR methods to evaluate factors affecting adult survival at focal populations is likely a profitable path forward to enhance understanding and conservation of R. draytonii.

Gait parameter and event estimation using smartphones.

PubMed

Pepa, Lucia; Verdini, Federica; Spalazzi, Luca

2017-09-01

The use of smartphones can greatly help for gait parameters estimation during daily living, but its accuracy needs a deeper evaluation against a gold standard. The objective of the paper is a step-by-step assessment of smartphone performance in heel strike, step count, step period, and step length estimation. The influence of smartphone placement and orientation on estimation performance is evaluated as well. This work relies on a smartphone app developed to acquire, process, and store inertial sensor data and rotation matrices about device position. Smartphone alignment was evaluated by expressing the acceleration vector in three reference frames. Two smartphone placements were tested. Three methods for heel strike detection were considered. On the basis of estimated heel strikes, step count is performed, step period is obtained, and the inverted pendulum model is applied for step length estimation. Pearson correlation coefficient, absolute and relative errors, ANOVA, and Bland-Altman limits of agreement were used to compare smartphone estimation with stereophotogrammetry on eleven healthy subjects. High correlations were found between smartphone and stereophotogrammetric measures: up to 0.93 for step count, to 0.99 for heel strike, 0.96 for step period, and 0.92 for step length. Error ranges are comparable to those in the literature. Smartphone placement did not affect the performance. The major influence of acceleration reference frames and heel strike detection method was found in step count. This study provides detailed information about expected accuracy when smartphone is used as a gait monitoring tool. The obtained results encourage real life applications. Copyright © 2017 Elsevier B.V. All rights reserved.

Are Books Like Number Lines? Children Spontaneously Encode Spatial-Numeric Relationships in a Novel Spatial Estimation Task.

PubMed

Thompson, Clarissa A; Morris, Bradley J; Sidney, Pooja G

2017-01-01

Do children spontaneously represent spatial-numeric features of a task, even when it does not include printed numbers (Mix et al., 2016)? Sixty first grade students completed a novel spatial estimation task by seeking and finding pages in a 100-page book without printed page numbers. Children were shown pages 1 through 6 and 100, and then were asked, "Can you find page X?" Children's precision of estimates on the page finder task and a 0-100 number line estimation task was calculated with the Percent Absolute Error (PAE) formula (Siegler and Booth, 2004), in which lower PAE indicated more precise estimates. Children's numerical knowledge was further assessed with: (1) numeral identification (e.g., What number is this: 57?), (2) magnitude comparison (e.g., Which is larger: 54 or 57?), and (3) counting on (e.g., Start counting from 84 and count up 5 more). Children's accuracy on these tasks was correlated with their number line PAE. Children's number line estimation PAE predicted their page finder PAE, even after controlling for age and accuracy on the other numerical tasks. Children's estimates on the page finder and number line tasks appear to tap a general magnitude representation. However, the page finder task did not correlate with numeral identification and counting-on performance, likely because these tasks do not measure children's magnitude knowledge. Our results suggest that the novel page finder task is a useful measure of children's magnitude knowledge, and that books have similar spatial-numeric affordances as number lines and numeric board games.

Analytical variability of estimated platelet counts on canine blood smears.

PubMed

Paltrinieri, Saverio; Paciletti, Veronica; Zambarbieri, Jari

2018-06-04

The analytical variability of estimated platelet counts in dogs has not been reported. The purpose of this study was to assess the magnitude of analytical imprecision of platelet estimates and the possible impact of this imprecision on clinical decisions. Three independent observers counted the number of platelets in 3 different areas (LE = lateral edge; CM = central monolayer; FE = feathered edge) of 30 canine blood smears with different instrumental platelet counts. The coefficient of variation (CV) for each observer was calculated in different areas of each smear (intra-observer variability), among different regions of each smear (inter-area variability), and among different observers in each area (inter-observer variability). The influence of these variabilities on the classification of platelet estimates as adequate, increased, or decreased was also assessed. The CVs recorded in the different areas by each observer ranged from 8% to 88% and were negatively correlated (P < .001, r = -.65) with the mean number of platelets per field. The mean platelet number was significantly lower in the FE and significantly higher in the CM compared with the LE, but the magnitude of this difference varied with the operators. The concordance among operators regarding platelet estimates was fair (k = 0.36) to substantial (k = 0.71) depending on the area. The overall inter-area concordance was moderate (k = 0.59). Platelet estimates suffer from high variability that could lead to patient misclassification. Therefore, guidelines to standardize the platelet estimate are needed. © 2018 American Society for Veterinary Clinical Pathology.

A Robust Adaptive Unscented Kalman Filter for Nonlinear Estimation with Uncertain Noise Covariance.

PubMed

Zheng, Binqi; Fu, Pengcheng; Li, Baoqing; Yuan, Xiaobing

2018-03-07

The Unscented Kalman filter (UKF) may suffer from performance degradation and even divergence while mismatch between the noise distribution assumed as a priori by users and the actual ones in a real nonlinear system. To resolve this problem, this paper proposes a robust adaptive UKF (RAUKF) to improve the accuracy and robustness of state estimation with uncertain noise covariance. More specifically, at each timestep, a standard UKF will be implemented first to obtain the state estimations using the new acquired measurement data. Then an online fault-detection mechanism is adopted to judge if it is necessary to update current noise covariance. If necessary, innovation-based method and residual-based method are used to calculate the estimations of current noise covariance of process and measurement, respectively. By utilizing a weighting factor, the filter will combine the last noise covariance matrices with the estimations as the new noise covariance matrices. Finally, the state estimations will be corrected according to the new noise covariance matrices and previous state estimations. Compared with the standard UKF and other adaptive UKF algorithms, RAUKF converges faster to the actual noise covariance and thus achieves a better performance in terms of robustness, accuracy, and computation for nonlinear estimation with uncertain noise covariance, which is demonstrated by the simulation results.

A Robust Adaptive Unscented Kalman Filter for Nonlinear Estimation with Uncertain Noise Covariance

PubMed Central

Zheng, Binqi; Yuan, Xiaobing

2018-01-01

The Unscented Kalman filter (UKF) may suffer from performance degradation and even divergence while mismatch between the noise distribution assumed as a priori by users and the actual ones in a real nonlinear system. To resolve this problem, this paper proposes a robust adaptive UKF (RAUKF) to improve the accuracy and robustness of state estimation with uncertain noise covariance. More specifically, at each timestep, a standard UKF will be implemented first to obtain the state estimations using the new acquired measurement data. Then an online fault-detection mechanism is adopted to judge if it is necessary to update current noise covariance. If necessary, innovation-based method and residual-based method are used to calculate the estimations of current noise covariance of process and measurement, respectively. By utilizing a weighting factor, the filter will combine the last noise covariance matrices with the estimations as the new noise covariance matrices. Finally, the state estimations will be corrected according to the new noise covariance matrices and previous state estimations. Compared with the standard UKF and other adaptive UKF algorithms, RAUKF converges faster to the actual noise covariance and thus achieves a better performance in terms of robustness, accuracy, and computation for nonlinear estimation with uncertain noise covariance, which is demonstrated by the simulation results. PMID:29518960

Efficiently estimating salmon escapement uncertainty using systematically sampled data

USGS Publications Warehouse

Reynolds, Joel H.; Woody, Carol Ann; Gove, Nancy E.; Fair, Lowell F.

2007-01-01

Fish escapement is generally monitored using nonreplicated systematic sampling designs (e.g., via visual counts from towers or hydroacoustic counts). These sampling designs support a variety of methods for estimating the variance of the total escapement. Unfortunately, all the methods give biased results, with the magnitude of the bias being determined by the underlying process patterns. Fish escapement commonly exhibits positive autocorrelation and nonlinear patterns, such as diurnal and seasonal patterns. For these patterns, poor choice of variance estimator can needlessly increase the uncertainty managers have to deal with in sustaining fish populations. We illustrate the effect of sampling design and variance estimator choice on variance estimates of total escapement for anadromous salmonids from systematic samples of fish passage. Using simulated tower counts of sockeye salmon Oncorhynchus nerka escapement on the Kvichak River, Alaska, five variance estimators for nonreplicated systematic samples were compared to determine the least biased. Using the least biased variance estimator, four confidence interval estimators were compared for expected coverage and mean interval width. Finally, five systematic sampling designs were compared to determine the design giving the smallest average variance estimate for total annual escapement. For nonreplicated systematic samples of fish escapement, all variance estimators were positively biased. Compared to the other estimators, the least biased estimator reduced bias by, on average, from 12% to 98%. All confidence intervals gave effectively identical results. Replicated systematic sampling designs consistently provided the smallest average estimated variance among those compared.

Utility and validation of day and night snorkel counts for estimating bull trout abundance in first-to-third order streams

Treesearch

Russell F. Thurow; James T. Peterson; John W. Guzevich

2006-01-01

Despite the widespread use of underwater observation to census stream-dwelling fishes, the accuracy of snorkeling methods has rarely been validated. We evaluated the efficiency of day and night snorkel counts for estimating the abundance of bull trout Salvelinus confluentus in 215 sites within first- to third-order streams. We used a dual-gear...

Power counting to better jet observables

NASA Astrophysics Data System (ADS)

Larkoski, Andrew J.; Moult, Ian; Neill, Duff

2014-12-01

Optimized jet substructure observables for identifying boosted topologies will play an essential role in maximizing the physics reach of the Large Hadron Collider. Ideally, the design of discriminating variables would be informed by analytic calculations in perturbative QCD. Unfortunately, explicit calculations are often not feasible due to the complexity of the observables used for discrimination, and so many validation studies rely heavily, and solely, on Monte Carlo. In this paper we show how methods based on the parametric power counting of the dynamics of QCD, familiar from effective theory analyses, can be used to design, understand, and make robust predictions for the behavior of jet substructure variables. As a concrete example, we apply power counting for discriminating boosted Z bosons from massive QCD jets using observables formed from the n-point energy correlation functions. We show that power counting alone gives a definite prediction for the observable that optimally separates the background-rich from the signal-rich regions of phase space. Power counting can also be used to understand effects of phase space cuts and the effect of contamination from pile-up, which we discuss. As these arguments rely only on the parametric scaling of QCD, the predictions from power counting must be reproduced by any Monte Carlo, which we verify using Pythia 8 and Herwig++. We also use the example of quark versus gluon discrimination to demonstrate the limits of the power counting technique.

Electrochemical magneto-actuated biosensor for CD4 count in AIDS diagnosis and monitoring.

PubMed

Carinelli, S; Xufré Ballesteros, C; Martí, M; Alegret, S; Pividori, M I

2015-12-15

The counting of CD4(+) T lymphocytes is a clinical parameter used for AIDS diagnosis and follow-up. As this disease is particularly prevalent in developing countries, simple and affordable CD4 cell counting methods are urgently needed in resource-limited settings. This paper describes an electrochemical magneto-actuated biosensor for CD4 count in whole blood. The CD4(+) T lymphocytes were isolated, preconcentrated and labeled from 100 μL of whole blood by immunomagnetic separation with magnetic particles modified with antiCD3 antibodies. The captured cells were labeled with a biotinylated antiCD4 antibody, followed by the reaction with the electrochemical reporter streptavidin-peroxidase conjugate. The limit of detection for the CD4 counting magneto-actuated biosensor in whole blood was as low as 44 cells μL(-1) while the logistic range was found to be from 89 to 912 cells μL(-1), which spans the whole medical interest range for CD4 counts in AIDS patients. The electrochemical detection together with the immunomagnetic separation confers high sensitivity, resulting in a rapid, inexpensive, robust, user-friendly method for CD4 counting. This approach is a promising alternative for the costly standard flow cytometry and suitable as diagnostic tool at decentralized practitioner sites in low resource settings, especially in less developed countries. Copyright © 2015 Elsevier B.V. All rights reserved.

Resampling-based Methods in Single and Multiple Testing for Equality of Covariance/Correlation Matrices

PubMed Central

Yang, Yang; DeGruttola, Victor

2016-01-01

Traditional resampling-based tests for homogeneity in covariance matrices across multiple groups resample residuals, that is, data centered by group means. These residuals do not share the same second moments when the null hypothesis is false, which makes them difficult to use in the setting of multiple testing. An alternative approach is to resample standardized residuals, data centered by group sample means and standardized by group sample covariance matrices. This approach, however, has been observed to inflate type I error when sample size is small or data are generated from heavy-tailed distributions. We propose to improve this approach by using robust estimation for the first and second moments. We discuss two statistics: the Bartlett statistic and a statistic based on eigen-decomposition of sample covariance matrices. Both statistics can be expressed in terms of standardized errors under the null hypothesis. These methods are extended to test homogeneity in correlation matrices. Using simulation studies, we demonstrate that the robust resampling approach provides comparable or superior performance, relative to traditional approaches, for single testing and reasonable performance for multiple testing. The proposed methods are applied to data collected in an HIV vaccine trial to investigate possible determinants, including vaccine status, vaccine-induced immune response level and viral genotype, of unusual correlation pattern between HIV viral load and CD4 count in newly infected patients. PMID:22740584

Resampling-based methods in single and multiple testing for equality of covariance/correlation matrices.

PubMed

Yang, Yang; DeGruttola, Victor

2012-06-22

Traditional resampling-based tests for homogeneity in covariance matrices across multiple groups resample residuals, that is, data centered by group means. These residuals do not share the same second moments when the null hypothesis is false, which makes them difficult to use in the setting of multiple testing. An alternative approach is to resample standardized residuals, data centered by group sample means and standardized by group sample covariance matrices. This approach, however, has been observed to inflate type I error when sample size is small or data are generated from heavy-tailed distributions. We propose to improve this approach by using robust estimation for the first and second moments. We discuss two statistics: the Bartlett statistic and a statistic based on eigen-decomposition of sample covariance matrices. Both statistics can be expressed in terms of standardized errors under the null hypothesis. These methods are extended to test homogeneity in correlation matrices. Using simulation studies, we demonstrate that the robust resampling approach provides comparable or superior performance, relative to traditional approaches, for single testing and reasonable performance for multiple testing. The proposed methods are applied to data collected in an HIV vaccine trial to investigate possible determinants, including vaccine status, vaccine-induced immune response level and viral genotype, of unusual correlation pattern between HIV viral load and CD4 count in newly infected patients.

Aerial population estimates of wild horses (Equus caballus) in the adobe town and salt wells creek herd management areas using an integrated simultaneous double-count and sightability bias correction technique

USGS Publications Warehouse

Lubow, Bruce C.; Ransom, Jason I.

2007-01-01

An aerial survey technique combining simultaneous double-count and sightability bias correction methodologies was used to estimate the population of wild horses inhabiting Adobe Town and Salt Wells Creek Herd Management Areas, Wyoming. Based on 5 surveys over 4 years, we conclude that the technique produced estimates consistent with the known number of horses removed between surveys and an annual population growth rate of 16.2 percent per year. Therefore, evidence from this series of surveys supports the validity of this survey method. Our results also indicate that the ability of aerial observers to see horse groups is very strongly dependent on skill of the individual observer, size of the horse group, and vegetation cover. It is also more modestly dependent on the ruggedness of the terrain and the position of the sun relative to the observer. We further conclude that censuses, or uncorrected raw counts, are inadequate estimates of population size for this herd. Such uncorrected counts were all undercounts in our trials, and varied in magnitude from year to year and observer to observer. As of April 2007, we estimate that the population of the Adobe Town /Salt Wells Creek complex is 906 horses with a 95 percent confidence interval ranging from 857 to 981 horses.

Data-Driven Robust RVFLNs Modeling of a Blast Furnace Iron-Making Process Using Cauchy Distribution Weighted M-Estimation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Ping; Lv, Youbin; Wang, Hong

Optimal operation of a practical blast furnace (BF) ironmaking process depends largely on a good measurement of molten iron quality (MIQ) indices. However, measuring the MIQ online is not feasible using the available techniques. In this paper, a novel data-driven robust modeling is proposed for online estimation of MIQ using improved random vector functional-link networks (RVFLNs). Since the output weights of traditional RVFLNs are obtained by the least squares approach, a robustness problem may occur when the training dataset is contaminated with outliers. This affects the modeling accuracy of RVFLNs. To solve this problem, a Cauchy distribution weighted M-estimation basedmore » robust RFVLNs is proposed. Since the weights of different outlier data are properly determined by the Cauchy distribution, their corresponding contribution on modeling can be properly distinguished. Thus robust and better modeling results can be achieved. Moreover, given that the BF is a complex nonlinear system with numerous coupling variables, the data-driven canonical correlation analysis is employed to identify the most influential components from multitudinous factors that affect the MIQ indices to reduce the model dimension. Finally, experiments using industrial data and comparative studies have demonstrated that the obtained model produces a better modeling and estimating accuracy and stronger robustness than other modeling methods.« less

Accounting for imperfect detection is critical for inferring marine turtle nesting population trends.

PubMed

Pfaller, Joseph B; Bjorndal, Karen A; Chaloupka, Milani; Williams, Kristina L; Frick, Michael G; Bolten, Alan B

2013-01-01

Assessments of population trends based on time-series counts of individuals are complicated by imperfect detection, which can lead to serious misinterpretations of data. Population trends of threatened marine turtles worldwide are usually based on counts of nests or nesting females. We analyze 39 years of nest-count, female-count, and capture-mark-recapture (CMR) data for nesting loggerhead turtles (Caretta caretta) on Wassaw Island, Georgia, USA. Annual counts of nests and females, not corrected for imperfect detection, yield significant, positive trends in abundance. However, multistate open robust design modeling of CMR data that accounts for changes in imperfect detection reveals that the annual abundance of nesting females has remained essentially constant over the 39-year period. The dichotomy could result from improvements in surveys or increased within-season nest-site fidelity in females, either of which would increase detection probability. For the first time in a marine turtle population, we compare results of population trend analyses that do and do not account for imperfect detection and demonstrate the potential for erroneous conclusions. Past assessments of marine turtle population trends based exclusively on count data should be interpreted with caution and re-evaluated when possible. These concerns apply equally to population assessments of all species with imperfect detection.

Performance Equivalence and Validation of the Soleris Automated System for Quantitative Microbial Content Testing Using Pure Suspension Cultures.

PubMed

Limberg, Brian J; Johnstone, Kevin; Filloon, Thomas; Catrenich, Carl

2016-09-01

Using United States Pharmacopeia-National Formulary (USP-NF) general method <1223> guidance, the Soleris(®) automated system and reagents (Nonfermenting Total Viable Count for bacteria and Direct Yeast and Mold for yeast and mold) were validated, using a performance equivalence approach, as an alternative to plate counting for total microbial content analysis using five representative microbes: Staphylococcus aureus, Bacillus subtilis, Pseudomonas aeruginosa, Candida albicans, and Aspergillus brasiliensis. Detection times (DTs) in the alternative automated system were linearly correlated to CFU/sample (R(2) = 0.94-0.97) with ≥70% accuracy per USP General Chapter <1223> guidance. The LOD and LOQ of the automated system were statistically similar to the traditional plate count method. This system was significantly more precise than plate counting (RSD 1.2-2.9% for DT, 7.8-40.6% for plate counts), was statistically comparable to plate counting with respect to variations in analyst, vial lots, and instruments, and was robust when variations in the operating detection thresholds (dTs; ±2 units) were used. The automated system produced accurate results, was more precise and less labor-intensive, and met or exceeded criteria for a valid alternative quantitative method, consistent with USP-NF general method <1223> guidance.

Using Image Attributes to Assure Accurate Particle Size and Count Using Nanoparticle Tracking Analysis.

PubMed

Defante, Adrian P; Vreeland, Wyatt N; Benkstein, Kurt D; Ripple, Dean C

2018-05-01

Nanoparticle tracking analysis (NTA) obtains particle size by analysis of particle diffusion through a time series of micrographs and particle count by a count of imaged particles. The number of observed particles imaged is controlled by the scattering cross-section of the particles and by camera settings such as sensitivity and shutter speed. Appropriate camera settings are defined as those that image, track, and analyze a sufficient number of particles for statistical repeatability. Here, we test if image attributes, features captured within the image itself, can provide measurable guidelines to assess the accuracy for particle size and count measurements using NTA. The results show that particle sizing is a robust process independent of image attributes for model systems. However, particle count is sensitive to camera settings. Using open-source software analysis, it was found that a median pixel area, 4 pixels 2 , results in a particle concentration within 20% of the expected value. The distribution of these illuminated pixel areas can also provide clues about the polydispersity of particle solutions prior to using a particle tracking analysis. Using the median pixel area serves as an operator-independent means to assess the quality of the NTA measurement for count. Published by Elsevier Inc.

The Herschel Virgo Cluster Survey. XVII. SPIRE point-source catalogs and number counts

NASA Astrophysics Data System (ADS)

Pappalardo, Ciro; Bendo, George J.; Bianchi, Simone; Hunt, Leslie; Zibetti, Stefano; Corbelli, Edvige; di Serego Alighieri, Sperello; Grossi, Marco; Davies, Jonathan; Baes, Maarten; De Looze, Ilse; Fritz, Jacopo; Pohlen, Michael; Smith, Matthew W. L.; Verstappen, Joris; Boquien, Médéric; Boselli, Alessandro; Cortese, Luca; Hughes, Thomas; Viaene, Sebastien; Bizzocchi, Luca; Clemens, Marcel

2015-01-01

Aims: We present three independent catalogs of point-sources extracted from SPIRE images at 250, 350, and 500 μm, acquired with the Herschel Space Observatory as a part of the Herschel Virgo Cluster Survey (HeViCS). The catalogs have been cross-correlated to consistently extract the photometry at SPIRE wavelengths for each object. Methods: Sources have been detected using an iterative loop. The source positions are determined by estimating the likelihood to be a real source for each peak on the maps, according to the criterion defined in the sourceExtractorSussextractor task. The flux densities are estimated using the sourceExtractorTimeline, a timeline-based point source fitter that also determines the fitting procedure with the width of the Gaussian that best reproduces the source considered. Afterwards, each source is subtracted from the maps, removing a Gaussian function in every position with the full width half maximum equal to that estimated in sourceExtractorTimeline. This procedure improves the robustness of our algorithm in terms of source identification. We calculate the completeness and the flux accuracy by injecting artificial sources in the timeline and estimate the reliability of the catalog using a permutation method. Results: The HeViCS catalogs contain about 52 000, 42 200, and 18 700 sources selected at 250, 350, and 500 μm above 3σ and are ~75%, 62%, and 50% complete at flux densities of 20 mJy at 250, 350, 500 μm, respectively. We then measured source number counts at 250, 350, and 500 μm and compare them with previous data and semi-analytical models. We also cross-correlated the catalogs with the Sloan Digital Sky Survey to investigate the redshift distribution of the nearby sources. From this cross-correlation, we select ~2000 sources with reliable fluxes and a high signal-to-noise ratio, finding an average redshift z ~ 0.3 ± 0.22 and 0.25 (16-84 percentile). Conclusions: The number counts at 250, 350, and 500 μm show an increase in the slope below 200 mJy, indicating a strong evolution in number of density for galaxies at these fluxes. In general, models tend to overpredict the counts at brighter flux densities, underlying the importance of studying the Rayleigh-Jeans part of the spectral energy distribution to refine the theoretical recipes of the models. Our iterative method for source identification allowed the detection of a family of 500 μm sources that are not foreground objects belonging to Virgo and not found in other catalogs. Herschel is an ESA space observatory with science instruments provided by a European-led principal investigator consortia and with an important participation from NASA.The 250, 350, 500 μm, and the total catalogs are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (ftp://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/573/A129

Efficient robust doubly adaptive regularized regression with applications.

PubMed

Karunamuni, Rohana J; Kong, Linglong; Tu, Wei

2018-01-01

We consider the problem of estimation and variable selection for general linear regression models. Regularized regression procedures have been widely used for variable selection, but most existing methods perform poorly in the presence of outliers. We construct a new penalized procedure that simultaneously attains full efficiency and maximum robustness. Furthermore, the proposed procedure satisfies the oracle properties. The new procedure is designed to achieve sparse and robust solutions by imposing adaptive weights on both the decision loss and the penalty function. The proposed method of estimation and variable selection attains full efficiency when the model is correct and, at the same time, achieves maximum robustness when outliers are present. We examine the robustness properties using the finite-sample breakdown point and an influence function. We show that the proposed estimator attains the maximum breakdown point. Furthermore, there is no loss in efficiency when there are no outliers or the error distribution is normal. For practical implementation of the proposed method, we present a computational algorithm. We examine the finite-sample and robustness properties using Monte Carlo studies. Two datasets are also analyzed.

An improved method for bivariate meta-analysis when within-study correlations are unknown.

PubMed

Hong, Chuan; D Riley, Richard; Chen, Yong

2018-03-01

Multivariate meta-analysis, which jointly analyzes multiple and possibly correlated outcomes in a single analysis, is becoming increasingly popular in recent years. An attractive feature of the multivariate meta-analysis is its ability to account for the dependence between multiple estimates from the same study. However, standard inference procedures for multivariate meta-analysis require the knowledge of within-study correlations, which are usually unavailable. This limits standard inference approaches in practice. Riley et al proposed a working model and an overall synthesis correlation parameter to account for the marginal correlation between outcomes, where the only data needed are those required for a separate univariate random-effects meta-analysis. As within-study correlations are not required, the Riley method is applicable to a wide variety of evidence synthesis situations. However, the standard variance estimator of the Riley method is not entirely correct under many important settings. As a consequence, the coverage of a function of pooled estimates may not reach the nominal level even when the number of studies in the multivariate meta-analysis is large. In this paper, we improve the Riley method by proposing a robust variance estimator, which is asymptotically correct even when the model is misspecified (ie, when the likelihood function is incorrect). Simulation studies of a bivariate meta-analysis, in a variety of settings, show a function of pooled estimates has improved performance when using the proposed robust variance estimator. In terms of individual pooled estimates themselves, the standard variance estimator and robust variance estimator give similar results to the original method, with appropriate coverage. The proposed robust variance estimator performs well when the number of studies is relatively large. Therefore, we recommend the use of the robust method for meta-analyses with a relatively large number of studies (eg, m≥50). When the sample size is relatively small, we recommend the use of the robust method under the working independence assumption. We illustrate the proposed method through 2 meta-analyses. Copyright © 2017 John Wiley & Sons, Ltd.

Toward Robust Estimation of the Components of Forest Population Change

Treesearch

Francis A. Roesch

2014-01-01

Multiple levels of simulation are used to test the robustness of estimators of the components of change. I first created a variety of spatial-temporal populations based on, but more variable than, an actual forest monitoring data set and then sampled those populations under a variety of sampling error structures. The performance of each of four estimation approaches is...

The Graphical Display of Simulation Results, with Applications to the Comparison of Robust IRT Estimators of Ability.

ERIC Educational Resources Information Center

Thissen, David; Wainer, Howard

Simulation studies of the performance of (potentially) robust statistical estimation produce large quantities of numbers in the form of performance indices of the various estimators under various conditions. This report presents a multivariate graphical display used to aid in the digestion of the plentiful results in a current study of Item…

Unbiased estimation of the eyeball volume using the Cavalieri principle on computed tomography images.

PubMed

Acer, Niyazi; Sahin, Bunyamin; Ucar, Tolga; Usanmaz, Mustafa

2009-01-01

The size of the eyeball has been the subject of a few studies. None of them used stereological methods to estimate the volume. In the current study, we estimated the volume of eyeball in normal men and women using the stereological methods. Eyeball volume (EV) was estimated using the Cavalieri principle as a combination of point-counting and planimetry techniques. We used computed tomography scans taken from 36 participants (15 men and 21 women) to estimate the EV. The mean (SD) EV values obtained by planimetry method were 7.49 (0.79) and 7.06 (0.85) cm in men and women, respectively. By using point-counting method, the mean (SD) values were 7.48 (0.85) and 7.21 (0.84) cm in men and women, respectively. There was no statistically significant difference between the findings from the 2 methods (P > 0.05). A weak correlation was found between the axial length of eyeball and the EV estimated by point counting and planimetry (P < 0.05, r = 0.494 and r = 0.523, respectively). The findings of the current study using the stereological methods could provide data for the evaluation of normal and pathologic volumes of the eyeball.

OpenCFU, a new free and open-source software to count cell colonies and other circular objects.

PubMed

Geissmann, Quentin

2013-01-01

Counting circular objects such as cell colonies is an important source of information for biologists. Although this task is often time-consuming and subjective, it is still predominantly performed manually. The aim of the present work is to provide a new tool to enumerate circular objects from digital pictures and video streams. Here, I demonstrate that the created program, OpenCFU, is very robust, accurate and fast. In addition, it provides control over the processing parameters and is implemented in an intuitive and modern interface. OpenCFU is a cross-platform and open-source software freely available at http://opencfu.sourceforge.net.

A Robust State Estimation Framework Considering Measurement Correlations and Imperfect Synchronization

DOE PAGES

Zhao, Junbo; Wang, Shaobu; Mili, Lamine; ...

2018-01-08

Here, this paper develops a robust power system state estimation framework with the consideration of measurement correlations and imperfect synchronization. In the framework, correlations of SCADA and Phasor Measurements (PMUs) are calculated separately through unscented transformation and a Vector Auto-Regression (VAR) model. In particular, PMU measurements during the waiting period of two SCADA measurement scans are buffered to develop the VAR model with robustly estimated parameters using projection statistics approach. The latter takes into account the temporal and spatial correlations of PMU measurements and provides redundant measurements to suppress bad data and mitigate imperfect synchronization. In case where the SCADAmore » and PMU measurements are not time synchronized, either the forecasted PMU measurements or the prior SCADA measurements from the last estimation run are leveraged to restore system observability. Then, a robust generalized maximum-likelihood (GM)-estimator is extended to integrate measurement error correlations and to handle the outliers in the SCADA and PMU measurements. Simulation results that stem from a comprehensive comparison with other alternatives under various conditions demonstrate the benefits of the proposed framework.« less

A Robust State Estimation Framework Considering Measurement Correlations and Imperfect Synchronization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhao, Junbo; Wang, Shaobu; Mili, Lamine

Here, this paper develops a robust power system state estimation framework with the consideration of measurement correlations and imperfect synchronization. In the framework, correlations of SCADA and Phasor Measurements (PMUs) are calculated separately through unscented transformation and a Vector Auto-Regression (VAR) model. In particular, PMU measurements during the waiting period of two SCADA measurement scans are buffered to develop the VAR model with robustly estimated parameters using projection statistics approach. The latter takes into account the temporal and spatial correlations of PMU measurements and provides redundant measurements to suppress bad data and mitigate imperfect synchronization. In case where the SCADAmore » and PMU measurements are not time synchronized, either the forecasted PMU measurements or the prior SCADA measurements from the last estimation run are leveraged to restore system observability. Then, a robust generalized maximum-likelihood (GM)-estimator is extended to integrate measurement error correlations and to handle the outliers in the SCADA and PMU measurements. Simulation results that stem from a comprehensive comparison with other alternatives under various conditions demonstrate the benefits of the proposed framework.« less

An analysis of I/O efficient order-statistic-based techniques for noise power estimation in the HRMS sky survey's operational system

NASA Technical Reports Server (NTRS)

Zimmerman, G. A.; Olsen, E. T.

1992-01-01

Noise power estimation in the High-Resolution Microwave Survey (HRMS) sky survey element is considered as an example of a constant false alarm rate (CFAR) signal detection problem. Order-statistic-based noise power estimators for CFAR detection are considered in terms of required estimator accuracy and estimator dynamic range. By limiting the dynamic range of the value to be estimated, the performance of an order-statistic estimator can be achieved by simpler techniques requiring only a single pass of the data. Simple threshold-and-count techniques are examined, and it is shown how several parallel threshold-and-count estimation devices can be used to expand the dynamic range to meet HRMS system requirements with minimal hardware complexity. An input/output (I/O) efficient limited-precision order-statistic estimator with wide but limited dynamic range is also examined.

Where can pixel counting area estimates meet user-defined accuracy requirements?

NASA Astrophysics Data System (ADS)

Waldner, François; Defourny, Pierre

2017-08-01

Pixel counting is probably the most popular way to estimate class areas from satellite-derived maps. It involves determining the number of pixels allocated to a specific thematic class and multiplying it by the pixel area. In the presence of asymmetric classification errors, the pixel counting estimator is biased. The overarching objective of this article is to define the applicability conditions of pixel counting so that the estimates are below a user-defined accuracy target. By reasoning in terms of landscape fragmentation and spatial resolution, the proposed framework decouples the resolution bias and the classifier bias from the overall classification bias. The consequence is that prior to any classification, part of the tolerated bias is already committed due to the choice of the spatial resolution of the imagery. How much classification bias is affordable depends on the joint interaction of spatial resolution and fragmentation. The method was implemented over South Africa for cropland mapping, demonstrating its operational applicability. Particular attention was paid to modeling a realistic sensor's spatial response by explicitly accounting for the effect of its point spread function. The diagnostic capabilities offered by this framework have multiple potential domains of application such as guiding users in their choice of imagery and providing guidelines for space agencies to elaborate the design specifications of future instruments.

Static and elevated pollen traps do not provide an accurate assessment of personal pollen exposure.

PubMed

Penel, V; Calleja, M; Pichot, C; Charpin, D

2017-03-01

Background. Volumetric pollen traps are commonly used to assess pollen exposure. These traps are well suited for estimating the regional mean airborne pollen concentration but are likely not to provide an accurate index of personal exposure. In this study, we tested the hypothesis that hair sampling may provide different pollen counts from those from pollen traps, especially when the pollen exposure is diverse. Methods. We compared pollen counts in hair washes to counts provided by stationary volumetric and gravimetric pollen traps in 2 different settings: urban with volunteers living in short distance from one another and from the static trap and suburban in which volunteers live in a scattered environment, quite far from the static trap. Results. Pollen counts in hair washes are in full agreement with trap counts for uniform pollen exposure. In contrast, for diverse pollen exposure, .individual pollen counts in hair washes vary strongly in quantity and taxa composition between individuals and dates. These results demonstrate that the pollen counts method (hair washes vs. stationary pollen traps) may lead to different absolute and relative contributions of taxa to the total pollen count. Conclusions. In a geographic area with a high diversity of environmental exposure to pollen, static pollen traps, in contrast to hair washes, do not provide a reliable estimate of this higher diversity.

Methods of detecting and counting raptors: A review

USGS Publications Warehouse

Fuller, M.R.; Mosher, J.A.; Ralph, C. John; Scott, J. Michael

1981-01-01

Most raptors are wide-ranging, secretive, and occur at relatively low densities. These factors, in conjunction with the nocturnal activity of owls, cause the counting of raptors by most standard census and survey efforts to be very time consuming and expensive. This paper reviews the most common methods of detecting and counting raptors. It is hoped that it will be of use to the ever-increasing number of biologists, land-use planners, and managers that must determine the occurrence, density, or population dynamics of raptors. Road counts of fixed station or continuous transect design are often used to sample large areas. Detection of spontaneous or elicited vocalizations, especially those of owls, provides a means of detecting and estimating raptor numbers. Searches for nests are accomplished from foot surveys, observations from automobiles and boats, or from aircraft when nest structures are conspicuous (e.g., Osprey). Knowledge of nest habitat, historic records, and inquiries of local residents are useful for locating nests. Often several of these techniques are combined to help find nest sites. Aerial searches have also been used to locate or count large raptors (e.g., eagles), or those that may be conspicuous in open habitats (e.g., tundra). Counts of birds entering or leaving nest colonies or colonial roosts have been attempted on a limited basis. Results from Christmas Bird Counts have provided an index of the abundance of some species. Trapping and banding generally has proven to be an inefficient method of detecting raptors or estimating their populations. Concentrations of migrants at strategically located points around the world afford the best opportunity to count many rap tors in a relatively short period of time, but the influence of many unquantified variables has inhibited extensive interpretation of these counts. Few data exist to demonstrate the effectiveness of these methods. We believe more research on sampling techniques, rather than complete counts or intensive searches, will provide adequate yet affordable estimates of raptor numbers in addition to providing methods for detecting the presence of raptors on areas of interest to researchers and managers.

Density estimation in aerial images of large crowds for automatic people counting

NASA Astrophysics Data System (ADS)

Herrmann, Christian; Metzler, Juergen

2013-05-01

Counting people is a common topic in the area of visual surveillance and crowd analysis. While many image-based solutions are designed to count only a few persons at the same time, like pedestrians entering a shop or watching an advertisement, there is hardly any solution for counting large crowds of several hundred persons or more. We addressed this problem previously by designing a semi-automatic system being able to count crowds consisting of hundreds or thousands of people based on aerial images of demonstrations or similar events. This system requires major user interaction to segment the image. Our principle aim is to reduce this manual interaction. To achieve this, we propose a new and automatic system. Besides counting the people in large crowds, the system yields the positions of people allowing a plausibility check by a human operator. In order to automatize the people counting system, we use crowd density estimation. The determination of crowd density is based on several features like edge intensity or spatial frequency. They indicate the density and discriminate between a crowd and other image regions like buildings, bushes or trees. We compare the performance of our automatic system to the previous semi-automatic system and to manual counting in images. By counting a test set of aerial images showing large crowds containing up to 12,000 people, the performance gain of our new system will be measured. By improving our previous system, we will increase the benefit of an image-based solution for counting people in large crowds.

Evaluation of surveillance methods for monitoring house fly abundance and activity on large commercial dairy operations.

PubMed

Gerry, Alec C; Higginbotham, G E; Periera, L N; Lam, A; Shelton, C R

2011-06-01

Relative house fly, Musca domestica L., activity at three large dairies in central California was monitored during the peak fly activity period from June to August 2005 by using spot cards, fly tapes, bait traps, and Alsynite traps. Counts for all monitoring methods were significantly related at two of three dairies; with spot card counts significantly related to fly tape counts recorded the same week, and both spot card counts and fly tape counts significantly related to bait trap counts 1-2 wk later. Mean fly counts differed significantly between dairies, but a significant interaction between dairies sampled and monitoring methods used demonstrates that between-dairy comparisons are unwise. Estimate precision was determined by the coefficient of variability (CV) (or SE/mean). Using a CV = 0.15 as a desired level of estimate precision and assuming an integrate pest management (IPM) action threshold near the peak house fly activity measured by each monitoring method, house fly monitoring at a large dairy would require 12 spot cards placed in midafternoon shaded fly resting sites near cattle or seven bait traps placed in open areas near cattle. Software (FlySpotter; http://ucanr.org/ sites/FlySpotter/download/) using computer vision technology was developed to count fly spots on a scanned image of a spot card to dramatically reduce time invested in monitoring house flies. Counts provided by the FlySpotter software were highly correlated to visual counts. The use of spot cards for monitoring house flies is recommended for dairy IPM programs.

Population estimates and monitoring guidelines for endangered Laysan Teal, Anas Laysanensis, at Midway Atoll: Pilot study results 2008-2010.

USGS Publications Warehouse

Reynolds, Michelle H.; Brinck, Kevin W.; Laniawe, Leona

2011-01-01

To improve the Laysan Teal population estimates, we recommend changes to the monitoring protocol. Additional years of data are needed to quantify inter-annual seasonal detection probabilities, which may allow the use of standardized direct counts as an unbiased index of population size. Survey protocols should be enhanced through frequent resights, regular survey intervals, and determining reliable standards to detect catastrophic declines and annual changes in adult abundance. In late 2009 to early 2010, 68% of the population was marked with unique color band combinations. This allowed for potentially accurate adult population estimates and survival estimates without the need to mark new birds in 2010, 2011, and possibly 2012. However, efforts should be made to replace worn or illegible bands so birds can be identified in future surveys. It would be valuable to develop more sophisticated population size and survival models using Program MARK, a state-of-the-art software package which uses likelihood models to analyze mark-recapture data. This would allow for more reliable adult population and survival estimates to compare with the ―source‖ Laysan Teal population on Laysan Island. These models will require additional years of resight data (> 1 year) and, in some cases, an intensive annual effort of marking and recapture. Because data indicate standardized all-wetland counts are a poor index of abundance, monitoring efforts could be improved by expanding resight surveys to include all wetlands, discontinuing the all-wetland counts, and reallocating some of the wetland count effort to collect additional opportunistic resights. Approximately two years of additional bimonthly surveys are needed to validate the direct count as an appropriate index of population abundance. Additional years of individual resight data will allow estimates of adult population size, as specified in recovery criteria, and to track species population dynamics at Midway Atoll.

Optimization of seasonal ARIMA models using differential evolution - simulated annealing (DESA) algorithm in forecasting dengue cases in Baguio City

NASA Astrophysics Data System (ADS)

Addawe, Rizavel C.; Addawe, Joel M.; Magadia, Joselito C.

2016-10-01

Accurate forecasting of dengue cases would significantly improve epidemic prevention and control capabilities. This paper attempts to provide useful models in forecasting dengue epidemic specific to the young and adult population of Baguio City. To capture the seasonal variations in dengue incidence, this paper develops a robust modeling approach to identify and estimate seasonal autoregressive integrated moving average (SARIMA) models in the presence of additive outliers. Since the least squares estimators are not robust in the presence of outliers, we suggest a robust estimation based on winsorized and reweighted least squares estimators. A hybrid algorithm, Differential Evolution - Simulated Annealing (DESA), is used to identify and estimate the parameters of the optimal SARIMA model. The method is applied to the monthly reported dengue cases in Baguio City, Philippines.

A quantile count model of water depth constraints on Cape Sable seaside sparrows

USGS Publications Warehouse

Cade, B.S.; Dong, Q.

2008-01-01

1. A quantile regression model for counts of breeding Cape Sable seaside sparrows Ammodramus maritimus mirabilis (L.) as a function of water depth and previous year abundance was developed based on extensive surveys, 1992-2005, in the Florida Everglades. The quantile count model extends linear quantile regression methods to discrete response variables, providing a flexible alternative to discrete parametric distributional models, e.g. Poisson, negative binomial and their zero-inflated counterparts. 2. Estimates from our multiplicative model demonstrated that negative effects of increasing water depth in breeding habitat on sparrow numbers were dependent on recent occupation history. Upper 10th percentiles of counts (one to three sparrows) decreased with increasing water depth from 0 to 30 cm when sites were not occupied in previous years. However, upper 40th percentiles of counts (one to six sparrows) decreased with increasing water depth for sites occupied in previous years. 3. Greatest decreases (-50% to -83%) in upper quantiles of sparrow counts occurred as water depths increased from 0 to 15 cm when previous year counts were 1, but a small proportion of sites (5-10%) held at least one sparrow even as water depths increased to 20 or 30 cm. 4. A zero-inflated Poisson regression model provided estimates of conditional means that also decreased with increasing water depth but rates of change were lower and decreased with increasing previous year counts compared to the quantile count model. Quantiles computed for the zero-inflated Poisson model enhanced interpretation of this model but had greater lack-of-fit for water depths > 0 cm and previous year counts 1, conditions where the negative effect of water depths were readily apparent and fitted better with the quantile count model.

Applying citizen-science data and mark-recapture models to estimate numbers of migrant golden eagles in an important bird area in eastern North America

USGS Publications Warehouse

Dennhardt, Andrew J.; Duerr, Adam E.; Brandes, David; Katzner, Todd

2017-01-01

Estimates of population abundance are important to wildlife management and conservation. However, it can be difficult to characterize the numbers of broadly distributed, low-density, and elusive bird species. Although Golden Eagles (Aquila chrysaetos) are rare, difficult to detect, and broadly distributed, they are concentrated during their autumn migration at monitoring sites in eastern North America. We used hawk-count data collected by citizen scientists in a virtual mark–recapture modeling analysis to estimate the numbers of Golden Eagles that migrate in autumn along Kittatinny Ridge, an Important Bird Area in Pennsylvania, USA. In order to evaluate the sensitivity of our abundance estimates to variation in eagle capture histories, we applied candidate models to 8 different sets of capture histories, constructed with or without age-class information and using known mean flight speeds 6 1, 2, 4, or 6 SE for eagles to travel between hawk-count sites. Although some abundance estimates were produced by models that poorly fitted the data (ĉ > 3.0), 2 sets of population estimates were produced by acceptably performing models (cˆ less than or equal to 3.0). Application of these models to count data from November, 2002–2011, suggested a mean population abundance of 1,354 6 117 SE (range: 873–1,938). We found that Golden Eagles left the ridgeline at different rates and in different places along the route, and that typically ,50% of individuals were detected at the hawk-count sites. Our study demonstrates a useful technique for estimating population abundance that may be applicable to other migrant species that are repeatedly detected at multiple monitoring sites along a topographic diversion or leading line.

Are Books Like Number Lines? Children Spontaneously Encode Spatial-Numeric Relationships in a Novel Spatial Estimation Task

PubMed Central

Thompson, Clarissa A.; Morris, Bradley J.; Sidney, Pooja G.

2017-01-01

Do children spontaneously represent spatial-numeric features of a task, even when it does not include printed numbers (Mix et al., 2016)? Sixty first grade students completed a novel spatial estimation task by seeking and finding pages in a 100-page book without printed page numbers. Children were shown pages 1 through 6 and 100, and then were asked, “Can you find page X?” Children’s precision of estimates on the page finder task and a 0-100 number line estimation task was calculated with the Percent Absolute Error (PAE) formula (Siegler and Booth, 2004), in which lower PAE indicated more precise estimates. Children’s numerical knowledge was further assessed with: (1) numeral identification (e.g., What number is this: 57?), (2) magnitude comparison (e.g., Which is larger: 54 or 57?), and (3) counting on (e.g., Start counting from 84 and count up 5 more). Children’s accuracy on these tasks was correlated with their number line PAE. Children’s number line estimation PAE predicted their page finder PAE, even after controlling for age and accuracy on the other numerical tasks. Children’s estimates on the page finder and number line tasks appear to tap a general magnitude representation. However, the page finder task did not correlate with numeral identification and counting-on performance, likely because these tasks do not measure children’s magnitude knowledge. Our results suggest that the novel page finder task is a useful measure of children’s magnitude knowledge, and that books have similar spatial-numeric affordances as number lines and numeric board games. PMID:29312084

Robust estimation procedure in panel data model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shariff, Nurul Sima Mohamad; Hamzah, Nor Aishah

2014-06-19

The panel data modeling has received a great attention in econometric research recently. This is due to the availability of data sources and the interest to study cross sections of individuals observed over time. However, the problems may arise in modeling the panel in the presence of cross sectional dependence and outliers. Even though there are few methods that take into consideration the presence of cross sectional dependence in the panel, the methods may provide inconsistent parameter estimates and inferences when outliers occur in the panel. As such, an alternative method that is robust to outliers and cross sectional dependencemore » is introduced in this paper. The properties and construction of the confidence interval for the parameter estimates are also considered in this paper. The robustness of the procedure is investigated and comparisons are made to the existing method via simulation studies. Our results have shown that robust approach is able to produce an accurate and reliable parameter estimates under the condition considered.« less

Cancer Burden in the HIV-Infected Population in the United States

PubMed Central

Pfeiffer, Ruth M.; Gail, Mitchell H.; Hall, H. Irene; Chaturvedi, Anil K.; Bhatia, Kishor; Uldrick, Thomas S.; Yarchoan, Robert; Goedert, James J.; Engels, Eric A.

2011-01-01

Background Effective antiretroviral therapy has reduced the risk of AIDS and dramatically prolonged the survival of HIV-infected people in the United States. Consequently, an increasing number of HIV-infected people are at risk of non-AIDS-defining cancers that typically occur at older ages. We estimated the annual number of cancers in the HIV-infected population, both with and without AIDS, in the United States. Methods Incidence rates for individual cancer types were obtained from the HIV/AIDS Cancer Match Study by linking 15 HIV and cancer registries in the United States. Estimated counts of the US HIV-infected and AIDS populations were obtained from Centers for Disease Control and Prevention surveillance data. We obtained estimated counts of AIDS-defining (ie, Kaposi sarcoma, non-Hodgkin lymphoma, and cervical cancer) and non-AIDS-defining cancers in the US AIDS population during 1991–2005 by multiplying cancer incidence rates and AIDS population counts, stratified by year, age, sex, race and ethnicity, transmission category, and AIDS-relative time. We tested trends in counts and standardized incidence rates using linear regression models. We multiplied overall cancer rates and HIV-only (HIV infected, without AIDS) population counts, available from 34 US states during 2004–2007, to estimate cancers in the HIV-only population. All statistical tests were two-sided. Results The US AIDS population expanded fourfold from 1991 to 2005 (96 179 to 413 080) largely because of an increase in the number of people aged 40 years or older. During 1991–2005, an estimated 79 656 cancers occurred in the AIDS population. From 1991–1995 to 2001–2005, the estimated number of AIDS-defining cancers decreased by greater than threefold (34 587 to 10 325 cancers; Ptrend < .001), whereas non-AIDS-defining cancers increased by approximately threefold (3193 to 10 059 cancers; Ptrend < .001). From 1991–1995 to 2001–2005, estimated counts increased for anal (206 to 1564 cancers), liver (116 to 583 cancers), prostate (87 to 759 cancers), and lung cancers (875 to 1882 cancers), and Hodgkin lymphoma (426 to 897 cancers). In the HIV-only population in 34 US states, an estimated 2191 non-AIDS-defining cancers occurred during 2004–2007, including 454 lung, 166 breast, and 154 anal cancers. Conclusions Over a 15-year period (1991–2005), increases in non-AIDS-defining cancers were mainly driven by growth and aging of the AIDS population. This growing burden requires targeted cancer prevention and treatment strategies. PMID:21483021

Hierarchical Bayes estimation of species richness and occupancy in spatially replicated surveys

USGS Publications Warehouse

Kery, M.; Royle, J. Andrew

2008-01-01

1. Species richness is the most widely used biodiversity metric, but cannot be observed directly as, typically, some species are overlooked. Imperfect detectability must therefore be accounted for to obtain unbiased species-richness estimates. When richness is assessed at multiple sites, two approaches can be used to estimate species richness: either estimating for each site separately, or pooling all samples. The first approach produces imprecise estimates, while the second loses site-specific information. 2. In contrast, a hierarchical Bayes (HB) multispecies site-occupancy model benefits from the combination of information across sites without losing site-specific information and also yields occupancy estimates for each species. The heart of the model is an estimate of the incompletely observed presence-absence matrix, a centrepiece of biogeography and monitoring studies. We illustrate the model using Swiss breeding bird survey data, and compare its estimates with the widely used jackknife species-richness estimator and raw species counts. 3. Two independent observers each conducted three surveys in 26 1-km(2) quadrats, and detected 27-56 (total 103) species. The average estimated proportion of species detected after three surveys was 0.87 under the HB model. Jackknife estimates were less precise (less repeatable between observers) than raw counts, but HB estimates were as repeatable as raw counts. The combination of information in the HB model thus resulted in species-richness estimates presumably at least as unbiased as previous approaches that correct for detectability, but without costs in precision relative to uncorrected, biased species counts. 4. Total species richness in the entire region sampled was estimated at 113.1 (CI 106-123); species detectability ranged from 0.08 to 0.99, illustrating very heterogeneous species detectability; and species occupancy was 0.06-0.96. Even after six surveys, absolute bias in observed occupancy was estimated at up to 0.40. 5. Synthesis and applications. The HB model for species-richness estimation combines information across sites and enjoys more precise, and presumably less biased, estimates than previous approaches. It also yields estimates of several measures of community size and composition. Covariates for occupancy and detectability can be included. We believe it has considerable potential for monitoring programmes as well as in biogeography and community ecology.

Robust Variable Selection with Exponential Squared Loss.

PubMed

Wang, Xueqin; Jiang, Yunlu; Huang, Mian; Zhang, Heping

2013-04-01

Robust variable selection procedures through penalized regression have been gaining increased attention in the literature. They can be used to perform variable selection and are expected to yield robust estimates. However, to the best of our knowledge, the robustness of those penalized regression procedures has not been well characterized. In this paper, we propose a class of penalized robust regression estimators based on exponential squared loss. The motivation for this new procedure is that it enables us to characterize its robustness that has not been done for the existing procedures, while its performance is near optimal and superior to some recently developed methods. Specifically, under defined regularity conditions, our estimators are [Formula: see text] and possess the oracle property. Importantly, we show that our estimators can achieve the highest asymptotic breakdown point of 1/2 and that their influence functions are bounded with respect to the outliers in either the response or the covariate domain. We performed simulation studies to compare our proposed method with some recent methods, using the oracle method as the benchmark. We consider common sources of influential points. Our simulation studies reveal that our proposed method performs similarly to the oracle method in terms of the model error and the positive selection rate even in the presence of influential points. In contrast, other existing procedures have a much lower non-causal selection rate. Furthermore, we re-analyze the Boston Housing Price Dataset and the Plasma Beta-Carotene Level Dataset that are commonly used examples for regression diagnostics of influential points. Our analysis unravels the discrepancies of using our robust method versus the other penalized regression method, underscoring the importance of developing and applying robust penalized regression methods.

Robust Variable Selection with Exponential Squared Loss

PubMed Central

Wang, Xueqin; Jiang, Yunlu; Huang, Mian; Zhang, Heping

2013-01-01

Robust variable selection procedures through penalized regression have been gaining increased attention in the literature. They can be used to perform variable selection and are expected to yield robust estimates. However, to the best of our knowledge, the robustness of those penalized regression procedures has not been well characterized. In this paper, we propose a class of penalized robust regression estimators based on exponential squared loss. The motivation for this new procedure is that it enables us to characterize its robustness that has not been done for the existing procedures, while its performance is near optimal and superior to some recently developed methods. Specifically, under defined regularity conditions, our estimators are n-consistent and possess the oracle property. Importantly, we show that our estimators can achieve the highest asymptotic breakdown point of 1/2 and that their influence functions are bounded with respect to the outliers in either the response or the covariate domain. We performed simulation studies to compare our proposed method with some recent methods, using the oracle method as the benchmark. We consider common sources of influential points. Our simulation studies reveal that our proposed method performs similarly to the oracle method in terms of the model error and the positive selection rate even in the presence of influential points. In contrast, other existing procedures have a much lower non-causal selection rate. Furthermore, we re-analyze the Boston Housing Price Dataset and the Plasma Beta-Carotene Level Dataset that are commonly used examples for regression diagnostics of influential points. Our analysis unravels the discrepancies of using our robust method versus the other penalized regression method, underscoring the importance of developing and applying robust penalized regression methods. PMID:23913996

Are house counts reliable estimators of dusky-footed woodrat population size?

Treesearch

WILLIAM F. LAUDENSLAYER; ROBERTA FARGO

1999-01-01

Dusky-footed woodrat (Neotoma jiocipes) abundance is often esti~nated using housc counts; a house rypically being described as a large pilc of sticks, usually built on the ground, but occasionally on tree limbs. For purposes of thc count, it is somcti~nes assunlccl that each "active" house represents one woodrat. An activc woodrat house is indicated by its...

Synthetic biology and regulatory networks: where metabolic systems biology meets control engineering

PubMed Central

He, Fei; Murabito, Ettore; Westerhoff, Hans V.

2016-01-01

Metabolic pathways can be engineered to maximize the synthesis of various products of interest. With the advent of computational systems biology, this endeavour is usually carried out through in silico theoretical studies with the aim to guide and complement further in vitro and in vivo experimental efforts. Clearly, what counts is the result in vivo, not only in terms of maximal productivity but also robustness against environmental perturbations. Engineering an organism towards an increased production flux, however, often compromises that robustness. In this contribution, we review and investigate how various analytical approaches used in metabolic engineering and synthetic biology are related to concepts developed by systems and control engineering. While trade-offs between production optimality and cellular robustness have already been studied diagnostically and statically, the dynamics also matter. Integration of the dynamic design aspects of control engineering with the more diagnostic aspects of metabolic, hierarchical control and regulation analysis is leading to the new, conceptual and operational framework required for the design of robust and productive dynamic pathways. PMID:27075000

Spatial distribution, sampling precision and survey design optimisation with non-normal variables: The case of anchovy (Engraulis encrasicolus) recruitment in Spanish Mediterranean waters

NASA Astrophysics Data System (ADS)

Tugores, M. Pilar; Iglesias, Magdalena; Oñate, Dolores; Miquel, Joan

2016-02-01

In the Mediterranean Sea, the European anchovy (Engraulis encrasicolus) displays a key role in ecological and economical terms. Ensuring stock sustainability requires the provision of crucial information, such as species spatial distribution or unbiased abundance and precision estimates, so that management strategies can be defined (e.g. fishing quotas, temporal closure areas or marine protected areas MPA). Furthermore, the estimation of the precision of global abundance at different sampling intensities can be used for survey design optimisation. Geostatistics provide a priori unbiased estimations of the spatial structure, global abundance and precision for autocorrelated data. However, their application to non-Gaussian data introduces difficulties in the analysis in conjunction with low robustness or unbiasedness. The present study applied intrinsic geostatistics in two dimensions in order to (i) analyse the spatial distribution of anchovy in Spanish Western Mediterranean waters during the species' recruitment season, (ii) produce distribution maps, (iii) estimate global abundance and its precision, (iv) analyse the effect of changing the sampling intensity on the precision of global abundance estimates and, (v) evaluate the effects of several methodological options on the robustness of all the analysed parameters. The results suggested that while the spatial structure was usually non-robust to the tested methodological options when working with the original dataset, it became more robust for the transformed datasets (especially for the log-backtransformed dataset). The global abundance was always highly robust and the global precision was highly or moderately robust to most of the methodological options, except for data transformation.

Characterizing the performance of the Conway-Maxwell Poisson generalized linear model.

PubMed

Francis, Royce A; Geedipally, Srinivas Reddy; Guikema, Seth D; Dhavala, Soma Sekhar; Lord, Dominique; LaRocca, Sarah

2012-01-01

Count data are pervasive in many areas of risk analysis; deaths, adverse health outcomes, infrastructure system failures, and traffic accidents are all recorded as count events, for example. Risk analysts often wish to estimate the probability distribution for the number of discrete events as part of doing a risk assessment. Traditional count data regression models of the type often used in risk assessment for this problem suffer from limitations due to the assumed variance structure. A more flexible model based on the Conway-Maxwell Poisson (COM-Poisson) distribution was recently proposed, a model that has the potential to overcome the limitations of the traditional model. However, the statistical performance of this new model has not yet been fully characterized. This article assesses the performance of a maximum likelihood estimation method for fitting the COM-Poisson generalized linear model (GLM). The objectives of this article are to (1) characterize the parameter estimation accuracy of the MLE implementation of the COM-Poisson GLM, and (2) estimate the prediction accuracy of the COM-Poisson GLM using simulated data sets. The results of the study indicate that the COM-Poisson GLM is flexible enough to model under-, equi-, and overdispersed data sets with different sample mean values. The results also show that the COM-Poisson GLM yields accurate parameter estimates. The COM-Poisson GLM provides a promising and flexible approach for performing count data regression. © 2011 Society for Risk Analysis.

A hybrid double-observer sightability model for aerial surveys

USGS Publications Warehouse

Griffin, Paul C.; Lubow, Bruce C.; Jenkins, Kurt J.; Vales, David J.; Moeller, Barbara J.; Reid, Mason; Happe, Patricia J.; Mccorquodale, Scott M.; Tirhi, Michelle J.; Schaberi, Jim P.; Beirne, Katherine

2013-01-01

Raw counts from aerial surveys make no correction for undetected animals and provide no estimate of precision with which to judge the utility of the counts. Sightability modeling and double-observer (DO) modeling are 2 commonly used approaches to account for detection bias and to estimate precision in aerial surveys. We developed a hybrid DO sightability model (model MH) that uses the strength of each approach to overcome the weakness in the other, for aerial surveys of elk (Cervus elaphus). The hybrid approach uses detection patterns of 2 independent observer pairs in a helicopter and telemetry-based detections of collared elk groups. Candidate MH models reflected hypotheses about effects of recorded covariates and unmodeled heterogeneity on the separate front-seat observer pair and back-seat observer pair detection probabilities. Group size and concealing vegetation cover strongly influenced detection probabilities. The pilot's previous experience participating in aerial surveys influenced detection by the front pair of observers if the elk group was on the pilot's side of the helicopter flight path. In 9 surveys in Mount Rainier National Park, the raw number of elk counted was approximately 80–93% of the abundance estimated by model MH. Uncorrected ratios of bulls per 100 cows generally were low compared to estimates adjusted for detection bias, but ratios of calves per 100 cows were comparable whether based on raw survey counts or adjusted estimates. The hybrid method was an improvement over commonly used alternatives, with improved precision compared to sightability modeling and reduced bias compared to DO modeling.

Bias and robustness of uncertainty components estimates in transient climate projections

NASA Astrophysics Data System (ADS)

Hingray, Benoit; Blanchet, Juliette; Jean-Philippe, Vidal

2016-04-01

A critical issue in climate change studies is the estimation of uncertainties in projections along with the contribution of the different uncertainty sources, including scenario uncertainty, the different components of model uncertainty and internal variability. Quantifying the different uncertainty sources faces actually different problems. For instance and for the sake of simplicity, an estimate of model uncertainty is classically obtained from the empirical variance of the climate responses obtained for the different modeling chains. These estimates are however biased. Another difficulty arises from the limited number of members that are classically available for most modeling chains. In this case, the climate response of one given chain and the effect of its internal variability may be actually difficult if not impossible to separate. The estimate of scenario uncertainty, model uncertainty and internal variability components are thus likely to be not really robust. We explore the importance of the bias and the robustness of the estimates for two classical Analysis of Variance (ANOVA) approaches: a Single Time approach (STANOVA), based on the only data available for the considered projection lead time and a time series based approach (QEANOVA), which assumes quasi-ergodicity of climate outputs over the whole available climate simulation period (Hingray and Saïd, 2014). We explore both issues for a simple but classical configuration where uncertainties in projections are composed of two single sources: model uncertainty and internal climate variability. The bias in model uncertainty estimates is explored from theoretical expressions of unbiased estimators developed for both ANOVA approaches. The robustness of uncertainty estimates is explored for multiple synthetic ensembles of time series projections generated with MonteCarlo simulations. For both ANOVA approaches, when the empirical variance of climate responses is used to estimate model uncertainty, the bias is always positive. It can be especially high with STANOVA. In the most critical configurations, when the number of members available for each modeling chain is small (< 3) and when internal variability explains most of total uncertainty variance (75% or more), the overestimation is higher than 100% of the true model uncertainty variance. The bias can be considerably reduced with a time series ANOVA approach, owing to the multiple time steps accounted for. The longer the transient time period used for the analysis, the larger the reduction. When a quasi-ergodic ANOVA approach is applied to decadal data for the whole 1980-2100 period, the bias is reduced by a factor 2.5 to 20 depending on the projection lead time. In all cases, the bias is likely to be not negligible for a large number of climate impact studies resulting in a likely large overestimation of the contribution of model uncertainty to total variance. For both approaches, the robustness of all uncertainty estimates is higher when more members are available, when internal variability is smaller and/or the response-to-uncertainty ratio is higher. QEANOVA estimates are much more robust than STANOVA ones: QEANOVA simulated confidence intervals are roughly 3 to 5 times smaller than STANOVA ones. Excepted for STANOVA when less than 3 members is available, the robustness is rather high for total uncertainty and moderate for internal variability estimates. For model uncertainty or response-to-uncertainty ratio estimates, the robustness is conversely low for QEANOVA to very low for STANOVA. In the most critical configurations (small number of member, large internal variability), large over- or underestimation of uncertainty components is very thus likely. To propose relevant uncertainty analyses and avoid misleading interpretations, estimates of uncertainty components should be therefore bias corrected and ideally come with estimates of their robustness. This work is part of the COMPLEX Project (European Collaborative Project FP7-ENV-2012 number: 308601; http://www.complex.ac.uk/). Hingray, B., Saïd, M., 2014. Partitioning internal variability and model uncertainty components in a multimodel multireplicate ensemble of climate projections. J.Climate. doi:10.1175/JCLI-D-13-00629.1 Hingray, B., Blanchet, J. (revision) Unbiased estimators for uncertainty components in transient climate projections. J. Climate Hingray, B., Blanchet, J., Vidal, J.P. (revision) Robustness of uncertainty components estimates in climate projections. J.Climate

Trend estimation in populations with imperfect detection

USGS Publications Warehouse

Kery, Marc; Dorazio, Robert M.; Soldaat, Leo; Van Strien, Arco; Zuiderwijk, Annie; Royle, J. Andrew

2009-01-01

1. Trends of animal populations are of great interest in ecology but cannot be directly observed owing to imperfect detection. Binomial mixture models use replicated counts to estimate abundance, corrected for detection, in demographically closed populations. Here, we extend these models to open populations and illustrate them using sand lizard Lacerta agilis counts from the national Dutch reptile monitoring scheme. 2. Our model requires replicated counts from multiple sites in each of several periods, within which population closure is assumed. Counts are described by a hierarchical generalized linear model, where the state model deals with spatio-temporal patterns in true abundance and the observation model with imperfect counts, given that true state. We used WinBUGS to fit the model to lizard counts from 208 transects with 1–10 (mean 3) replicate surveys during each spring 1994–2005. 3. Our state model for abundance contained two independent log-linear Poisson regressions on year for coastal and inland sites, and random site effects to account for unexplained heterogeneity. The observation model for detection of an individual lizard contained effects of region, survey date, temperature, observer experience and random survey effects. 4. Lizard populations increased in both regions but more steeply on the coast. Detectability increased over the first few years of the study, was greater on the coast and for the most experienced observers, and highest around 1 June. Interestingly, the population increase inland was not detectable when the observed counts were analysed without account of detectability. The proportional increase between 1994 and 2005 in total lizard abundance across all sites was estimated at 86% (95% CRI 35–151). 5. Synthesis and applications. Open-population binomial mixture models are attractive for studying true population dynamics while explicitly accounting for the observation process, i.e. imperfect detection. We emphasize the important conceptual benefit provided by temporal replicate observations in terms of the interpretability of animal counts.

Robust detection, isolation and accommodation for sensor failures

NASA Technical Reports Server (NTRS)

Emami-Naeini, A.; Akhter, M. M.; Rock, S. M.

1986-01-01

The objective is to extend the recent advances in robust control system design of multivariable systems to sensor failure detection, isolation, and accommodation (DIA), and estimator design. This effort provides analysis tools to quantify the trade-off between performance robustness and DIA sensitivity, which are to be used to achieve higher levels of performance robustness for given levels of DIA sensitivity. An innovations-based DIA scheme is used. Estimators, which depend upon a model of the process and process inputs and outputs, are used to generate these innovations. Thresholds used to determine failure detection are computed based on bounds on modeling errors, noise properties, and the class of failures. The applicability of the newly developed tools are demonstrated on a multivariable aircraft turbojet engine example. A new concept call the threshold selector was developed. It represents a significant and innovative tool for the analysis and synthesis of DiA algorithms. The estimators were made robust by introduction of an internal model and by frequency shaping. The internal mode provides asymptotically unbiased filter estimates.The incorporation of frequency shaping of the Linear Quadratic Gaussian cost functional modifies the estimator design to make it suitable for sensor failure DIA. The results are compared with previous studies which used thresholds that were selcted empirically. Comparison of these two techniques on a nonlinear dynamic engine simulation shows improved performance of the new method compared to previous techniques

A Robust Step Detection Algorithm and Walking Distance Estimation Based on Daily Wrist Activity Recognition Using a Smart Band.

PubMed

Trong Bui, Duong; Nguyen, Nhan Duc; Jeong, Gu-Min

2018-06-25

Human activity recognition and pedestrian dead reckoning are an interesting field because of their importance utilities in daily life healthcare. Currently, these fields are facing many challenges, one of which is the lack of a robust algorithm with high performance. This paper proposes a new method to implement a robust step detection and adaptive distance estimation algorithm based on the classification of five daily wrist activities during walking at various speeds using a smart band. The key idea is that the non-parametric adaptive distance estimator is performed after two activity classifiers and a robust step detector. In this study, two classifiers perform two phases of recognizing five wrist activities during walking. Then, a robust step detection algorithm, which is integrated with an adaptive threshold, peak and valley correction algorithm, is applied to the classified activities to detect the walking steps. In addition, the misclassification activities are fed back to the previous layer. Finally, three adaptive distance estimators, which are based on a non-parametric model of the average walking speed, calculate the length of each strike. The experimental results show that the average classification accuracy is about 99%, and the accuracy of the step detection is 98.7%. The error of the estimated distance is 2.2⁻4.2% depending on the type of wrist activities.

Rain volume estimation over areas using satellite and radar data

NASA Technical Reports Server (NTRS)

Doneaud, A. A.; Vonderhaar, T. H.

1985-01-01

An investigation of the feasibility of rain volume estimation using satellite data following a technique recently developed with radar data called the Arera Time Integral was undertaken. Case studies were selected on the basis of existing radar and satellite data sets which match in space and time. Four multicell clusters were analyzed. Routines for navigation remapping amd smoothing of satellite images were performed. Visible counts were normalized for solar zenith angle. A radar sector of interest was defined to delineate specific radar echo clusters for each radar time throughout the radar echo cluster lifetime. A satellite sector of interest was defined by applying small adjustments to the radar sector using a manual processing technique. The radar echo area, the IR maximum counts and the IR counts matching radar echo areas were found to evolve similarly, except for the decaying phase of the cluster where the cirrus debris keeps the IR counts high.

Quick counting method for estimating the number of viable microbes on food and food processing equipment.

PubMed

Winter, F H; York, G K; el-Nakhal, H

1971-07-01

A rapid method for estimating the extent of microbial contamination on food and on food processing equipment is described. Microbial cells are rinsed from food or swab samples with sterile diluent and concentrated on the surface of membrane filters. The filters are incubated on a suitable bacteriological medium for 4 hr at 30 C, heated at 105 C for 5 min, and stained. The membranes are then dried at 60 C for 15 min, rendered transparent with immersion oil, and examined microscopically. Data obtained by the rapid method were compared with counts of the same samples determined by the standard plate count method. Over 60 comparisons resulted in a correlation coefficient of 0.906. Because the rapid technique can provide reliable microbiological count information in extremely short times, it can be a most useful tool in the routine evaluation of microbial contamination of food processing facilities and for some foods.

CosmoQuest - Mapping Surface Features Across the Inner Solar System

NASA Astrophysics Data System (ADS)

Grier, Jennifer A.; Richardson, Matthew; Gay, Pamela L.; Lehan, Cory; Owens, Ryan; Robbins, Stuart J.; DellaGiustina, Daniella; Bennett, Carina; Runco, Susan; Graff, Paige

2017-10-01

The CosmoQuest Virtual Research Facility allows research scientists to work together with citizen scientists in ‘big data’ investigations. Some research requires the examination of vast numbers of images - partnering with engaged and trained citizen scientists allows for that research to be completed in a thorough and timely manner. The techniques used by CosmoQuest to collect impact crater data have been validated to ensure robustness (Robbins et al., 2014), and include software tools that accurately identify crater clusters, and multiple crater identifications. CosmoQuest has current or up-and-coming projects that span much of the inner solar system. “Moon Mappers” gives the public a chance to learn about the importance of cratered surfaces, and investigate factors that effect the identification and measurement of impact craters such as incidence angle. In the “Mars Mappers” program citizens map small craters in valley networks. These will be used to estimate times of ancient water flow. In “Mercury Mappers” the public learns about other issues related to crater counting, such as secondaries. On Mercury, secondaries appear to dominate counts up to 10km. By mapping these craters, we will be able to better understand the maximum diameter of secondaries relative to the parent primary. The public encounters Vesta in “Vesta Mappers,” a project that contributes data to the overall crater counting efforts on that body. Asteroid investigations do not end there - the OSIRIS-REx team is collaborating with CosmoQuest to create a science campaign to generate boulder and crater counting datasets of the asteroid Bennu. This “Bennu Mappers” project will inform the final selection of the sample return site. The Earth is the target for the “Image Detective” project, which uses the 2 million images returned from crewed space flight. These images are rich in information about our changing Earth, as well as phenomena like aurora. Citizens tag these images with meta-data such as visible features and the center point location of imagery to enable scientists and the public to more easily search for imagery of interest in NASA’s online database of astronaut imagery of Earth.

A Comparison of the Sensitivity and Fecal Egg Counts of the McMaster Egg Counting and Kato-Katz Thick Smear Methods for Soil-Transmitted Helminths

PubMed Central

Levecke, Bruno; Behnke, Jerzy M.; Ajjampur, Sitara S. R.; Albonico, Marco; Ame, Shaali M.; Charlier, Johannes; Geiger, Stefan M.; Hoa, Nguyen T. V.; Kamwa Ngassam, Romuald I.; Kotze, Andrew C.; McCarthy, James S.; Montresor, Antonio; Periago, Maria V.; Roy, Sheela; Tchuem Tchuenté, Louis-Albert; Thach, D. T. C.; Vercruysse, Jozef

2011-01-01

Background The Kato-Katz thick smear (Kato-Katz) is the diagnostic method recommended for monitoring large-scale treatment programs implemented for the control of soil-transmitted helminths (STH) in public health, yet it is difficult to standardize. A promising alternative is the McMaster egg counting method (McMaster), commonly used in veterinary parasitology, but rarely so for the detection of STH in human stool. Methodology/Principal Findings The Kato-Katz and McMaster methods were compared for the detection of STH in 1,543 subjects resident in five countries across Africa, Asia and South America. The consistency of the performance of both methods in different trials, the validity of the fixed multiplication factor employed in the Kato-Katz method and the accuracy of these methods for estimating ‘true’ drug efficacies were assessed. The Kato-Katz method detected significantly more Ascaris lumbricoides infections (88.1% vs. 75.6%, p<0.001), whereas the difference in sensitivity between the two methods was non-significant for hookworm (78.3% vs. 72.4%) and Trichuris trichiura (82.6% vs. 80.3%). The sensitivity of the methods varied significantly across trials and magnitude of fecal egg counts (FEC). Quantitative comparison revealed a significant correlation (Rs >0.32) in FEC between both methods, and indicated no significant difference in FEC, except for A. lumbricoides, where the Kato-Katz resulted in significantly higher FEC (14,197 eggs per gram of stool (EPG) vs. 5,982 EPG). For the Kato-Katz, the fixed multiplication factor resulted in significantly higher FEC than the multiplication factor adjusted for mass of feces examined for A. lumbricoides (16,538 EPG vs. 15,396 EPG) and T. trichiura (1,490 EPG vs. 1,363 EPG), but not for hookworm. The McMaster provided more accurate efficacy results (absolute difference to ‘true’ drug efficacy: 1.7% vs. 4.5%). Conclusions/Significance The McMaster is an alternative method for monitoring large-scale treatment programs. It is a robust (accurate multiplication factor) and accurate (reliable efficacy results) method, which can be easily standardized. PMID:21695104

A generalised random encounter model for estimating animal density with remote sensor data.

PubMed

Lucas, Tim C D; Moorcroft, Elizabeth A; Freeman, Robin; Rowcliffe, J Marcus; Jones, Kate E

2015-05-01

Wildlife monitoring technology is advancing rapidly and the use of remote sensors such as camera traps and acoustic detectors is becoming common in both the terrestrial and marine environments. Current methods to estimate abundance or density require individual recognition of animals or knowing the distance of the animal from the sensor, which is often difficult. A method without these requirements, the random encounter model (REM), has been successfully applied to estimate animal densities from count data generated from camera traps. However, count data from acoustic detectors do not fit the assumptions of the REM due to the directionality of animal signals.We developed a generalised REM (gREM), to estimate absolute animal density from count data from both camera traps and acoustic detectors. We derived the gREM for different combinations of sensor detection widths and animal signal widths (a measure of directionality). We tested the accuracy and precision of this model using simulations of different combinations of sensor detection widths and animal signal widths, number of captures and models of animal movement.We find that the gREM produces accurate estimates of absolute animal density for all combinations of sensor detection widths and animal signal widths. However, larger sensor detection and animal signal widths were found to be more precise. While the model is accurate for all capture efforts tested, the precision of the estimate increases with the number of captures. We found no effect of different animal movement models on the accuracy and precision of the gREM.We conclude that the gREM provides an effective method to estimate absolute animal densities from remote sensor count data over a range of sensor and animal signal widths. The gREM is applicable for count data obtained in both marine and terrestrial environments, visually or acoustically (e.g. big cats, sharks, birds, echolocating bats and cetaceans). As sensors such as camera traps and acoustic detectors become more ubiquitous, the gREM will be increasingly useful for monitoring unmarked animal populations across broad spatial, temporal and taxonomic scales.

Semantic similarity measure in biomedical domain leverage web search engine.

PubMed

Chen, Chi-Huang; Hsieh, Sheau-Ling; Weng, Yung-Ching; Chang, Wen-Yung; Lai, Feipei

2010-01-01

Semantic similarity measure plays an essential role in Information Retrieval and Natural Language Processing. In this paper we propose a page-count-based semantic similarity measure and apply it in biomedical domains. Previous researches in semantic web related applications have deployed various semantic similarity measures. Despite the usefulness of the measurements in those applications, measuring semantic similarity between two terms remains a challenge task. The proposed method exploits page counts returned by the Web Search Engine. We define various similarity scores for two given terms P and Q, using the page counts for querying P, Q and P AND Q. Moreover, we propose a novel approach to compute semantic similarity using lexico-syntactic patterns with page counts. These different similarity scores are integrated adapting support vector machines, to leverage the robustness of semantic similarity measures. Experimental results on two datasets achieve correlation coefficients of 0.798 on the dataset provided by A. Hliaoutakis, 0.705 on the dataset provide by T. Pedersen with physician scores and 0.496 on the dataset provided by T. Pedersen et al. with expert scores.

Constraining Swiss Methane Emissions from Atmospheric Observations: Sensitivities and Temporal Development

NASA Astrophysics Data System (ADS)

Henne, Stephan; Leuenberger, Markus; Steinbacher, Martin; Eugster, Werner; Meinhardt, Frank; Bergamaschi, Peter; Emmenegger, Lukas; Brunner, Dominik

2017-04-01

Similar to other Western European countries, agricultural sources dominate the methane (CH4) emission budget in Switzerland. 'Bottom-up' estimates of these emissions are still connected with relatively large uncertainties due to considerable variability and uncertainties in observed emission factors for the underlying processes (e.g., enteric fermentation, manure management). Here, we present a regional-scale (˜300 x 200 km2) atmospheric inversion study of CH4 emissions in Switzerland making use of the recently established CarboCount-CH network of four stations on the Swiss Plateau as well as the neighbouring mountain-top sites Jungfraujoch and Schauinsland (Germany). Continuous observations from all CarboCount-CH sites are available since 2013. We use a high-resolution (7 x 7 km2) Lagrangian particle dispersion model (FLEXPART-COSMO) in connection with two different inversion systems (Bayesian and extended Kalman filter) to estimate spatially and temporally resolved CH4 emissions for the Swiss domain in the period 2013 to 2016. An extensive set of sensitivity inversions is used to assess the overall uncertainty of our inverse approach. In general we find good agreement of the total Swiss CH4 emissions between our 'top-down' estimate and the national 'bottom-up' reporting. In addition, a robust emission seasonality, with reduced winter time values, can be seen in all years. No significant trend or year-to-year variability was observed for the analysed four-year period, again in agreement with a very small downward trend in the national 'bottom-up' reporting. Special attention is given to the influence of boundary conditions as taken from different global scale model simulations (TM5, FLEXPART) and remote observations. We find that uncertainties in the boundary conditions can induce large offsets in the national total emissions. However, spatial emission patterns are less sensitive to the choice of boundary condition. Furthermore and in order to demonstrate the validity of our approach, a series of inversion runs using synthetic observations, generated from 'true' emissions, in combination with various sources of uncertainty are presented.

On the robustness of a Bayes estimate. [in reliability theory

NASA Technical Reports Server (NTRS)

Canavos, G. C.

1974-01-01

This paper examines the robustness of a Bayes estimator with respect to the assigned prior distribution. A Bayesian analysis for a stochastic scale parameter of a Weibull failure model is summarized in which the natural conjugate is assigned as the prior distribution of the random parameter. The sensitivity analysis is carried out by the Monte Carlo method in which, although an inverted gamma is the assigned prior, realizations are generated using distribution functions of varying shape. For several distributional forms and even for some fixed values of the parameter, simulated mean squared errors of Bayes and minimum variance unbiased estimators are determined and compared. Results indicate that the Bayes estimator remains squared-error superior and appears to be largely robust to the form of the assigned prior distribution.

PET image reconstruction: a robust state space approach.

PubMed

Liu, Huafeng; Tian, Yi; Shi, Pengcheng

2005-01-01

Statistical iterative reconstruction algorithms have shown improved image quality over conventional nonstatistical methods in PET by using accurate system response models and measurement noise models. Strictly speaking, however, PET measurements, pre-corrected for accidental coincidences, are neither Poisson nor Gaussian distributed and thus do not meet basic assumptions of these algorithms. In addition, the difficulty in determining the proper system response model also greatly affects the quality of the reconstructed images. In this paper, we explore the usage of state space principles for the estimation of activity map in tomographic PET imaging. The proposed strategy formulates the organ activity distribution through tracer kinetics models, and the photon-counting measurements through observation equations, thus makes it possible to unify the dynamic reconstruction problem and static reconstruction problem into a general framework. Further, it coherently treats the uncertainties of the statistical model of the imaging system and the noisy nature of measurement data. Since H(infinity) filter seeks minimummaximum-error estimates without any assumptions on the system and data noise statistics, it is particular suited for PET image reconstruction where the statistical properties of measurement data and the system model are very complicated. The performance of the proposed framework is evaluated using Shepp-Logan simulated phantom data and real phantom data with favorable results.

Robust range estimation with a monocular camera for vision-based forward collision warning system.

PubMed

Park, Ki-Yeong; Hwang, Sun-Young

2014-01-01

We propose a range estimation method for vision-based forward collision warning systems with a monocular camera. To solve the problem of variation of camera pitch angle due to vehicle motion and road inclination, the proposed method estimates virtual horizon from size and position of vehicles in captured image at run-time. The proposed method provides robust results even when road inclination varies continuously on hilly roads or lane markings are not seen on crowded roads. For experiments, a vision-based forward collision warning system has been implemented and the proposed method is evaluated with video clips recorded in highway and urban traffic environments. Virtual horizons estimated by the proposed method are compared with horizons manually identified, and estimated ranges are compared with measured ranges. Experimental results confirm that the proposed method provides robust results both in highway and in urban traffic environments.

Robust Range Estimation with a Monocular Camera for Vision-Based Forward Collision Warning System

PubMed Central

2014-01-01

We propose a range estimation method for vision-based forward collision warning systems with a monocular camera. To solve the problem of variation of camera pitch angle due to vehicle motion and road inclination, the proposed method estimates virtual horizon from size and position of vehicles in captured image at run-time. The proposed method provides robust results even when road inclination varies continuously on hilly roads or lane markings are not seen on crowded roads. For experiments, a vision-based forward collision warning system has been implemented and the proposed method is evaluated with video clips recorded in highway and urban traffic environments. Virtual horizons estimated by the proposed method are compared with horizons manually identified, and estimated ranges are compared with measured ranges. Experimental results confirm that the proposed method provides robust results both in highway and in urban traffic environments. PMID:24558344

Evaluation of 230 patients with relapsed/refractory deletion 17p chronic lymphocytic leukaemia treated with ibrutinib from 3 clinical trials.

PubMed

Jones, Jeffrey; Mato, Anthony; Coutre, Steven; Byrd, John C; Furman, Richard R; Hillmen, Peter; Osterborg, Anders; Tam, Constantine; Stilgenbauer, Stephan; Wierda, William G; Heerema, Nyla A; Eckert, Karl; Clow, Fong; Zhou, Cathy; Chu, Alvina D; James, Danelle F; O'Brien, Susan M

2018-06-05

Patients with chronic lymphocytic leukaemia/small lymphocytic lymphoma (CLL/SLL) with deletion 17p [del(17p)] have poor outcomes with chemoimmunotherapy. Ibrutinib is indicated for the treatment of CLL/SLL, including del(17p) CLL/SLL, and allows for treatment without chemotherapy. This integrated analysis was performed to evaluate outcomes in 230 patients with relapsed/refractory del(17p) CLL/SLL from three ibrutinib studies. With a median of 2 prior therapies (range, 1-12), 18% and 79% of evaluable patients had del(11q) or unmutated IGHV, respectively. With a median follow-up of 28 months, overall response rate was 85% and estimated 30-month progression-free and overall survival rates were 57% [95% confidence interval (CI) 50-64] and 69% (95% CI 61-75), respectively. Patients with normal lactate dehydrogenase or no bulky disease had the most favourable survival outcomes. Sustained haematological improvements in haemoglobin, platelet count and absolute neutrophil count occurred in 61%, 67% and 70% of patients with baseline cytopenias, respectively. New onset severe cytopenias and infections decreased in frequency over time. Progression-free and overall survival with ibrutinib surpass those of other therapies for patients with del(17p) CLL/SLL. These results provide further evidence of the robust clinical activity of ibrutinib in difficult-to-treat CLL/SLL populations. © 2018 The Authors. British Journal of Haematology published by John Wiley & Sons Ltd.

A robust and accurate center-frequency estimation (RACE) algorithm for improving motion estimation performance of SinMod on tagged cardiac MR images without known tagging parameters.

PubMed

Liu, Hong; Wang, Jie; Xu, Xiangyang; Song, Enmin; Wang, Qian; Jin, Renchao; Hung, Chih-Cheng; Fei, Baowei

2014-11-01

A robust and accurate center-frequency (CF) estimation (RACE) algorithm for improving the performance of the local sine-wave modeling (SinMod) method, which is a good motion estimation method for tagged cardiac magnetic resonance (MR) images, is proposed in this study. The RACE algorithm can automatically, effectively and efficiently produce a very appropriate CF estimate for the SinMod method, under the circumstance that the specified tagging parameters are unknown, on account of the following two key techniques: (1) the well-known mean-shift algorithm, which can provide accurate and rapid CF estimation; and (2) an original two-direction-combination strategy, which can further enhance the accuracy and robustness of CF estimation. Some other available CF estimation algorithms are brought out for comparison. Several validation approaches that can work on the real data without ground truths are specially designed. Experimental results on human body in vivo cardiac data demonstrate the significance of accurate CF estimation for SinMod, and validate the effectiveness of RACE in facilitating the motion estimation performance of SinMod. Copyright © 2014 Elsevier Inc. All rights reserved.

Plant responses to increasing CO2 reduce estimates of climate impacts on drought severity.

PubMed

Swann, Abigail L S; Hoffman, Forrest M; Koven, Charles D; Randerson, James T

2016-09-06

Rising atmospheric CO2 will make Earth warmer, and many studies have inferred that this warming will cause droughts to become more widespread and severe. However, rising atmospheric CO2 also modifies stomatal conductance and plant water use, processes that are often are overlooked in impact analysis. We find that plant physiological responses to CO2 reduce predictions of future drought stress, and that this reduction is captured by using plant-centric rather than atmosphere-centric metrics from Earth system models (ESMs). The atmosphere-centric Palmer Drought Severity Index predicts future increases in drought stress for more than 70% of global land area. This area drops to 37% with the use of precipitation minus evapotranspiration (P-E), a measure that represents the water flux available to downstream ecosystems and humans. The two metrics yield consistent estimates of increasing stress in regions where precipitation decreases are more robust (southern North America, northeastern South America, and southern Europe). The metrics produce diverging estimates elsewhere, with P-E predicting decreasing stress across temperate Asia and central Africa. The differing sensitivity of drought metrics to radiative and physiological aspects of increasing CO2 partly explains the divergent estimates of future drought reported in recent studies. Further, use of ESM output in offline models may double-count plant feedbacks on relative humidity and other surface variables, leading to overestimates of future stress. The use of drought metrics that account for the response of plant transpiration to changing CO2, including direct use of P-E and soil moisture from ESMs, is needed to reduce uncertainties in future assessment.

Plant responses to increasing CO2 reduce estimates of climate impacts on drought severity

PubMed Central

Koven, Charles D.; Randerson, James T.

2016-01-01

Rising atmospheric CO2 will make Earth warmer, and many studies have inferred that this warming will cause droughts to become more widespread and severe. However, rising atmospheric CO2 also modifies stomatal conductance and plant water use, processes that are often are overlooked in impact analysis. We find that plant physiological responses to CO2 reduce predictions of future drought stress, and that this reduction is captured by using plant-centric rather than atmosphere-centric metrics from Earth system models (ESMs). The atmosphere-centric Palmer Drought Severity Index predicts future increases in drought stress for more than 70% of global land area. This area drops to 37% with the use of precipitation minus evapotranspiration (P-E), a measure that represents the water flux available to downstream ecosystems and humans. The two metrics yield consistent estimates of increasing stress in regions where precipitation decreases are more robust (southern North America, northeastern South America, and southern Europe). The metrics produce diverging estimates elsewhere, with P-E predicting decreasing stress across temperate Asia and central Africa. The differing sensitivity of drought metrics to radiative and physiological aspects of increasing CO2 partly explains the divergent estimates of future drought reported in recent studies. Further, use of ESM output in offline models may double-count plant feedbacks on relative humidity and other surface variables, leading to overestimates of future stress. The use of drought metrics that account for the response of plant transpiration to changing CO2, including direct use of P-E and soil moisture from ESMs, is needed to reduce uncertainties in future assessment. PMID:27573831

Robust Parallel Motion Estimation and Mapping with Stereo Cameras in Underground Infrastructure

NASA Astrophysics Data System (ADS)

Liu, Chun; Li, Zhengning; Zhou, Yuan

2016-06-01

Presently, we developed a novel robust motion estimation method for localization and mapping in underground infrastructure using a pre-calibrated rigid stereo camera rig. Localization and mapping in underground infrastructure is important to safety. Yet it's also nontrivial since most underground infrastructures have poor lighting condition and featureless structure. Overcoming these difficulties, we discovered that parallel system is more efficient than the EKF-based SLAM approach since parallel system divides motion estimation and 3D mapping tasks into separate threads, eliminating data-association problem which is quite an issue in SLAM. Moreover, the motion estimation thread takes the advantage of state-of-art robust visual odometry algorithm which is highly functional under low illumination and provides accurate pose information. We designed and built an unmanned vehicle and used the vehicle to collect a dataset in an underground garage. The parallel system was evaluated by the actual dataset. Motion estimation results indicated a relative position error of 0.3%, and 3D mapping results showed a mean position error of 13cm. Off-line process reduced position error to 2cm. Performance evaluation by actual dataset showed that our system is capable of robust motion estimation and accurate 3D mapping in poor illumination and featureless underground environment.

The 'robust' capture-recapture design allows components of recruitment to be estimated

USGS Publications Warehouse

Pollock, K.H.; Kendall, W.L.; Nichols, J.D.; Lebreton, J.-D.; North, P.M.

1993-01-01

The 'robust' capture-recapture design (Pollock 1982) allows analyses which combine features of closed population model analyses (Otis et aI., 1978, White et aI., 1982) and open population model analyses (Pollock et aI., 1990). Estimators obtained under these analyses are more robust to unequal catch ability than traditional Jolly-Seber estimators (Pollock, 1982; Pollock et al., 1990; Kendall, 1992). The robust design also allows estimation of parameters for population size, survival rate and recruitment numbers for all periods of the study unlike under Jolly-Seber type models. The major advantage of this design that we emphasize in this short review paper is that it allows separate estimation of immigration and in situ recruitment numbers for a two or more age class model (Nichols and Pollock, 1990). This is contrasted with the age-dependent Jolly-Seber model (Pollock, 1981; Stokes, 1984; Pollock et L, 1990) which provides separate estimates for immigration and in situ recruitment for all but the first two age classes where there is at least a three age class model. The ability to achieve this separation of recruitment components can be very important to population modelers and wildlife managers as many species can only be separated into two easily identified age classes in the field.

Presence-absence surveys of prey and their use in predicting leopard (Panthera pardus) densities: a case study from Armenia.

PubMed

Khorozyan, Igor G; Malkhasyan, Alexander G; Abramov, Alexei V

2008-12-01

It is important to predict how many individuals of a predator species can survive in a given area on the basis of prey sufficiency and to compare predictive estimates with actual numbers to understand whether or not key threats are related to prey availability. Rugged terrain and low detection probabilities do not allow for the use of traditional prey count techniques in mountain areas. We used presence-absence occupancy modeling and camera-trapping to estimate the abundance and densities of prey species and regression analysis to predict leopard (Panthera pardus) densities from estimated prey biomass in the mountains of the Nuvadi area, Meghri Ridge, southern Armenia. The prey densities were 12.94 ± 2.18 individuals km(-2) for the bezoar goat (Capra aegagrus), 6.88 ± 1.56 for the wild boar (Sus scrofa) and 0.44 ± 0.20 for the roe deer (Capreolus capreolus). The detection probability of the prey was a strong function of the activity patterns, and was highest in diurnal bezoar goats (0.59 ± 0.09). Based on robust regression, the estimated total ungulate prey biomass (720.37 ± 142.72 kg km(-2) ) can support a leopard density of 7. 18 ± 3.06 individuals 100 km(-2) . The actual leopard density is only 0.34 individuals 100 km(-2) (i.e. one subadult male recorded over the 296.9 km(2) ), estimated from tracking and camera-trapping. The most plausible explanation for this discrepancy between predicted and actual leopard density is that poaching and disturbance caused by livestock breeding, plant gathering, deforestation and human-induced wild fires are affecting the leopard population in Armenia. © 2008 ISZS, Blackwell Publishing and IOZ/CAS.

Improving Aquatic Warbler Population Assessments by Accounting for Imperfect Detection

PubMed Central

Oppel, Steffen; Marczakiewicz, Piotr; Lachmann, Lars; Grzywaczewski, Grzegorz

2014-01-01

Monitoring programs designed to assess changes in population size over time need to account for imperfect detection and provide estimates of precision around annual abundance estimates. Especially for species dependent on conservation management, robust monitoring is essential to evaluate the effectiveness of management. Many bird species of temperate grasslands depend on specific conservation management to maintain suitable breeding habitat. One such species is the Aquatic Warbler (Acrocephalus paludicola), which breeds in open fen mires in Central Europe. Aquatic Warbler populations have so far been assessed using a complete survey that aims to enumerate all singing males over a large area. Because this approach provides no estimate of precision and does not account for observation error, detecting moderate population changes is challenging. From 2011 to 2013 we trialled a new line transect sampling monitoring design in the Biebrza valley, Poland, to estimate abundance of singing male Aquatic Warblers. We surveyed Aquatic Warblers repeatedly along 50 randomly placed 1-km transects, and used binomial mixture models to estimate abundances per transect. The repeated line transect sampling required 150 observer days, and thus less effort than the traditional ‘full count’ approach (175 observer days). Aquatic Warbler abundance was highest at intermediate water levels, and detection probability varied between years and was influenced by vegetation height. A power analysis indicated that our line transect sampling design had a power of 68% to detect a 20% population change over 10 years, whereas raw count data had a 9% power to detect the same trend. Thus, by accounting for imperfect detection we increased the power to detect population changes. We recommend to adopt the repeated line transect sampling approach for monitoring Aquatic Warblers in Poland and in other important breeding areas to monitor changes in population size and the effects of habitat management. PMID:24713994

Transforming geographic scale: a comparison of combined population and areal weighting to other interpolation methods.

PubMed

Hallisey, Elaine; Tai, Eric; Berens, Andrew; Wilt, Grete; Peipins, Lucy; Lewis, Brian; Graham, Shannon; Flanagan, Barry; Lunsford, Natasha Buchanan

2017-08-07

Transforming spatial data from one scale to another is a challenge in geographic analysis. As part of a larger, primary study to determine a possible association between travel barriers to pediatric cancer facilities and adolescent cancer mortality across the United States, we examined methods to estimate mortality within zones at varying distances from these facilities: (1) geographic centroid assignment, (2) population-weighted centroid assignment, (3) simple areal weighting, (4) combined population and areal weighting, and (5) geostatistical areal interpolation. For the primary study, we used county mortality counts from the National Center for Health Statistics (NCHS) and population data by census tract for the United States to estimate zone mortality. In this paper, to evaluate the five mortality estimation methods, we employed address-level mortality data from the state of Georgia in conjunction with census data. Our objective here is to identify the simplest method that returns accurate mortality estimates. The distribution of Georgia county adolescent cancer mortality counts mirrors the Poisson distribution of the NCHS counts for the U.S. Likewise, zone value patterns, along with the error measures of hierarchy and fit, are similar for the state and the nation. Therefore, Georgia data are suitable for methods testing. The mean absolute value arithmetic differences between the observed counts for Georgia and the five methods were 5.50, 5.00, 4.17, 2.74, and 3.43, respectively. Comparing the methods through paired t-tests of absolute value arithmetic differences showed no statistical difference among the methods. However, we found a strong positive correlation (r = 0.63) between estimated Georgia mortality rates and combined weighting rates at zone level. Most importantly, Bland-Altman plots indicated acceptable agreement between paired arithmetic differences of Georgia rates and combined population and areal weighting rates. This research contributes to the literature on areal interpolation, demonstrating that combined population and areal weighting, compared to other tested methods, returns the most accurate estimates of mortality in transforming small counts by county to aggregated counts for large, non-standard study zones. This conceptually simple cartographic method should be of interest to public health practitioners and researchers limited to analysis of data for relatively large enumeration units.

Hankin and Reeves' approach to estimating fish abundance in small streams: Limitations and alternatives

USGS Publications Warehouse

Thompson, W.L.

2003-01-01

Hankin and Reeves' (1988) approach to estimating fish abundance in small streams has been applied in stream fish studies across North America. However, their population estimator relies on two key assumptions: (1) removal estimates are equal to the true numbers of fish, and (2) removal estimates are highly correlated with snorkel counts within a subset of sampled stream units. Violations of these assumptions may produce suspect results. To determine possible sources of the assumption violations, I used data on the abundance of steelhead Oncorhynchus mykiss from Hankin and Reeves' (1988) in a simulation composed of 50,000 repeated, stratified systematic random samples from a spatially clustered distribution. The simulation was used to investigate effects of a range of removal estimates, from 75% to 100% of true fish abundance, on overall stream fish population estimates. The effects of various categories of removal-estimates-to-snorkel-count correlation levels (r = 0.75-1.0) on fish population estimates were also explored. Simulation results indicated that Hankin and Reeves' approach may produce poor results unless removal estimates exceed at least 85% of the true number of fish within sampled units and unless correlations between removal estimates and snorkel counts are at least 0.90. A potential modification to Hankin and Reeves' approach is the inclusion of environmental covariates that affect detection rates of fish into the removal model or other mark-recapture model. A potential alternative approach is to use snorkeling combined with line transect sampling to estimate fish densities within stream units. As with any method of population estimation, a pilot study should be conducted to evaluate its usefulness, which requires a known (or nearly so) population of fish to serve as a benchmark for evaluating bias and precision of estimators.

Estimation and correction of visibility bias in aerial surveys of wintering ducks

USGS Publications Warehouse

Pearse, A.T.; Gerard, P.D.; Dinsmore, S.J.; Kaminski, R.M.; Reinecke, K.J.

2008-01-01

Incomplete detection of all individuals leading to negative bias in abundance estimates is a pervasive source of error in aerial surveys of wildlife, and correcting that bias is a critical step in improving surveys. We conducted experiments using duck decoys as surrogates for live ducks to estimate bias associated with surveys of wintering ducks in Mississippi, USA. We found detection of decoy groups was related to wetland cover type (open vs. forested), group size (1?100 decoys), and interaction of these variables. Observers who detected decoy groups reported counts that averaged 78% of the decoys actually present, and this counting bias was not influenced by either covariate cited above. We integrated this sightability model into estimation procedures for our sample surveys with weight adjustments derived from probabilities of group detection (estimated by logistic regression) and count bias. To estimate variances of abundance estimates, we used bootstrap resampling of transects included in aerial surveys and data from the bias-correction experiment. When we implemented bias correction procedures on data from a field survey conducted in January 2004, we found bias-corrected estimates of abundance increased 36?42%, and associated standard errors increased 38?55%, depending on species or group estimated. We deemed our method successful for integrating correction of visibility bias in an existing sample survey design for wintering ducks in Mississippi, and we believe this procedure could be implemented in a variety of sampling problems for other locations and species.

RnaSeqSampleSize: real data based sample size estimation for RNA sequencing.

PubMed

Zhao, Shilin; Li, Chung-I; Guo, Yan; Sheng, Quanhu; Shyr, Yu

2018-05-30

One of the most important and often neglected components of a successful RNA sequencing (RNA-Seq) experiment is sample size estimation. A few negative binomial model-based methods have been developed to estimate sample size based on the parameters of a single gene. However, thousands of genes are quantified and tested for differential expression simultaneously in RNA-Seq experiments. Thus, additional issues should be carefully addressed, including the false discovery rate for multiple statistic tests, widely distributed read counts and dispersions for different genes. To solve these issues, we developed a sample size and power estimation method named RnaSeqSampleSize, based on the distributions of gene average read counts and dispersions estimated from real RNA-seq data. Datasets from previous, similar experiments such as the Cancer Genome Atlas (TCGA) can be used as a point of reference. Read counts and their dispersions were estimated from the reference's distribution; using that information, we estimated and summarized the power and sample size. RnaSeqSampleSize is implemented in R language and can be installed from Bioconductor website. A user friendly web graphic interface is provided at http://cqs.mc.vanderbilt.edu/shiny/RnaSeqSampleSize/ . RnaSeqSampleSize provides a convenient and powerful way for power and sample size estimation for an RNAseq experiment. It is also equipped with several unique features, including estimation for interested genes or pathway, power curve visualization, and parameter optimization.

Simulated fissioning of uranium and testing of the fission-track dating method

USGS Publications Warehouse

McGee, V.E.; Johnson, N.M.; Naeser, C.W.

1985-01-01

A computer program (FTD-SIM) faithfully simulates the fissioning of 238U with time and 235U with neutron dose. The simulation is based on first principles of physics where the fissioning of 238U with the flux of time is described by Ns = ??f 238Ut and the fissioning of 235U with the fluence of neutrons is described by Ni = ??235U??. The Poisson law is used to set the stochastic variation of fissioning within the uranium population. The life history of a given crystal can thus be traced under an infinite variety of age and irradiation conditions. A single dating attempt or up to 500 dating attempts on a given crystal population can be simulated by specifying the age of the crystal population, the size and variation in the areas to be counted, the amount and distribution of uranium, the neutron dose to be used and its variation, and the desired ratio of 238U to 235U. A variety of probability distributions can be applied to uranium and counting-area. The Price and Walker age equation is used to estimate age. The output of FTD-SIM includes the tabulated results of each individual dating attempt (sample) on demand and/or the summary statistics and histograms for multiple dating attempts (samples) including the sampling age. An analysis of the results from FTD-SIM shows that: (1) The external detector method is intrinsically more precise than the population method. (2) For the external detector method a correlation between spontaneous track count, Ns, and induced track count, Ni, results when the population of grains has a stochastic uranium content and/or when the counting areas between grains are stochastic. For the population method no correlation can exist. (3) In the external detector method the sampling distribution of age is independent of the number of grains counted. In the population method the sampling distribution of age is highly dependent on the number of grains counted. (4) Grains with zero-track counts, either in Ns or Ni, are in integral part of fissioning theory and under certain circumstances must be included in any estimate of age. (5) In estimating standard error of age the standard error of Ns and Ni and ?? must be accurately estimated and propagated through the age equation. Several statistical models are presently available to do so. ?? 1985.

Sample Size and Allocation of Effort in Point Count Sampling of Birds in Bottomland Hardwood Forests

Treesearch

Winston P. Smith; Daniel J. Twedt; Robert J. Cooper; David A. Wiedenfeld; Paul B. Hamel; Robert P. Ford

1995-01-01

To examine sample size requirements and optimum allocation of effort in point count sampling of bottomland hardwood forests, we computed minimum sample sizes from variation recorded during 82 point counts (May 7-May 16, 1992) from three localities containing three habitat types across three regions of the Mississippi Alluvial Valley (MAV). Also, we estimated the effect...

Predicting defoliation by the gypsy moth using egg mass counts and a helper variable

Treesearch

Michael E. Montgomery

1991-01-01

Traditionally, counts of egg masses have been used to predict defoliation by the gypsy moth. Regardless of the method and precision used to obtain the counts, estimates of egg mass density alone often do not provide satisfactory predictions of defoliation. Although defoliation levels greater than 50% are seldom observed if egg mass densities are less than 600 per...

Problem Solvers: Problem--Counting Is for the Birds and Solutions--Multiplication along the Silk Road

ERIC Educational Resources Information Center

Jones, Carolyn M.

2010-01-01

Connecting mathematical thinking to the natural world can be as simple as looking up to the sky. Volunteer bird watchers around the world help scientists gather data about bird populations. Counting flying birds might inspire new estimation methods, such as counting the number of birds per unit of time and then timing the whole flock's flight. In…

A random sampling approach for robust estimation of tissue-to-plasma ratio from extremely sparse data.

PubMed

Chu, Hui-May; Ette, Ene I

2005-09-02

his study was performed to develop a new nonparametric approach for the estimation of robust tissue-to-plasma ratio from extremely sparsely sampled paired data (ie, one sample each from plasma and tissue per subject). Tissue-to-plasma ratio was estimated from paired/unpaired experimental data using independent time points approach, area under the curve (AUC) values calculated with the naïve data averaging approach, and AUC values calculated using sampling based approaches (eg, the pseudoprofile-based bootstrap [PpbB] approach and the random sampling approach [our proposed approach]). The random sampling approach involves the use of a 2-phase algorithm. The convergence of the sampling/resampling approaches was investigated, as well as the robustness of the estimates produced by different approaches. To evaluate the latter, new data sets were generated by introducing outlier(s) into the real data set. One to 2 concentration values were inflated by 10% to 40% from their original values to produce the outliers. Tissue-to-plasma ratios computed using the independent time points approach varied between 0 and 50 across time points. The ratio obtained from AUC values acquired using the naive data averaging approach was not associated with any measure of uncertainty or variability. Calculating the ratio without regard to pairing yielded poorer estimates. The random sampling and pseudoprofile-based bootstrap approaches yielded tissue-to-plasma ratios with uncertainty and variability. However, the random sampling approach, because of the 2-phase nature of its algorithm, yielded more robust estimates and required fewer replications. Therefore, a 2-phase random sampling approach is proposed for the robust estimation of tissue-to-plasma ratio from extremely sparsely sampled data.

Genetic parameters of infectious bovine keratoconjunctivitis and its relationship with weight and parasite infestations in Australian tropical Bos taurus cattle.

PubMed

Ali, Abdirahman A; O'Neill, Christopher J; Thomson, Peter C; Kadarmideen, Haja N

2012-07-27

Infectious bovine keratoconjunctivitis (IBK) or 'pinkeye' is an economically important ocular disease that significantly impacts animal performance. Genetic parameters for IBK infection and its genetic and phenotypic correlations with cattle tick counts, number of helminth (unspecified species) eggs per gram of faeces and growth traits in Australian tropically adapted Bos taurus cattle were estimated. Animals were clinically examined for the presence of IBK infection before and after weaning when the calves were 3 to 6 months and 15 to 18 months old, respectively and were also recorded for tick counts, helminth eggs counts as an indicator of intestinal parasites and live weights at several ages including 18 months. Negative genetic correlations were estimated between IBK incidence and weight traits for animals in pre-weaning and post-weaning datasets. Genetic correlations among weight measurements were positive, with moderate to high values. Genetic correlations of IBK incidence with tick counts were positive for the pre-weaning and negative for the post-weaning datasets but negative with helminth eggs counts for the pre-weaning dataset and slightly positive for the post-weaning dataset. Genetic correlations between tick and helminth eggs counts were moderate and positive for both datasets. Phenotypic correlations of IBK incidence with helminth eggs per gram of faeces were moderate and positive for both datasets, but were close to zero for both datasets with tick counts. Our results suggest that genetic selection against IBK incidence in tropical cattle is feasible and that calves genetically prone to acquire IBK infection could also be genetically prone to have a slower growth. The positive genetic correlations among weight traits and between tick and helminth eggs counts suggest that they are controlled by common genes (with pleiotropic effects). Genetic correlations between IBK incidence and tick and helminth egg counts were moderate and opposite between pre-weaning and post-weaning datasets, suggesting that the environmental and (or) maternal effects differ between these two growth phases. This preliminary study provides estimated genetic parameters for IBK incidence, which could be used to design selection and breeding programs for tropical adaptation in beef cattle.

Impact on life expectancy of HIV-1 positive individuals of CD4+ cell count and viral load response to antiretroviral therapy

PubMed Central

May, Margaret T.; Gompels, Mark; Delpech, Valerie; Porter, Kholoud; Orkin, Chloe; Kegg, Stephen; Hay, Phillip; Johnson, Margaret; Palfreeman, Adrian; Gilson, Richard; Chadwick, David; Martin, Fabiola; Hill, Teresa; Walsh, John; Post, Frank; Fisher, Martin; Ainsworth, Jonathan; Jose, Sophie; Leen, Clifford; Nelson, Mark; Anderson, Jane; Sabin, Caroline

2014-01-01

Objective: The objective of this study is to estimate life expectancies of HIV-positive patients conditional on response to antiretroviral therapy (ART). Methods: Patients aged more than 20 years who started ART during 2000–2010 (excluding IDU) in HIV clinics contributing to the UK CHIC Study were followed for mortality until 2012. We determined the latest CD4+ cell count and viral load before ART and in each of years 1–5 of ART. For each duration of ART, life tables based on estimated mortality rates by sex, age, latest CD4+ cell count and viral suppression (HIV-1 RNA <400 copies/ml), were used to estimate expected age at death for ages 20–85 years. Results: Of 21 388 patients who started ART, 961 (4.5%) died during 110 697 person-years. At start of ART, expected age at death [95% confidence interval (CI)] of 35-year-old men with CD4+ cell count less than 200, 200–349, at least 350 cells/μl was 71 (68–73), 78 (74–82) and 77 (72–81) years, respectively, compared with 78 years for men in the general UK population. Thirty-five-year-old men who increased their CD4+ cell count in the first year of ART from less than 200 to 200–349 or at least 350 cells/μl and achieved viral suppression gained 7 and 10 years, respectively. After 5 years on ART, expected age at death of 35-year-old men varied from 54 (48–61) (CD4+ cell count <200 cells/μl and no viral suppression) to 80 (76–83) years (CD4+ cell count ≥350 cells/μl and viral suppression). Conclusion: Successfully treated HIV-positive individuals have a normal life expectancy. Patients who started ART with a low CD4+ cell count significantly improve their life expectancy if they have a good CD4+ cell count response and undetectable viral load. PMID:24556869

Genetic parameters of infectious bovine keratoconjunctivitis and its relationship with weight and parasite infestations in Australian tropical Bos taurus cattle

PubMed Central

2012-01-01

Background Infectious bovine keratoconjunctivitis (IBK) or ‘pinkeye’ is an economically important ocular disease that significantly impacts animal performance. Genetic parameters for IBK infection and its genetic and phenotypic correlations with cattle tick counts, number of helminth (unspecified species) eggs per gram of faeces and growth traits in Australian tropically adapted Bos taurus cattle were estimated. Methods Animals were clinically examined for the presence of IBK infection before and after weaning when the calves were 3 to 6 months and 15 to 18 months old, respectively and were also recorded for tick counts, helminth eggs counts as an indicator of intestinal parasites and live weights at several ages including 18 months. Results Negative genetic correlations were estimated between IBK incidence and weight traits for animals in pre-weaning and post-weaning datasets. Genetic correlations among weight measurements were positive, with moderate to high values. Genetic correlations of IBK incidence with tick counts were positive for the pre-weaning and negative for the post-weaning datasets but negative with helminth eggs counts for the pre-weaning dataset and slightly positive for the post-weaning dataset. Genetic correlations between tick and helminth eggs counts were moderate and positive for both datasets. Phenotypic correlations of IBK incidence with helminth eggs per gram of faeces were moderate and positive for both datasets, but were close to zero for both datasets with tick counts. Conclusions Our results suggest that genetic selection against IBK incidence in tropical cattle is feasible and that calves genetically prone to acquire IBK infection could also be genetically prone to have a slower growth. The positive genetic correlations among weight traits and between tick and helminth eggs counts suggest that they are controlled by common genes (with pleiotropic effects). Genetic correlations between IBK incidence and tick and helminth egg counts were moderate and opposite between pre-weaning and post-weaning datasets, suggesting that the environmental and (or) maternal effects differ between these two growth phases. This preliminary study provides estimated genetic parameters for IBK incidence, which could be used to design selection and breeding programs for tropical adaptation in beef cattle. PMID:22839739

Background Conditions for the October 29, 2003 Solar Flare by the AVS-F Apparatus Data

NASA Astrophysics Data System (ADS)

Arkhangelskaja, I. V.; Arkhangelskiy, A. I.; Lyapin, A. R.; Troitskaya, E. V.

The background model for AVS-F apparatus onboard CORONAS-F satellite for the October 29, 2003 X10-class solar flare is discussed in the presented work. This background model developed for AVS-F counts rate in the low- and high-energy spectral ranges in both individual channels and summarized. Count rate were approximated by polynomials of high order taking into account the mean count rate in the geomagnetic equatorial region at the different orbits parts and Kp-index averaged on 5 bins in time interval from -24 to -12 hours before the time of geomagnetic equator passing. The observed averaged counts rate on equator in the region of geomagnetic latitude ±5o and estimated minimum count rate values are in coincidence within statistical errors for all selected orbits parts used for background modeling. This model will used to refine the estimated energy of registered during the solar flare spectral features and detailed analysis of their temporal profiles behavior both in corresponding energy bands and in summarized energy range.

Logistic regression for dichotomized counts.

PubMed

Preisser, John S; Das, Kalyan; Benecha, Habtamu; Stamm, John W

2016-12-01

Sometimes there is interest in a dichotomized outcome indicating whether a count variable is positive or zero. Under this scenario, the application of ordinary logistic regression may result in efficiency loss, which is quantifiable under an assumed model for the counts. In such situations, a shared-parameter hurdle model is investigated for more efficient estimation of regression parameters relating to overall effects of covariates on the dichotomous outcome, while handling count data with many zeroes. One model part provides a logistic regression containing marginal log odds ratio effects of primary interest, while an ancillary model part describes the mean count of a Poisson or negative binomial process in terms of nuisance regression parameters. Asymptotic efficiency of the logistic model parameter estimators of the two-part models is evaluated with respect to ordinary logistic regression. Simulations are used to assess the properties of the models with respect to power and Type I error, the latter investigated under both misspecified and correctly specified models. The methods are applied to data from a randomized clinical trial of three toothpaste formulations to prevent incident dental caries in a large population of Scottish schoolchildren. © The Author(s) 2014.

Block Volume Estimation from the Discontinuity Spacing Measurements of Mesozoic Limestone Quarries, Karaburun Peninsula, Turkey

PubMed Central

Elci, Hakan; Turk, Necdet

2014-01-01

Block volumes are generally estimated by analyzing the discontinuity spacing measurements obtained either from the scan lines placed over the rock exposures or the borehole cores. Discontinuity spacing measurements made at the Mesozoic limestone quarries in Karaburun Peninsula were used to estimate the average block volumes that could be produced from them using the suggested methods in the literature. The Block Quality Designation (BQD) ratio method proposed by the authors has been found to have given in the same order of the rock block volume to the volumetric joint count (J v) method. Moreover, dimensions of the 2378 blocks produced between the years of 2009 and 2011 in the working quarries have been recorded. Assuming, that each block surfaces is a discontinuity, the mean block volume (V b), the mean volumetric joint count (J vb) and the mean block shape factor of the blocks are determined and compared with the estimated mean in situ block volumes (V in) and volumetric joint count (J vi) values estimated from the in situ discontinuity measurements. The established relations are presented as a chart to be used in practice for estimating the mean volume of blocks that can be obtained from a quarry site by analyzing the rock mass discontinuity spacing measurements. PMID:24696642

Decoding and modelling of time series count data using Poisson hidden Markov model and Markov ordinal logistic regression models.

PubMed

Sebastian, Tunny; Jeyaseelan, Visalakshi; Jeyaseelan, Lakshmanan; Anandan, Shalini; George, Sebastian; Bangdiwala, Shrikant I

2018-01-01

Hidden Markov models are stochastic models in which the observations are assumed to follow a mixture distribution, but the parameters of the components are governed by a Markov chain which is unobservable. The issues related to the estimation of Poisson-hidden Markov models in which the observations are coming from mixture of Poisson distributions and the parameters of the component Poisson distributions are governed by an m-state Markov chain with an unknown transition probability matrix are explained here. These methods were applied to the data on Vibrio cholerae counts reported every month for 11-year span at Christian Medical College, Vellore, India. Using Viterbi algorithm, the best estimate of the state sequence was obtained and hence the transition probability matrix. The mean passage time between the states were estimated. The 95% confidence interval for the mean passage time was estimated via Monte Carlo simulation. The three hidden states of the estimated Markov chain are labelled as 'Low', 'Moderate' and 'High' with the mean counts of 1.4, 6.6 and 20.2 and the estimated average duration of stay of 3, 3 and 4 months, respectively. Environmental risk factors were studied using Markov ordinal logistic regression analysis. No significant association was found between disease severity levels and climate components.

Block volume estimation from the discontinuity spacing measurements of mesozoic limestone quarries, Karaburun Peninsula, Turkey.

PubMed

Elci, Hakan; Turk, Necdet

2014-01-01

Block volumes are generally estimated by analyzing the discontinuity spacing measurements obtained either from the scan lines placed over the rock exposures or the borehole cores. Discontinuity spacing measurements made at the Mesozoic limestone quarries in Karaburun Peninsula were used to estimate the average block volumes that could be produced from them using the suggested methods in the literature. The Block Quality Designation (BQD) ratio method proposed by the authors has been found to have given in the same order of the rock block volume to the volumetric joint count (J(v)) method. Moreover, dimensions of the 2378 blocks produced between the years of 2009 and 2011 in the working quarries have been recorded. Assuming, that each block surfaces is a discontinuity, the mean block volume (V(b)), the mean volumetric joint count (J(vb)) and the mean block shape factor of the blocks are determined and compared with the estimated mean in situ block volumes (V(in)) and volumetric joint count (J(vi)) values estimated from the in situ discontinuity measurements. The established relations are presented as a chart to be used in practice for estimating the mean volume of blocks that can be obtained from a quarry site by analyzing the rock mass discontinuity spacing measurements.

Point counts of landbirds in bottomland hardwood forests of the Mississippi Alluvial Valley: How long and how many?

USGS Publications Warehouse

Smith, W.P.; Wiedenfeld, D.A.; Hanel, P.B.; Twedt, D.J.; Ford, R.P.; Cooper, R.J.; Smith, Winston Paul

1993-01-01

To quantify efficacy of point count sampling in bottomland hardwood forests, we examined the influence of point count duration on corresponding estimates of number of individuals and species recorded. To accomplish this we conducted a totalof 82 point counts 7 May-16 May 1992distributed among three habitats (Wet, Mesic, Dry) in each of three regions within the lower Mississippi Alluvial Valley (MAV). Each point count consisted of recording the number of individual birds (all species) seen or heard during the initial three minutes and per each minute thereafter for a period totaling ten minutes. In addition, we included 384 point counts recorded during an 8-week period in each of 3 years (1985-1987) among 56 randomly-selected forest patches within the bottomlands of western Tennessee. Each point count consisted of recording the number of individuals (excluding migrating species) during each of four, 5 minute intervals for a period totaling 20 minutes. To estimate minimum sample size, we determined sampling variation at each level (region, habitat, and locality) with the 82 point counts from the lower (MAV) and applied the procedures of Neter and Wasserman (1974:493; Applied linear statistical models). Neither the cumulative number of individuals nor number of species per sampling interval attained an asymptote after 10 or 20 minutes of sampling. For western Tennessee bottomlands, total individual and species counts relative to point count duration were similar among years and comparable to the pattern observed throughout the lower MAV. Across the MAV, we recorded a total of 1,62 1 birds distributed among 52 species with the majority (8721/1621) representing 8 species. More birds were recorded within 25-50 m than in either of the other distance categories. There was significant variation in numbers of individuals and species among point counts. For both, significant differences between region and patch (nested within region) occurred; neither habitat nor interaction between habitat and region was significant. For = 0.05 and L3 = 0.10, minimum sample size estimates (per factor level) varied by orders of magnitude depending upon the observed or specified range of desired detectable difference. For observed regional variation, 20 and 40 point counts were required to accommodate variability in total birds (MSE = 9.28) and species (MSE = 3.79), respectively; 25 percent of the mean could be achieved with 5 counts per factor level. Corresponding sample sizes required to detect differences of rarer species (e.g., Wood Thrush) were 500; for common species (e.g., Northern Cardinal) this same level of precision could be achieved with 100 counts.

Physical Activity Assessment with the ActiGraph GT3X and Doubly Labeled Water.

PubMed

Chomistek, Andrea K; Yuan, Changzheng; Matthews, Charles E; Troiano, Richard P; Bowles, Heather R; Rood, Jennifer; Barnett, Junaidah B; Willett, Walter C; Rimm, Eric B; Bassett, David R

2017-09-01

To compare the degree to which four accelerometer metrics-total activity counts per day (TAC per day), steps per day (steps per day), physical activity energy expenditure (PAEE) (kcal·kg·d), and moderate- to vigorous-intensity physical activity (MVPA) (min·d)-were correlated with PAEE measured by doubly labeled water (DLW). Additionally, accelerometer metrics based on vertical axis counts and triaxial counts were compared. This analysis included 684 women and 611 men age 43 to 83 yr. Participants wore the Actigraph GT3X on the hip for 7 d twice during the study and the average of the two measurements was used. Each participant also completed one DLW measurement, with a subset having a repeat. PAEE was estimated by subtracting resting metabolic rate and the thermic effect of food from total daily energy expenditure estimated by DLW. Partial Spearman correlations were used to estimate associations between PAEE and each accelerometer metric. Correlations between the accelerometer metrics and DLW-determined PAEE were higher for triaxial counts than vertical axis counts. After adjusting for weight, age, accelerometer wear time, and fat free mass, the correlation between TAC per day based on triaxial counts and DLW-determined PAEE was 0.44 in women and 0.41 in men. Correlations for steps per day and accelerometer-estimated PAEE with DLW-determined PAEE were similar. After adjustment for within-person variation in DLW-determined PAEE, the correlations for TAC per day increased to 0.61 and 0.49, respectively. Correlations between MVPA and DLW-determined PAEE were lower, particularly for modified bouts of ≥10 min. Accelerometer measures that represent total activity volume, including TAC per day, steps per day, and PAEE, were more highly correlated with DLW-determined PAEE than MVPA using traditional thresholds and should be considered by researchers seeking to reduce accelerometer data to a single metric.

The piecewise-linear dynamic attenuator reduces the impact of count rate loss with photon-counting detectors

NASA Astrophysics Data System (ADS)

Hsieh, Scott S.; Pelc, Norbert J.

2014-06-01

Photon counting x-ray detectors (PCXDs) offer several advantages compared to standard energy-integrating x-ray detectors, but also face significant challenges. One key challenge is the high count rates required in CT. At high count rates, PCXDs exhibit count rate loss and show reduced detective quantum efficiency in signal-rich (or high flux) measurements. In order to reduce count rate requirements, a dynamic beam-shaping filter can be used to redistribute flux incident on the patient. We study the piecewise-linear attenuator in conjunction with PCXDs without energy discrimination capabilities. We examined three detector models: the classic nonparalyzable and paralyzable detector models, and a ‘hybrid’ detector model which is a weighted average of the two which approximates an existing, real detector (Taguchi et al 2011 Med. Phys. 38 1089-102 ). We derive analytic expressions for the variance of the CT measurements for these detectors. These expressions are used with raw data estimated from DICOM image files of an abdomen and a thorax to estimate variance in reconstructed images for both the dynamic attenuator and a static beam-shaping (‘bowtie’) filter. By redistributing flux, the dynamic attenuator reduces dose by 40% without increasing peak variance for the ideal detector. For non-ideal PCXDs, the impact of count rate loss is also reduced. The nonparalyzable detector shows little impact from count rate loss, but with the paralyzable model, count rate loss leads to noise streaks that can be controlled with the dynamic attenuator. With the hybrid model, the characteristic count rates required before noise streaks dominate the reconstruction are reduced by a factor of 2 to 3. We conclude that the piecewise-linear attenuator can reduce the count rate requirements of the PCXD in addition to improving dose efficiency. The magnitude of this reduction depends on the detector, with paralyzable detectors showing much greater benefit than nonparalyzable detectors.

Estimating abundance while accounting for rarity, correlated behavior, and other sources of variation in counts

USGS Publications Warehouse

Dorazio, Robert M.; Martin, Juulien; Edwards, Holly H.

2013-01-01

The class of N-mixture models allows abundance to be estimated from repeated, point count surveys while adjusting for imperfect detection of individuals. We developed an extension of N-mixture models to account for two commonly observed phenomena in point count surveys: rarity and lack of independence induced by unmeasurable sources of variation in the detectability of individuals. Rarity increases the number of locations with zero detections in excess of those expected under simple models of abundance (e.g., Poisson or negative binomial). Correlated behavior of individuals and other phenomena, though difficult to measure, increases the variation in detection probabilities among surveys. Our extension of N-mixture models includes a hurdle model of abundance and a beta-binomial model of detectability that accounts for additional (extra-binomial) sources of variation in detections among surveys. As an illustration, we fit this model to repeated point counts of the West Indian manatee, which was observed in a pilot study using aerial surveys. Our extension of N-mixture models provides increased flexibility. The effects of different sets of covariates may be estimated for the probability of occurrence of a species, for its mean abundance at occupied locations, and for its detectability.

Estimating abundance while accounting for rarity, correlated behavior, and other sources of variation in counts.

PubMed

Dorazio, Robert M; Martin, Julien; Edwards, Holly H

2013-07-01

The class of N-mixture models allows abundance to be estimated from repeated, point count surveys while adjusting for imperfect detection of individuals. We developed an extension of N-mixture models to account for two commonly observed phenomena in point count surveys: rarity and lack of independence induced by unmeasurable sources of variation in the detectability of individuals. Rarity increases the number of locations with zero detections in excess of those expected under simple models of abundance (e.g., Poisson or negative binomial). Correlated behavior of individuals and other phenomena, though difficult to measure, increases the variation in detection probabilities among surveys. Our extension of N-mixture models includes a hurdle model of abundance and a beta-binomial model of detectability that accounts for additional (extra-binomial) sources of variation in detections among surveys. As an illustration, we fit this model to repeated point counts of the West Indian manatee, which was observed in a pilot study using aerial surveys. Our extension of N-mixture models provides increased flexibility. The effects of different sets of covariates may be estimated for the probability of occurrence of a species, for its mean abundance at occupied locations, and for its detectability.

Tailoring point counts for inference about avian density: dealing with nondetection and availability

USGS Publications Warehouse

Johnson, Fred A.; Dorazio, Robert M.; Castellón, Traci D.; Martin, Julien; Garcia, Jay O.; Nichols, James D.

2014-01-01

Point counts are commonly used for bird surveys, but interpretation is ambiguous unless there is an accounting for the imperfect detection of individuals. We show how repeated point counts, supplemented by observation distances, can account for two aspects of the counting process: (1) detection of birds conditional on being available for observation and (2) the availability of birds for detection given presence. We propose a hierarchical model that permits the radius in which birds are available for detection to vary with forest stand age (or other relevant habitat features), so that the number of birds available at each location is described by a Poisson-gamma mixture. Conditional on availability, the number of birds detected at each location is modeled by a beta-binomial distribution. We fit this model to repeated point count data of Florida scrub-jays and found evidence that the area in which birds were available for detection decreased with increasing stand age. Estimated density was 0.083 (95%CI: 0.060–0.113) scrub-jays/ha. Point counts of birds have a number of appealing features. Based on our findings, however, an accounting for both components of the counting process may be necessary to ensure that abundance estimates are comparable across time and space. Our approach could easily be adapted to other species and habitats.

OpenCFU, a New Free and Open-Source Software to Count Cell Colonies and Other Circular Objects

PubMed Central

Geissmann, Quentin

2013-01-01

Counting circular objects such as cell colonies is an important source of information for biologists. Although this task is often time-consuming and subjective, it is still predominantly performed manually. The aim of the present work is to provide a new tool to enumerate circular objects from digital pictures and video streams. Here, I demonstrate that the created program, OpenCFU, is very robust, accurate and fast. In addition, it provides control over the processing parameters and is implemented in an intuitive and modern interface. OpenCFU is a cross-platform and open-source software freely available at http://opencfu.sourceforge.net. PMID:23457446

Visual Estimation of Bacterial Growth Level in Microfluidic Culture Systems.

PubMed

Kim, Kyukwang; Kim, Seunggyu; Jeon, Jessie S

2018-02-03

Microfluidic devices are an emerging platform for a variety of experiments involving bacterial cell culture, and has advantages including cost and convenience. One inevitable step during bacterial cell culture is the measurement of cell concentration in the channel. The optical density measurement technique is generally used for bacterial growth estimation, but it is not applicable to microfluidic devices due to the small sample volumes in microfluidics. Alternately, cell counting or colony-forming unit methods may be applied, but these do not work in situ; nor do these methods show measurement results immediately. To this end, we present a new vision-based method to estimate the growth level of the bacteria in microfluidic channels. We use Fast Fourier transform (FFT) to detect the frequency level change of the microscopic image, focusing on the fact that the microscopic image becomes rough as the number of cells in the field of view increases, adding high frequencies to the spectrum of the image. Two types of microfluidic devices are used to culture bacteria in liquid and agar gel medium, and time-lapsed images are captured. The images obtained are analyzed using FFT, resulting in an increase in high-frequency noise proportional to the time passed. Furthermore, we apply the developed method in the microfluidic antibiotics susceptibility test by recognizing the regional concentration change of the bacteria that are cultured in the antibiotics gradient. Finally, a deep learning-based data regression is performed on the data obtained by the proposed vision-based method for robust reporting of data.

Doubly Robust Additive Hazards Models to Estimate Effects of a Continuous Exposure on Survival.

PubMed

Wang, Yan; Lee, Mihye; Liu, Pengfei; Shi, Liuhua; Yu, Zhi; Abu Awad, Yara; Zanobetti, Antonella; Schwartz, Joel D

2017-11-01

The effect of an exposure on survival can be biased when the regression model is misspecified. Hazard difference is easier to use in risk assessment than hazard ratio and has a clearer interpretation in the assessment of effect modifications. We proposed two doubly robust additive hazards models to estimate the causal hazard difference of a continuous exposure on survival. The first model is an inverse probability-weighted additive hazards regression. The second model is an extension of the doubly robust estimator for binary exposures by categorizing the continuous exposure. We compared these with the marginal structural model and outcome regression with correct and incorrect model specifications using simulations. We applied doubly robust additive hazard models to the estimation of hazard difference of long-term exposure to PM2.5 (particulate matter with an aerodynamic diameter less than or equal to 2.5 microns) on survival using a large cohort of 13 million older adults residing in seven states of the Southeastern United States. We showed that the proposed approaches are doubly robust. We found that each 1 μg m increase in annual PM2.5 exposure was associated with a causal hazard difference in mortality of 8.0 × 10 (95% confidence interval 7.4 × 10, 8.7 × 10), which was modified by age, medical history, socioeconomic status, and urbanicity. The overall hazard difference translates to approximately 5.5 (5.1, 6.0) thousand deaths per year in the study population. The proposed approaches improve the robustness of the additive hazards model and produce a novel additive causal estimate of PM2.5 on survival and several additive effect modifications, including social inequality.

Tools of Robustness for Item Response Theory.

ERIC Educational Resources Information Center

Jones, Douglas H.

This paper briefly demonstrates a few of the possibilities of a systematic application of robustness theory, concentrating on the estimation of ability when the true item response model does and does not fit the data. The definition of the maximum likelihood estimator (MLE) of ability is briefly reviewed. After introducing the notion of…

Model Uncertainty and Robustness: A Computational Framework for Multimodel Analysis

ERIC Educational Resources Information Center

Young, Cristobal; Holsteen, Katherine

2017-01-01

Model uncertainty is pervasive in social science. A key question is how robust empirical results are to sensible changes in model specification. We present a new approach and applied statistical software for computational multimodel analysis. Our approach proceeds in two steps: First, we estimate the modeling distribution of estimates across all…

The Robustness of LISREL Estimates in Structural Equation Models with Categorical Variables.

ERIC Educational Resources Information Center

Ethington, Corinna A.

This study examined the effect of type of correlation matrix on the robustness of LISREL maximum likelihood and unweighted least squares structural parameter estimates for models with categorical manifest variables. Two types of correlation matrices were analyzed; one containing Pearson product-moment correlations and one containing tetrachoric,…

Sliding Mode Approaches for Robust Control, State Estimation, Secure Communication, and Fault Diagnosis in Nuclear Systems

NASA Astrophysics Data System (ADS)

Ablay, Gunyaz

Using traditional control methods for controller design, parameter estimation and fault diagnosis may lead to poor results with nuclear systems in practice because of approximations and uncertainties in the system models used, possibly resulting in unexpected plant unavailability. This experience has led to an interest in development of robust control, estimation and fault diagnosis methods. One particularly robust approach is the sliding mode control methodology. Sliding mode approaches have been of great interest and importance in industry and engineering in the recent decades due to their potential for producing economic, safe and reliable designs. In order to utilize these advantages, sliding mode approaches are implemented for robust control, state estimation, secure communication and fault diagnosis in nuclear plant systems. In addition, a sliding mode output observer is developed for fault diagnosis in dynamical systems. To validate the effectiveness of the methodologies, several nuclear plant system models are considered for applications, including point reactor kinetics, xenon concentration dynamics, an uncertain pressurizer model, a U-tube steam generator model and a coupled nonlinear nuclear reactor model.

Statistical robustness of machine-learning estimates for characterizing a groundwater-surface water system, Southland, New Zealand

NASA Astrophysics Data System (ADS)

Friedel, M. J.; Daughney, C.

2016-12-01

The development of a successful surface-groundwater management strategy depends on the quality of data provided for analysis. This study evaluates the statistical robustness when using a modified self-organizing map (MSOM) technique to estimate missing values for three hypersurface models: synoptic groundwater-surface water hydrochemistry, time-series of groundwater-surface water hydrochemistry, and mixed-survey (combination of groundwater-surface water hydrochemistry and lithologies) hydrostratigraphic unit data. These models of increasing complexity are developed and validated based on observations from the Southland region of New Zealand. In each case, the estimation method is sufficiently robust to cope with groundwater-surface water hydrochemistry vagaries due to sample size and extreme data insufficiency, even when >80% of the data are missing. The estimation of surface water hydrochemistry time series values enabled the evaluation of seasonal variation, and the imputation of lithologies facilitated the evaluation of hydrostratigraphic controls on groundwater-surface water interaction. The robust statistical results for groundwater-surface water models of increasing data complexity provide justification to apply the MSOM technique in other regions of New Zealand and abroad.

Robust mislabel logistic regression without modeling mislabel probabilities.

PubMed

Hung, Hung; Jou, Zhi-Yu; Huang, Su-Yun

2018-03-01

Logistic regression is among the most widely used statistical methods for linear discriminant analysis. In many applications, we only observe possibly mislabeled responses. Fitting a conventional logistic regression can then lead to biased estimation. One common resolution is to fit a mislabel logistic regression model, which takes into consideration of mislabeled responses. Another common method is to adopt a robust M-estimation by down-weighting suspected instances. In this work, we propose a new robust mislabel logistic regression based on γ-divergence. Our proposal possesses two advantageous features: (1) It does not need to model the mislabel probabilities. (2) The minimum γ-divergence estimation leads to a weighted estimating equation without the need to include any bias correction term, that is, it is automatically bias-corrected. These features make the proposed γ-logistic regression more robust in model fitting and more intuitive for model interpretation through a simple weighting scheme. Our method is also easy to implement, and two types of algorithms are included. Simulation studies and the Pima data application are presented to demonstrate the performance of γ-logistic regression. © 2017, The International Biometric Society.

Genetic basis of differences in myxospore count between whirling disease-resistant and -susceptible strains of rainbow trout

USGS Publications Warehouse

Fetherman, Eric R.; Winkelman, Dana L.; Schisler, George J.; Antolin, Michael F.

2012-01-01

We used a quantitative genetics approach and estimated broad sense heritability (h2b) of myxospore count and the number of genes involved in myxospore formation to gain a better understanding of how resistance to Myxobolus cerebralis, the parasite responsible for whirling disease, is inherited in rainbow trout Oncorhynchus mykiss. An M. cerebralis-resistant strain of rainbow trout, the German Rainbow (GR), and a wild, susceptible strain of rainbow trout, the Colorado River Rainbow (CRR), were spawned to create 3 intermediate crossed populations (an F1 cross, F2 intercross, and a B2 backcross between the F1 and the CRR). Within each strain or cross, h2b was estimated from the between-family variance of myxospore counts using full-sibling families. Estimates of h2b and average myxospore counts were lowest in the GR strain, F1 cross, and F2 intercross (h2b = 0.34, 0.42, and 0.34; myxospores fish−1 = 275, 9566, and 45780, respectively), and highest in the B2 backcross and CRR strain (h2b = 0.93 and 0.89; myxospores fish−1 = 97865 and 187595, respectively). Comparison of means and a joint-scaling test suggest that resistance alleles arising from the GR strain are dominant to susceptible alleles from the CRR strain. Resistance was retained in the intermediate crosses but decreased as filial generation number increased (F2) or backcrossing occurred (B2). The estimated number of segregating loci responsible for differences in myxospore count in the parental strains was 9 ± 5. Our results indicate that resistance to M. cerebralis is a heritable trait within these populations and would respond to either artificial selection in hatcheries or natural selection in the wild.

Receptor binding assay for paralytic shellfish poisoning toxins: optimization and interlaboratory comparison.

PubMed

Ruberu, Shryamalie R; Liu, Yun-Gang; Wong, Carolyn T; Perera, S Kusum; Langlois, Gregg W; Doucette, Gregory J; Powell, Christine L

2003-01-01

A receptor binding assay (RBA) for detection of paralytic shellfish poisoning (PSP) toxins was formatted for use in a high throughput detection system using microplate scintillation counting. The RBA technology was transferred from the National Ocean Service, which uses a Wallac TriLux 1450 MicroBeta microplate scintillation counter, to the California Department of Health Services, which uses a Packard TopCount scintillation counter. Due to differences in the detector arrangement between these 2 counters, markedly different counting efficiencies were exhibited, requiring optimization of the RBA protocol for the TopCount instrument. Precision, accuracy, and sensitivity [limit of detection = 0.2 microg saxitoxin (STX) equiv/100 g shellfish tissue] of the modified protocol were equivalent to those of the original protocol. The RBA robustness and adaptability were demonstrated by an interlaboratory study, in which STX concentrations in shellfish generated by the TopCount were consistent with MicroBeta-derived values. Comparison of STX reference standards obtained from the U.S. Food and Drug Administration and the National Research Council, Canada, showed no observable differences. This study confirms the RBA's value as a rapid, high throughput screen prior to testing by the conventional mouse bioassay (MBA) and its suitability for providing an early warning of increasing PSP toxicity when toxin levels are below the MBA limit of detection.

Does the covariance structure matter in longitudinal modelling for the prediction of future CD4 counts?

PubMed

Taylor, J M; Law, N

1998-10-30

We investigate the importance of the assumed covariance structure for longitudinal modelling of CD4 counts. We examine how individual predictions of future CD4 counts are affected by the covariance structure. We consider four covariance structures: one based on an integrated Ornstein-Uhlenbeck stochastic process; one based on Brownian motion, and two derived from standard linear and quadratic random-effects models. Using data from the Multicenter AIDS Cohort Study and from a simulation study, we show that there is a noticeable deterioration in the coverage rate of confidence intervals if we assume the wrong covariance. There is also a loss in efficiency. The quadratic random-effects model is found to be the best in terms of correctly calibrated prediction intervals, but is substantially less efficient than the others. Incorrectly specifying the covariance structure as linear random effects gives too narrow prediction intervals with poor coverage rates. Fitting using the model based on the integrated Ornstein-Uhlenbeck stochastic process is the preferred one of the four considered because of its efficiency and robustness properties. We also use the difference between the future predicted and observed CD4 counts to assess an appropriate transformation of CD4 counts; a fourth root, cube root and square root all appear reasonable choices.

CNV-CH: A Convex Hull Based Segmentation Approach to Detect Copy Number Variations (CNV) Using Next-Generation Sequencing Data

PubMed Central

De, Rajat K.

2015-01-01

Copy number variation (CNV) is a form of structural alteration in the mammalian DNA sequence, which are associated with many complex neurological diseases as well as cancer. The development of next generation sequencing (NGS) technology provides us a new dimension towards detection of genomic locations with copy number variations. Here we develop an algorithm for detecting CNVs, which is based on depth of coverage data generated by NGS technology. In this work, we have used a novel way to represent the read count data as a two dimensional geometrical point. A key aspect of detecting the regions with CNVs, is to devise a proper segmentation algorithm that will distinguish the genomic locations having a significant difference in read count data. We have designed a new segmentation approach in this context, using convex hull algorithm on the geometrical representation of read count data. To our knowledge, most algorithms have used a single distribution model of read count data, but here in our approach, we have considered the read count data to follow two different distribution models independently, which adds to the robustness of detection of CNVs. In addition, our algorithm calls CNVs based on the multiple sample analysis approach resulting in a low false discovery rate with high precision. PMID:26291322

CNV-CH: A Convex Hull Based Segmentation Approach to Detect Copy Number Variations (CNV) Using Next-Generation Sequencing Data.

PubMed

Sinha, Rituparna; Samaddar, Sandip; De, Rajat K

2015-01-01

Copy number variation (CNV) is a form of structural alteration in the mammalian DNA sequence, which are associated with many complex neurological diseases as well as cancer. The development of next generation sequencing (NGS) technology provides us a new dimension towards detection of genomic locations with copy number variations. Here we develop an algorithm for detecting CNVs, which is based on depth of coverage data generated by NGS technology. In this work, we have used a novel way to represent the read count data as a two dimensional geometrical point. A key aspect of detecting the regions with CNVs, is to devise a proper segmentation algorithm that will distinguish the genomic locations having a significant difference in read count data. We have designed a new segmentation approach in this context, using convex hull algorithm on the geometrical representation of read count data. To our knowledge, most algorithms have used a single distribution model of read count data, but here in our approach, we have considered the read count data to follow two different distribution models independently, which adds to the robustness of detection of CNVs. In addition, our algorithm calls CNVs based on the multiple sample analysis approach resulting in a low false discovery rate with high precision.

Quantifying the causal effects of 20mph zones on road casualties in London via doubly robust estimation.

PubMed

Li, Haojie; Graham, Daniel J

2016-08-01

This paper estimates the causal effect of 20mph zones on road casualties in London. Potential confounders in the key relationship of interest are included within outcome regression and propensity score models, and the models are then combined to form a doubly robust estimator. A total of 234 treated zones and 2844 potential control zones are included in the data sample. The propensity score model is used to select a viable control group which has common support in the covariate distributions. We compare the doubly robust estimates with those obtained using three other methods: inverse probability weighting, regression adjustment, and propensity score matching. The results indicate that 20mph zones have had a significant causal impact on road casualty reduction in both absolute and proportional terms. Copyright © 2016 Elsevier Ltd. All rights reserved.

Effects of sampling strategy, detection probability, and independence of counts on the use of point counts

USGS Publications Warehouse

Pendleton, G.W.; Ralph, C. John; Sauer, John R.; Droege, Sam

1995-01-01

Many factors affect the use of point counts for monitoring bird populations, including sampling strategies, variation in detection rates, and independence of sample points. The most commonly used sampling plans are stratified sampling, cluster sampling, and systematic sampling. Each of these might be most useful for different objectives or field situations. Variation in detection probabilities and lack of independence among sample points can bias estimates and measures of precision. All of these factors should be con-sidered when using point count methods.

Estimating the mass variance in neutron multiplicity counting-A comparison of approaches

NASA Astrophysics Data System (ADS)

Dubi, C.; Croft, S.; Favalli, A.; Ocherashvili, A.; Pedersen, B.

2017-12-01

In the standard practice of neutron multiplicity counting , the first three sampled factorial moments of the event triggered neutron count distribution are used to quantify the three main neutron source terms: the spontaneous fissile material effective mass, the relative (α , n) production and the induced fission source responsible for multiplication. This study compares three methods to quantify the statistical uncertainty of the estimated mass: the bootstrap method, propagation of variance through moments, and statistical analysis of cycle data method. Each of the three methods was implemented on a set of four different NMC measurements, held at the JRC-laboratory in Ispra, Italy, sampling four different Pu samples in a standard Plutonium Scrap Multiplicity Counter (PSMC) well counter.

Estimating the mass variance in neutron multiplicity counting $-$ A comparison of approaches

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dubi, C.; Croft, S.; Favalli, A.

In the standard practice of neutron multiplicity counting, the first three sampled factorial moments of the event triggered neutron count distribution are used to quantify the three main neutron source terms: the spontaneous fissile material effective mass, the relative (α,n) production and the induced fission source responsible for multiplication. This study compares three methods to quantify the statistical uncertainty of the estimated mass: the bootstrap method, propagation of variance through moments, and statistical analysis of cycle data method. Each of the three methods was implemented on a set of four different NMC measurements, held at the JRC-laboratory in Ispra, Italy,more » sampling four different Pu samples in a standard Plutonium Scrap Multiplicity Counter (PSMC) well counter.« less

Estimating the mass variance in neutron multiplicity counting $-$ A comparison of approaches

DOE PAGES

Dubi, C.; Croft, S.; Favalli, A.; ...

2017-09-14

In the standard practice of neutron multiplicity counting, the first three sampled factorial moments of the event triggered neutron count distribution are used to quantify the three main neutron source terms: the spontaneous fissile material effective mass, the relative (α,n) production and the induced fission source responsible for multiplication. This study compares three methods to quantify the statistical uncertainty of the estimated mass: the bootstrap method, propagation of variance through moments, and statistical analysis of cycle data method. Each of the three methods was implemented on a set of four different NMC measurements, held at the JRC-laboratory in Ispra, Italy,more » sampling four different Pu samples in a standard Plutonium Scrap Multiplicity Counter (PSMC) well counter.« less

Robust small area estimation of poverty indicators using M-quantile approach (Case study: Sub-district level in Bogor district)

NASA Astrophysics Data System (ADS)

Girinoto, Sadik, Kusman; Indahwati

2017-03-01

The National Socio-Economic Survey samples are designed to produce estimates of parameters of planned domains (provinces and districts). The estimation of unplanned domains (sub-districts and villages) has its limitation to obtain reliable direct estimates. One of the possible solutions to overcome this problem is employing small area estimation techniques. The popular choice of small area estimation is based on linear mixed models. However, such models need strong distributional assumptions and do not easy allow for outlier-robust estimation. As an alternative approach for this purpose, M-quantile regression approach to small area estimation based on modeling specific M-quantile coefficients of conditional distribution of study variable given auxiliary covariates. It obtained outlier-robust estimation from influence function of M-estimator type and also no need strong distributional assumptions. In this paper, the aim of study is to estimate the poverty indicator at sub-district level in Bogor District-West Java using M-quantile models for small area estimation. Using data taken from National Socioeconomic Survey and Villages Potential Statistics, the results provide a detailed description of pattern of incidence and intensity of poverty within Bogor district. We also compare the results with direct estimates. The results showed the framework may be preferable when direct estimate having no incidence of poverty at all in the small area.

Robust power spectral estimation for EEG data

PubMed Central

Melman, Tamar; Victor, Jonathan D.

2016-01-01

Background Typical electroencephalogram (EEG) recordings often contain substantial artifact. These artifacts, often large and intermittent, can interfere with quantification of the EEG via its power spectrum. To reduce the impact of artifact, EEG records are typically cleaned by a preprocessing stage that removes individual segments or components of the recording. However, such preprocessing can introduce bias, discard available signal, and be labor-intensive. With this motivation, we present a method that uses robust statistics to reduce dependence on preprocessing by minimizing the effect of large intermittent outliers on the spectral estimates. New method Using the multitaper method[1] as a starting point, we replaced the final step of the standard power spectrum calculation with a quantile-based estimator, and the Jackknife approach to confidence intervals with a Bayesian approach. The method is implemented in provided MATLAB modules, which extend the widely used Chronux toolbox. Results Using both simulated and human data, we show that in the presence of large intermittent outliers, the robust method produces improved estimates of the power spectrum, and that the Bayesian confidence intervals yield close-to-veridical coverage factors. Comparison to existing method The robust method, as compared to the standard method, is less affected by artifact: inclusion of outliers produces fewer changes in the shape of the power spectrum as well as in the coverage factor. Conclusion In the presence of large intermittent outliers, the robust method can reduce dependence on data preprocessing as compared to standard methods of spectral estimation. PMID:27102041

Robust power spectral estimation for EEG data.

PubMed

Melman, Tamar; Victor, Jonathan D

2016-08-01

Typical electroencephalogram (EEG) recordings often contain substantial artifact. These artifacts, often large and intermittent, can interfere with quantification of the EEG via its power spectrum. To reduce the impact of artifact, EEG records are typically cleaned by a preprocessing stage that removes individual segments or components of the recording. However, such preprocessing can introduce bias, discard available signal, and be labor-intensive. With this motivation, we present a method that uses robust statistics to reduce dependence on preprocessing by minimizing the effect of large intermittent outliers on the spectral estimates. Using the multitaper method (Thomson, 1982) as a starting point, we replaced the final step of the standard power spectrum calculation with a quantile-based estimator, and the Jackknife approach to confidence intervals with a Bayesian approach. The method is implemented in provided MATLAB modules, which extend the widely used Chronux toolbox. Using both simulated and human data, we show that in the presence of large intermittent outliers, the robust method produces improved estimates of the power spectrum, and that the Bayesian confidence intervals yield close-to-veridical coverage factors. The robust method, as compared to the standard method, is less affected by artifact: inclusion of outliers produces fewer changes in the shape of the power spectrum as well as in the coverage factor. In the presence of large intermittent outliers, the robust method can reduce dependence on data preprocessing as compared to standard methods of spectral estimation. Copyright © 2016 Elsevier B.V. All rights reserved.

A Robust and Multi-Weighted Approach to Estimating Topographically Correlated Tropospheric Delays in Radar Interferograms

PubMed Central

Zhu, Bangyan; Li, Jiancheng; Chu, Zhengwei; Tang, Wei; Wang, Bin; Li, Dawei

2016-01-01

Spatial and temporal variations in the vertical stratification of the troposphere introduce significant propagation delays in interferometric synthetic aperture radar (InSAR) observations. Observations of small amplitude surface deformations and regional subsidence rates are plagued by tropospheric delays, and strongly correlated with topographic height variations. Phase-based tropospheric correction techniques assuming a linear relationship between interferometric phase and topography have been exploited and developed, with mixed success. Producing robust estimates of tropospheric phase delay however plays a critical role in increasing the accuracy of InSAR measurements. Meanwhile, few phase-based correction methods account for the spatially variable tropospheric delay over lager study regions. Here, we present a robust and multi-weighted approach to estimate the correlation between phase and topography that is relatively insensitive to confounding processes such as regional subsidence over larger regions as well as under varying tropospheric conditions. An expanded form of robust least squares is introduced to estimate the spatially variable correlation between phase and topography by splitting the interferograms into multiple blocks. Within each block, correlation is robustly estimated from the band-filtered phase and topography. Phase-elevation ratios are multiply- weighted and extrapolated to each persistent scatter (PS) pixel. We applied the proposed method to Envisat ASAR images over the Southern California area, USA, and found that our method mitigated the atmospheric noise better than the conventional phase-based method. The corrected ground surface deformation agreed better with those measured from GPS. PMID:27420066

A Robust and Multi-Weighted Approach to Estimating Topographically Correlated Tropospheric Delays in Radar Interferograms.

PubMed

Zhu, Bangyan; Li, Jiancheng; Chu, Zhengwei; Tang, Wei; Wang, Bin; Li, Dawei

2016-07-12

Spatial and temporal variations in the vertical stratification of the troposphere introduce significant propagation delays in interferometric synthetic aperture radar (InSAR) observations. Observations of small amplitude surface deformations and regional subsidence rates are plagued by tropospheric delays, and strongly correlated with topographic height variations. Phase-based tropospheric correction techniques assuming a linear relationship between interferometric phase and topography have been exploited and developed, with mixed success. Producing robust estimates of tropospheric phase delay however plays a critical role in increasing the accuracy of InSAR measurements. Meanwhile, few phase-based correction methods account for the spatially variable tropospheric delay over lager study regions. Here, we present a robust and multi-weighted approach to estimate the correlation between phase and topography that is relatively insensitive to confounding processes such as regional subsidence over larger regions as well as under varying tropospheric conditions. An expanded form of robust least squares is introduced to estimate the spatially variable correlation between phase and topography by splitting the interferograms into multiple blocks. Within each block, correlation is robustly estimated from the band-filtered phase and topography. Phase-elevation ratios are multiply- weighted and extrapolated to each persistent scatter (PS) pixel. We applied the proposed method to Envisat ASAR images over the Southern California area, USA, and found that our method mitigated the atmospheric noise better than the conventional phase-based method. The corrected ground surface deformation agreed better with those measured from GPS.

Applying standard perikymata profiles to Pongo pygmaeus canines to estimate perikymata counts between linear enamel hypoplasias.

PubMed

O'Hara, Mackie

2017-05-01

Recently, studies have interpreted regular spacing and average number of perikymata between dental enamel defects in orangutans to reflect seasonal episodes of physiological stress. To estimate the amount of time between developmental defects (enamel hypoplasia), studies have relied on perikymata counts. Unfortunately, perikymata are frequently not continuously visible between defects, significantly reducing data sets. A method is presented here for estimating the number of perikymata between defects using standard perikymata profiles (SPP) that allow the number of perikymata between all pairs of defects across a tooth to be analyzed. The SPP method should allow the entire complement of defects to be analyzed within the context of an individual's crown formation time. The average number of perikymata were established per decile and charted to create male and female Pongo pygmaeus SPPs. The position of the beginning of each defect was recorded for lower canines from males (n = 6) and females (n = 17). The number of perikymata between defects estimated by the SPP was compared to the actual count (where perikymata were continuously visible). The number of perikymata between defects estimated by the SPPs was accurate within three perikymata and highly correlated with the actual counts, significantly increasing the number of analyzable defect pairs. SPPs allow all defect pairs to be included in studies of defect timing, not just those with continuously visible perikymata. Establishing an individual's entire complement of dental defects makes it possible to calculate the regularity (and potential seasonality) of defects. © 2017 Wiley Periodicals, Inc.

Wavelet Filtering to Reduce Conservatism in Aeroservoelastic Robust Stability Margins

NASA Technical Reports Server (NTRS)

Brenner, Marty; Lind, Rick

1998-01-01

Wavelet analysis for filtering and system identification was used to improve the estimation of aeroservoelastic stability margins. The conservatism of the robust stability margins was reduced with parametric and nonparametric time-frequency analysis of flight data in the model validation process. Nonparametric wavelet processing of data was used to reduce the effects of external desirableness and unmodeled dynamics. Parametric estimates of modal stability were also extracted using the wavelet transform. Computation of robust stability margins for stability boundary prediction depends on uncertainty descriptions derived from the data for model validation. F-18 high Alpha Research Vehicle aeroservoelastic flight test data demonstrated improved robust stability prediction by extension of the stability boundary beyond the flight regime.

Genetic parameters for ewe reproductive performance and peri-parturient fecal egg counts and their genetic relationships with lamb body weights and fecal egg counts in Katahdin sheep

USDA-ARS?s Scientific Manuscript database

This study estimated genetic parameters for ewe reproductive traits [number of lambs born (NLB) and weaned (NLW) per ewe lambing] and peri-parturient (PPR) fecal egg counts (FEC) at lambing (PPR0) and 30 d postpartum (PPR30), and their genetic relationships with lamb BW and FEC in Katahdin sheep. Th...

The economic impact of state cigarette taxes and smoke-free air policies on convenience stores.

PubMed

Huang, Jidong; Chaloupka, Frank J

2013-03-01

To investigate whether increasing state cigarette taxes and/or enacting stronger smoke-free air (SFA) policies have negative impact on convenience store density in a state, a proxy that is determined by store openings and closings, which reflects store profits. State-level business count estimates for convenience stores for 50 states and District of Columbia from 1997 to 2009 were analysed using two-way fixed effects regression techniques that control for state-specific and year-specific determinants of convenience store density. The impact of tax and SFA policies was examined using a quasi-experimental research design that exploits changes in cigarette taxes and SFA policies within a state over time. Taxes are found to be uncorrelated with the density of combined convenience stores and gas stations in a state. Taxes are positively correlated with the density of convenience stores; however, the magnitude of this correlation is small, with a 10% increase in state cigarette taxes associated with a 0.19% (p<0.05) increase in the number of convenience stores per million people in a state. State-level SFA policies do not correlate with convenience store density in a state, regardless whether gas stations were included. These results are robust across different model specifications. In addition, they are robust with regard to the inclusion/exclusion of other state-level tobacco control measures and gasoline prices. Contrary to tobacco industry and related organisations' claims, higher cigarette taxes and stronger SFA policies do not negatively affect convenience stores.

Robustness of serial clustering of extra-tropical cyclones to the choice of tracking method

NASA Astrophysics Data System (ADS)

Pinto, Joaquim G.; Ulbrich, Sven; Karremann, Melanie K.; Stephenson, David B.; Economou, Theodoros; Shaffrey, Len C.

2016-04-01

Cyclone families are a frequent synoptic weather feature in the Euro-Atlantic area in winter. Given appropriate large-scale conditions, the occurrence of such series (clusters) of storms may lead to large socio-economic impacts and cumulative losses. Recent studies analyzing Reanalysis data using single cyclone tracking methods have shown that serial clustering of cyclones occurs on both flanks and downstream regions of the North Atlantic storm track. This study explores the sensitivity of serial clustering to the choice of tracking method. With this aim, the IMILAST cyclone track database based on ERA-interim data is analysed. Clustering is estimated by the dispersion (ratio of variance to mean) of winter (DJF) cyclones passages near each grid point over the Euro-Atlantic area. Results indicate that while the general pattern of clustering is identified for all methods, there are considerable differences in detail. This can primarily be attributed to the differences in the variance of cyclone counts between the methods, which range up to one order of magnitude. Nevertheless, clustering over the Eastern North Atlantic and Western Europe can be identified for all methods and can thus be generally considered as a robust feature. The statistical links between large-scale patterns like the NAO and clustering are obtained for all methods, though with different magnitudes. We conclude that the occurrence of cyclone clustering over the Eastern North Atlantic and Western Europe is largely independent from the choice of tracking method and hence from the definition of a cyclone.

How Accurately Can We Measure Galaxy Environment at High Redshift Using Only Photometric Redshifts?

NASA Astrophysics Data System (ADS)

Florez, Jonathan; Jogee, Shardha; Sherman, Sydney; Papovich, Casey J.; Finkelstein, Steven L.; Stevans, Matthew L.; Kawinwanichakij, Lalitwadee; Ciardullo, Robin; Gronwall, Caryl; SHELA/HETDEX

2017-06-01

We use a powerful synergy of six deep photometric surveys (Herschel SPIRE, Spitzer IRAC, NEWFIRM K-band, DECam ugriz, and XMM X-ray) and a future optical spectroscopic survey (HETDEX) in the Stripe 82 field to study galaxy evolution during the 1.9 < z < 3.5 epoch when cosmic star formation and black hole activity peaked, and protoclusters began to collapse. With an area of 24 sq. degrees, a sample size of ~ 0.8 million galaxies complete in stellar mass above M* ~ 10^10 solar masses, and a comoving volume of ~ 0.45 Gpc^3, our study will allow us to make significant advancements in understanding the connection between galaxies and their respective dark matter components. In this poster, we characterize how robustly we can measure environment using only our photometric redshifts. We compare both local and large-scale measures of environment (e.g., projected two-point correlation function, projected nearest neighbor densities, and galaxy counts within some projected aperture) at different photometric redshifts to cosmological simulations in order to quantify the uncertainty in our estimates of environment. We also explore how robustly one can recover the variation of galaxy properties with environment, when using only photometric redshifts. In the era of large photometric surveys, this work has broad implications for studies addressing the impact of environment on galaxy evolution at early cosmic epochs. We acknowledge support from NSF grants AST-1614798, AST-1413652 and NSF GRFP grant DGE-1610403.

AutoCellSeg: robust automatic colony forming unit (CFU)/cell analysis using adaptive image segmentation and easy-to-use post-editing techniques.

PubMed

Khan, Arif Ul Maula; Torelli, Angelo; Wolf, Ivo; Gretz, Norbert

2018-05-08

In biological assays, automated cell/colony segmentation and counting is imperative owing to huge image sets. Problems occurring due to drifting image acquisition conditions, background noise and high variation in colony features in experiments demand a user-friendly, adaptive and robust image processing/analysis method. We present AutoCellSeg (based on MATLAB) that implements a supervised automatic and robust image segmentation method. AutoCellSeg utilizes multi-thresholding aided by a feedback-based watershed algorithm taking segmentation plausibility criteria into account. It is usable in different operation modes and intuitively enables the user to select object features interactively for supervised image segmentation method. It allows the user to correct results with a graphical interface. This publicly available tool outperforms tools like OpenCFU and CellProfiler in terms of accuracy and provides many additional useful features for end-users.

Efficient robust reconstruction of dynamic PET activity maps with radioisotope decay constraints.

PubMed

Gao, Fei; Liu, Huafeng; Shi, Pengcheng

2010-01-01

Dynamic PET imaging performs sequence of data acquisition in order to provide visualization and quantification of physiological changes in specific tissues and organs. The reconstruction of activity maps is generally the first step in dynamic PET. State space Hinfinity approaches have been proved to be a robust method for PET image reconstruction where, however, temporal constraints are not considered during the reconstruction process. In addition, the state space strategies for PET image reconstruction have been computationally prohibitive for practical usage because of the need for matrix inversion. In this paper, we present a minimax formulation of the dynamic PET imaging problem where a radioisotope decay model is employed as physics-based temporal constraints on the photon counts. Furthermore, a robust steady state Hinfinity filter is developed to significantly improve the computational efficiency with minimal loss of accuracy. Experiments are conducted on Monte Carlo simulated image sequences for quantitative analysis and validation.

Counting Penguins.

ERIC Educational Resources Information Center

Perry, Mike; Kader, Gary

1998-01-01

Presents an activity on the simplification of penguin counting by employing the basic ideas and principles of sampling to teach students to understand and recognize its role in statistical claims. Emphasizes estimation, data analysis and interpretation, and central limit theorem. Includes a list of items for classroom discussion. (ASK)

Primary Place. Math Projects That Count.

ERIC Educational Resources Information Center

Buschman, Larry; And Others

1993-01-01

Offers elementary math-centered recycling activities and ideas on transforming throwaways into valuable classroom resources. The math activities teach estimating, counting, measuring, weighing, graphing, patterning, thinking, comparing, proportion, and dimensions. The recycling ideas present ways to use pieces of trash to create educational games.…

Relationship between automated total nucleated cell count and enumeration of cells on direct smears of canine synovial fluid.

PubMed

Dusick, Allison; Young, Karen M; Muir, Peter

2014-12-01

Canine osteoarthritis is a common disorder seen in veterinary clinical practice and causes considerable morbidity in dogs as they age. Synovial fluid analysis is an important tool for diagnosis and treatment of canine joint disease and obtaining a total nucleated cell count (TNCC) is particularly important. However, the low sample volumes obtained during arthrocentesis are often insufficient for performing an automated TNCC, thereby limiting diagnostic interpretation. The aim of the present study was to investigate whether estimation of TNCC in canine synovial fluid could be achieved by performing manual cell counts on direct smears of fluid. Fifty-eight synovial fluid samples, taken by arthrocentesis from 48 dogs, were included in the study. Direct smears of synovial fluid were prepared, and hyaluronidase added before cell counts were obtained using a commercial laser-based instrument. A protocol was established to count nucleated cells in a specific region of the smear, using a serpentine counting pattern; the mean number of nucleated cells per 400 × field was then calculated. There was a positive correlation between the automated TNCC and mean manual cell count, with more variability at higher TNCC. Regression analysis was performed to estimate TNCC from manual counts. By this method, 78% of the samples were correctly predicted to fall into one of three categories (within the reference interval, mildly to moderately increased, or markedly increased) relative to the automated TNCC. Intra-observer and inter-observer agreement was good to excellent. The results of the study suggest that interpretation of canine synovial fluid samples of low volume can be aided by methodical manual counting of cells on direct smears. Copyright © 2014 Elsevier Ltd. All rights reserved.

Robust multivariate nonparametric tests for detection of two-sample location shift in clinical trials

PubMed Central

Jiang, Xuejun; Guo, Xu; Zhang, Ning; Wang, Bo

2018-01-01

This article presents and investigates performance of a series of robust multivariate nonparametric tests for detection of location shift between two multivariate samples in randomized controlled trials. The tests are built upon robust estimators of distribution locations (medians, Hodges-Lehmann estimators, and an extended U statistic) with both unscaled and scaled versions. The nonparametric tests are robust to outliers and do not assume that the two samples are drawn from multivariate normal distributions. Bootstrap and permutation approaches are introduced for determining the p-values of the proposed test statistics. Simulation studies are conducted and numerical results are reported to examine performance of the proposed statistical tests. The numerical results demonstrate that the robust multivariate nonparametric tests constructed from the Hodges-Lehmann estimators are more efficient than those based on medians and the extended U statistic. The permutation approach can provide a more stringent control of Type I error and is generally more powerful than the bootstrap procedure. The proposed robust nonparametric tests are applied to detect multivariate distributional difference between the intervention and control groups in the Thai Healthy Choices study and examine the intervention effect of a four-session motivational interviewing-based intervention developed in the study to reduce risk behaviors among youth living with HIV. PMID:29672555

Semen parameters in fertile US men: the Study for Future Families.

PubMed

Redmon, J B; Thomas, W; Ma, W; Drobnis, E Z; Sparks, A; Wang, C; Brazil, C; Overstreet, J W; Liu, F; Swan, S H

2013-11-01

Establishing reference norms for semen parameters in fertile men is important for accurate assessment, counselling and treatment of men with male factor infertility. Identifying temporal or geographic variability in semen quality also requires accurate measurement of semen parameters in well-characterized, defined populations of men. The Study for Future Families (SFF) recruited men who were partners of pregnant women attending prenatal clinics in Los Angeles CA, Minneapolis MN, Columbia MO, New York City NY and Iowa City IA. Semen samples were collected on site from 763 men (73% White, 15% Hispanic/Latino, 7% Black and 5% Asian or other ethnic group) using strict quality control and well-defined protocols. Semen volume (by weight), sperm concentration (hemacytometer) and sperm motility were measured at each centre. Sperm morphology (both WHO, 1999 strict and WHO, 1987) was determined at a central laboratory. Mean abstinence was 3.2 days. Mean (median; 5th-95th percentile) values were: semen volume, 3.9 (3.7; 1.5-6.8) mL; sperm concentration, 60 (67; 12-192) × 10(6) /mL; total sperm count 209 (240; 32-763) × 10(6) ; % motile, 51 (52; 28-67) %; and total motile sperm count, 104 (128; 14-395) × 10(6) respectively. Values for sperm morphology were 11 (10; 3-20) % and 57 (59; 38-72) % normal forms for WHO (1999) (strict) and WHO (1987) criteria respectively. Black men had significantly lower semen volume, sperm concentration and total motile sperm counts than White and Hispanic/Latino men. Semen parameters were marginally higher in men who achieved pregnancy more quickly but differences were small and not statistically significant. The SFF provides robust estimates of semen parameters in fertile men living in five different geographic locations in the US. Fertile men display wide variation in all of the semen parameters traditionally used to assess fertility potential. © 2013 American Society of Andrology and European Academy of Andrology.

A COMPREHENSIVE ANALYSIS OF UNCERTAINTIES AFFECTING THE STELLAR MASS-HALO MASS RELATION FOR 0 < z < 4

DOE Office of Scientific and Technical Information (OSTI.GOV)

Behroozi, Peter S.; Wechsler, Risa H.; Conroy, Charlie

2010-07-01

We conduct a comprehensive analysis of the relationship between central galaxies and their host dark matter halos, as characterized by the stellar mass-halo mass (SM-HM) relation, with rigorous consideration of uncertainties. Our analysis focuses on results from the abundance matching technique, which assumes that every dark matter halo or subhalo above a specific mass threshold hosts one galaxy. We provide a robust estimate of the SM-HM relation for 0 < z < 1 and discuss the quantitative effects of uncertainties in observed galaxy stellar mass functions (including stellar mass estimates and counting uncertainties), halo mass functions (including cosmology and uncertaintiesmore » from substructure), and the abundance matching technique used to link galaxies to halos (including scatter in this connection). Our analysis results in a robust estimate of the SM-HM relation and its evolution from z = 0 to z = 4. The shape and the evolution are well constrained for z < 1. The largest uncertainties at these redshifts are due to stellar mass estimates (0.25 dex uncertainty in normalization); however, failure to account for scatter in stellar masses at fixed halo mass can lead to errors of similar magnitude in the SM-HM relation for central galaxies in massive halos. We also investigate the SM-HM relation to z = 4, although the shape of the relation at higher redshifts remains fairly unconstrained when uncertainties are taken into account. We find that the integrated star formation at a given halo mass peaks at 10%-20% of available baryons for all redshifts from 0 to 4. This peak occurs at a halo mass of 7 x 10{sup 11} M{sub sun} at z = 0 and this mass increases by a factor of 5 to z = 4. At lower and higher masses, star formation is substantially less efficient, with stellar mass scaling as M{sub *} {approx} M {sup 2.3}{sub h} at low masses and M{sub *} {approx} M {sup 0.29}{sub h} at high masses. The typical stellar mass for halos with mass less than 10{sup 12} M{sub sun} has increased by 0.3-0.45 dex for halos since z {approx} 1. These results will provide a powerful tool to inform galaxy evolution models.« less

A Comprehensive Analysis of Uncertainties Affecting the Stellar Mass-Halo Mass Relation for 0

DOE Office of Scientific and Technical Information (OSTI.GOV)

Behroozi, Peter S.; Conroy, Charlie; Wechsler, Risa H.

2010-06-07

We conduct a comprehensive analysis of the relationship between central galaxies and their host dark matter halos, as characterized by the stellar mass - halo mass (SM-HM) relation, with rigorous consideration of uncertainties. Our analysis focuses on results from the abundance matching technique, which assumes that every dark matter halo or subhalo above a specific mass threshold hosts one galaxy. We provide a robust estimate of the SM-HM relation for 0 < z < 1 and discuss the quantitative effects of uncertainties in observed galaxy stellar mass functions (GSMFs) (including stellar mass estimates and counting uncertainties), halo mass functions (includingmore » cosmology and uncertainties from substructure), and the abundance matching technique used to link galaxies to halos (including scatter in this connection). Our analysis results in a robust estimate of the SM-HM relation and its evolution from z=0 to z=4. The shape and evolution are well constrained for z < 1. The largest uncertainties at these redshifts are due to stellar mass estimates (0.25 dex uncertainty in normalization); however, failure to account for scatter in stellar masses at fixed halo mass can lead to errors of similar magnitude in the SM-HM relation for central galaxies in massive halos. We also investigate the SM-HM relation to z = 4, although the shape of the relation at higher redshifts remains fairly unconstrained when uncertainties are taken into account. We find that the integrated star formation at a given halo mass peaks at 10-20% of available baryons for all redshifts from 0 to 4. This peak occurs at a halo mass of 7 x 10{sup 11} M{sub {circle_dot}} at z = 0 and this mass increases by a factor of 5 to z = 4. At lower and higher masses, star formation is substantially less efficient, with stellar mass scaling as M{sub *} {approx} M{sub h}{sup 2.3} at low masses and M{sub *} {approx} M{sub h}{sup 0.29} at high masses. The typical stellar mass for halos with mass less than 10{sup 12} M{sub {circle_dot}} has increased by 0.3-0.45 dex for halos since z {approx} 1. These results will provide a powerful tool to inform galaxy evolution models.« less

On the importance of controlling for effort in analysis of count survey data: Modeling population change from Christmas Bird Count data

USGS Publications Warehouse

Link, W.A.; Sauer, J.R.; Helbig, Andreas J.; Flade, Martin

1999-01-01

Count survey data are commonly used for estimating temporal and spatial patterns of population change. Since count surveys are not censuses, counts can be influenced by 'nuisance factors' related to the probability of detecting animals but unrelated to the actual population size. The effects of systematic changes in these factors can be confounded with patterns of population change. Thus, valid analysis of count survey data requires the identification of nuisance factors and flexible models for their effects. We illustrate using data from the Christmas Bird Count (CBC), a midwinter survey of bird populations in North America. CBC survey effort has substantially increased in recent years, suggesting that unadjusted counts may overstate population growth (or understate declines). We describe a flexible family of models for the effect of effort, that includes models in which increasing effort leads to diminishing returns in terms of the number of birds counted.

Mitosis Counting in Breast Cancer: Object-Level Interobserver Agreement and Comparison to an Automatic Method

PubMed Central

Veta, Mitko; van Diest, Paul J.; Jiwa, Mehdi; Al-Janabi, Shaimaa; Pluim, Josien P. W.

2016-01-01

Background Tumor proliferation speed, most commonly assessed by counting of mitotic figures in histological slide preparations, is an important biomarker for breast cancer. Although mitosis counting is routinely performed by pathologists, it is a tedious and subjective task with poor reproducibility, particularly among non-experts. Inter- and intraobserver reproducibility of mitosis counting can be improved when a strict protocol is defined and followed. Previous studies have examined only the agreement in terms of the mitotic count or the mitotic activity score. Studies of the observer agreement at the level of individual objects, which can provide more insight into the procedure, have not been performed thus far. Methods The development of automatic mitosis detection methods has received large interest in recent years. Automatic image analysis is viewed as a solution for the problem of subjectivity of mitosis counting by pathologists. In this paper we describe the results from an interobserver agreement study between three human observers and an automatic method, and make two unique contributions. For the first time, we present an analysis of the object-level interobserver agreement on mitosis counting. Furthermore, we train an automatic mitosis detection method that is robust with respect to staining appearance variability and compare it with the performance of expert observers on an “external” dataset, i.e. on histopathology images that originate from pathology labs other than the pathology lab that provided the training data for the automatic method. Results The object-level interobserver study revealed that pathologists often do not agree on individual objects, even if this is not reflected in the mitotic count. The disagreement is larger for objects from smaller size, which suggests that adding a size constraint in the mitosis counting protocol can improve reproducibility. The automatic mitosis detection method can perform mitosis counting in an unbiased way, with substantial agreement with human experts. PMID:27529701

Mitosis Counting in Breast Cancer: Object-Level Interobserver Agreement and Comparison to an Automatic Method.

PubMed

Veta, Mitko; van Diest, Paul J; Jiwa, Mehdi; Al-Janabi, Shaimaa; Pluim, Josien P W

2016-01-01

Tumor proliferation speed, most commonly assessed by counting of mitotic figures in histological slide preparations, is an important biomarker for breast cancer. Although mitosis counting is routinely performed by pathologists, it is a tedious and subjective task with poor reproducibility, particularly among non-experts. Inter- and intraobserver reproducibility of mitosis counting can be improved when a strict protocol is defined and followed. Previous studies have examined only the agreement in terms of the mitotic count or the mitotic activity score. Studies of the observer agreement at the level of individual objects, which can provide more insight into the procedure, have not been performed thus far. The development of automatic mitosis detection methods has received large interest in recent years. Automatic image analysis is viewed as a solution for the problem of subjectivity of mitosis counting by pathologists. In this paper we describe the results from an interobserver agreement study between three human observers and an automatic method, and make two unique contributions. For the first time, we present an analysis of the object-level interobserver agreement on mitosis counting. Furthermore, we train an automatic mitosis detection method that is robust with respect to staining appearance variability and compare it with the performance of expert observers on an "external" dataset, i.e. on histopathology images that originate from pathology labs other than the pathology lab that provided the training data for the automatic method. The object-level interobserver study revealed that pathologists often do not agree on individual objects, even if this is not reflected in the mitotic count. The disagreement is larger for objects from smaller size, which suggests that adding a size constraint in the mitosis counting protocol can improve reproducibility. The automatic mitosis detection method can perform mitosis counting in an unbiased way, with substantial agreement with human experts.

Evaluation of a method using survey counts and tag data to estimate the number of Pacific walruses (Odobenus rosmarus divergens) using a coastal haulout in northwestern Alaska

USGS Publications Warehouse

Battaile, Brian; Jay, Chadwick V.; Udevitz, Mark S.; Fischbach, Anthony S.

2017-01-01

Increased periods of sparse sea ice over the continental shelf of the Chukchi Sea in late summer have reduced offshore haulout habitat for Pacific walruses (Odobenus rosmarus divergens) and increased opportunities for human activities in the region. Knowing how many walruses could be affected by human activities would be useful to conservation decisions. Currently, there are no adequate estimates of walrus abundance in the northeastern Chukchi Sea during summer–early autumn. Estimating abundance in autumn might be possible from coastal surveys of hauled out walruses during periods when offshore sea ice is unavailable to walruses. We evaluated methods to estimate the size of the walrus population that was using a haulout on the coast of northwestern Alaska in autumn by using aerial photography to count the number of hauled out walruses (herd size) and data from 37 tagged walruses to estimate availability (proportion of population hauled out). We used two methods to estimate availability, direct proportions of hauled out tagged walruses and smoothed proportions using local polynomial regression. Point estimates of herd size (4200–38,000 walruses) and total population size (76,000–287,000 walruses) ranged widely among days and between the two methods of estimating availability. Estimates of population size were influenced most by variation in estimates of availability. Coastal surveys might be improved most by counting walruses when the greatest numbers are hauled out, thereby reducing the influence of availability on population size estimates. The chance of collecting data during peak haulout periods would be improved by conducting multiple surveys.

A randomized approach to speed up the analysis of large-scale read-count data in the application of CNV detection.

PubMed

Wang, WeiBo; Sun, Wei; Wang, Wei; Szatkiewicz, Jin

2018-03-01

The application of high-throughput sequencing in a broad range of quantitative genomic assays (e.g., DNA-seq, ChIP-seq) has created a high demand for the analysis of large-scale read-count data. Typically, the genome is divided into tiling windows and windowed read-count data is generated for the entire genome from which genomic signals are detected (e.g. copy number changes in DNA-seq, enrichment peaks in ChIP-seq). For accurate analysis of read-count data, many state-of-the-art statistical methods use generalized linear models (GLM) coupled with the negative-binomial (NB) distribution by leveraging its ability for simultaneous bias correction and signal detection. However, although statistically powerful, the GLM+NB method has a quadratic computational complexity and therefore suffers from slow running time when applied to large-scale windowed read-count data. In this study, we aimed to speed up substantially the GLM+NB method by using a randomized algorithm and we demonstrate here the utility of our approach in the application of detecting copy number variants (CNVs) using a real example. We propose an efficient estimator, the randomized GLM+NB coefficients estimator (RGE), for speeding up the GLM+NB method. RGE samples the read-count data and solves the estimation problem on a smaller scale. We first theoretically validated the consistency and the variance properties of RGE. We then applied RGE to GENSENG, a GLM+NB based method for detecting CNVs. We named the resulting method as "R-GENSENG". Based on extensive evaluation using both simulated and empirical data, we concluded that R-GENSENG is ten times faster than the original GENSENG while maintaining GENSENG's accuracy in CNV detection. Our results suggest that RGE strategy developed here could be applied to other GLM+NB based read-count analyses, i.e. ChIP-seq data analysis, to substantially improve their computational efficiency while preserving the analytic power.

Robust Means and Covariance Matrices by the Minimum Volume Ellipsoid (MVE).

ERIC Educational Resources Information Center

Blankmeyer, Eric

P. Rousseeuw and A. Leroy (1987) proposed a very robust alternative to classical estimates of mean vectors and covariance matrices, the Minimum Volume Ellipsoid (MVE). This paper describes the MVE technique and presents a BASIC program to implement it. The MVE is a "high breakdown" estimator, one that can cope with samples in which as…

Estimated Costs for Delivery of HIV Antiretroviral Therapy to Individuals with CD4+ T-Cell Counts >350 cells/uL in Rural Uganda

PubMed Central

Jain, Vivek; Chang, Wei; Byonanebye, Dathan M.; Owaraganise, Asiphas; Twinomuhwezi, Ellon; Amanyire, Gideon; Black, Douglas; Marseille, Elliot; Kamya, Moses R.; Havlir, Diane V.; Kahn, James G.

2015-01-01

Background Evidence favoring earlier HIV ART initiation at high CD4+ T-cell counts (CD4>350/uL) has grown, and guidelines now recommend earlier HIV treatment. However, the cost of providing ART to individuals with CD4>350 in Sub-Saharan Africa has not been well estimated. This remains a major barrier to optimal global cost projections for accelerating the scale-up of ART. Our objective was to compute costs of ART delivery to high CD4+count individuals in a typical rural Ugandan health center-based HIV clinic, and use these data to construct scenarios of efficient ART scale-up. Methods Within a clinical study evaluating streamlined ART delivery to 197 individuals with CD4+ cell counts >350 cells/uL (EARLI Study: NCT01479634) in Mbarara, Uganda, we performed a micro-costing analysis of administrative records, ART prices, and time-and-motion analysis of staff work patterns. We computed observed per-person-per-year (ppy) costs, and constructed models estimating costs under several increasingly efficient ART scale-up scenarios using local salaries, lowest drug prices, optimized patient loads, and inclusion of viral load (VL) testing. Findings Among 197 individuals enrolled in the EARLI Study, median pre-ART CD4+ cell count was 569/uL (IQR 451–716). Observed ART delivery cost was $628 ppy at steady state. Models using local salaries and only core laboratory tests estimated costs of $529/$445 ppy (+/-VL testing, respectively). Models with lower salaries, lowest ART prices, and optimized healthcare worker schedules reduced costs by $100–200 ppy. Costs in a maximally efficient scale-up model were $320/$236 ppy (+/- VL testing). This included $39 for personnel, $106 for ART, $130/$46 for laboratory tests, and $46 for administrative/other costs. A key limitation of this study is its derivation and extrapolation of costs from one large rural treatment program of high CD4+ count individuals. Conclusions In a Ugandan HIV clinic, ART delivery costs—including VL testing—for individuals with CD4>350 were similar to estimates from high-efficiency programs. In higher efficiency scale-up models, costs were substantially lower. These favorable costs may be achieved because high CD4+ count patients are often asymptomatic, facilitating more efficient streamlined ART delivery. Our work provides a framework for calculating costs of efficient ART scale-up models using accessible data from specific programs and regions. PMID:26632823

Estimated Costs for Delivery of HIV Antiretroviral Therapy to Individuals with CD4+ T-Cell Counts >350 cells/uL in Rural Uganda.

PubMed

Jain, Vivek; Chang, Wei; Byonanebye, Dathan M; Owaraganise, Asiphas; Twinomuhwezi, Ellon; Amanyire, Gideon; Black, Douglas; Marseille, Elliot; Kamya, Moses R; Havlir, Diane V; Kahn, James G

2015-01-01

Evidence favoring earlier HIV ART initiation at high CD4+ T-cell counts (CD4>350/uL) has grown, and guidelines now recommend earlier HIV treatment. However, the cost of providing ART to individuals with CD4>350 in Sub-Saharan Africa has not been well estimated. This remains a major barrier to optimal global cost projections for accelerating the scale-up of ART. Our objective was to compute costs of ART delivery to high CD4+count individuals in a typical rural Ugandan health center-based HIV clinic, and use these data to construct scenarios of efficient ART scale-up. Within a clinical study evaluating streamlined ART delivery to 197 individuals with CD4+ cell counts >350 cells/uL (EARLI Study: NCT01479634) in Mbarara, Uganda, we performed a micro-costing analysis of administrative records, ART prices, and time-and-motion analysis of staff work patterns. We computed observed per-person-per-year (ppy) costs, and constructed models estimating costs under several increasingly efficient ART scale-up scenarios using local salaries, lowest drug prices, optimized patient loads, and inclusion of viral load (VL) testing. Among 197 individuals enrolled in the EARLI Study, median pre-ART CD4+ cell count was 569/uL (IQR 451-716). Observed ART delivery cost was $628 ppy at steady state. Models using local salaries and only core laboratory tests estimated costs of $529/$445 ppy (+/-VL testing, respectively). Models with lower salaries, lowest ART prices, and optimized healthcare worker schedules reduced costs by $100-200 ppy. Costs in a maximally efficient scale-up model were $320/$236 ppy (+/- VL testing). This included $39 for personnel, $106 for ART, $130/$46 for laboratory tests, and $46 for administrative/other costs. A key limitation of this study is its derivation and extrapolation of costs from one large rural treatment program of high CD4+ count individuals. In a Ugandan HIV clinic, ART delivery costs--including VL testing--for individuals with CD4>350 were similar to estimates from high-efficiency programs. In higher efficiency scale-up models, costs were substantially lower. These favorable costs may be achieved because high CD4+ count patients are often asymptomatic, facilitating more efficient streamlined ART delivery. Our work provides a framework for calculating costs of efficient ART scale-up models using accessible data from specific programs and regions.

Protocol for monitoring forest-nesting birds in National Park Service parks

USGS Publications Warehouse

Dawson, Deanna K.; Efford, Murray G.

2013-01-01

These documents detail the protocol for monitoring forest-nesting birds in National Park Service parks in the National Capital Region Network (NCRN). In the first year of sampling, counts of birds should be made at 384 points on the NCRN spatially randomized grid, developed to sample terrestrial resources. Sampling should begin on or about May 20 and continue into early July; on each day the sampling period begins at sunrise and ends five hours later. Each point should be counted twice, once in the first half of the field season and once in the second half, with visits made by different observers, balancing the within-season coverage of points and their spatial coverage by observers, and allowing observer differences to be tested. Three observers, skilled in identifying birds of the region by sight and sound and with previous experience in conducting timed counts of birds, will be needed for this effort. Observers should be randomly assigned to ‘routes’ consisting of eight points, in close proximity and, ideally, in similar habitat, that can be covered in one morning. Counts are 10 minutes in length, subdivided into four 2.5-min intervals. Within each time interval, new birds (i.e., those not already detected) are recorded as within or beyond 50 m of the point, based on where first detected. Binomial distance methods are used to calculate annual estimates of density for species. The data are also amenable to estimation of abundance and detection probability via the removal method. Generalized linear models can be used to assess between-year changes in density estimates or unadjusted count data. This level of sampling is expected to be sufficient to detect a 50% decline in 10 years for approximately 50 bird species, including 14 of 19 species that are priorities for conservation efforts, if analyses are based on unadjusted count data, and for 30 species (6 priority species) if analyses are based on density estimates. The estimates of required sample sizes are based on the mean number of individuals detected per 10 minutes in available data from surveys in three NCRN parks. Once network-wide data from the first year of sampling are available, this and other aspects of the protocol should be re-assessed, and changes made as desired or necessary before the start of the second field season. Thereafter, changes should not be made to the field methods, and sampling should be conducted annually for at least ten years. NCRN staff should keep apprised of new analytical methods developed for analysis of point-count data.

Mount Rainier National Park and Olympic National Park elk monitoring program annual report 2011

USGS Publications Warehouse

Happe, Patricia J.; Reid, Mason; Griffin, Paul C.; Jenkins, Kurt J.; Vales, David J.; Moeller, Barbara J.; Tirhi, Michelle; McCorquodale, Scott

2013-01-01

Fiscal year 2011 was the first year of implementing an approved elk monitoring protocol in Mount Rainier (MORA) and Olympic (OLYM) National Parks in the North Coast and Cascades Network (NCCN) (Griffin et al. 2012). However, it was the fourth and second year of gathering data according to protocol in MORA and OLYM respectively; data gathered during the protocol development phase followed procedures that are laid out in the protocol. Elk monitoring in these large wilderness parks relies on aerial surveys from a helicopter. Summer surveys are intended to provide quantitative estimates of abundance, sex and age composition, and distribution of migratory elk in high elevation trend count areas. An unknown number of elk is not detected during surveys; however the protocol estimates the number of missed elk by applying a model that accounts for detection bias. Detection bias in elk surveys in MORA is estimated using a double-observer sightability model that was developed using survey data from 2008-2010 (Griffin et al. 2012). That model was developed using elk that were previously equipped with radio collars by cooperating tribes. At the onset of protocol development in OLYM there were no existing radio-collars on elk. Consequently the majority of the effort in OLYM in the past 4 years has been focused on capturing and radio-collaring elk and conducting sightability trials needed to develop a double-observer sightability model in OLYM. In this annual report we provide estimates of abundance and composition for MORA elk, raw counts of elk made in OLYM, and describe sightability trials conducted in OLYM. At MORA the North trend count area was surveyed twice and the South once (North Rainier herd, and South Rainier herd). We counted 373 and 267 elk during two replicate surveys of the North Rainier herd, and 535 elk in the South Rainier herd. Using the model, we estimated that 413 and 320 elk were in the North and 652 elk were in the South trend count areas during the time of the respective surveys. At OLYM, the Core and Northwest trend count areas were completely surveyed, as were portions of the Quinault. In addition, we surveyed 10 survey units specifically to get resight data. Two-hundred and forty eight elk were counted in the Core, 19 in the Northwest, and 169 in the Quinault. We conducted double-observer sightability trials associated with 14 collared elk groups for use in developing the double-observer sightability model for OLYM.

Re-constructing historical Adélie penguin abundance estimates by retrospectively accounting for detection bias.

PubMed

Southwell, Colin; Emmerson, Louise; Newbery, Kym; McKinlay, John; Kerry, Knowles; Woehler, Eric; Ensor, Paul

2015-01-01

Seabirds and other land-breeding marine predators are considered to be useful and practical indicators of the state of marine ecosystems because of their dependence on marine prey and the accessibility of their populations at breeding colonies. Historical counts of breeding populations of these higher-order marine predators are one of few data sources available for inferring past change in marine ecosystems. However, historical abundance estimates derived from these population counts may be subject to unrecognised bias and uncertainty because of variable attendance of birds at breeding colonies and variable timing of past population surveys. We retrospectively accounted for detection bias in historical abundance estimates of the colonial, land-breeding Adélie penguin through an analysis of 222 historical abundance estimates from 81 breeding sites in east Antarctica. The published abundance estimates were de-constructed to retrieve the raw count data and then re-constructed by applying contemporary adjustment factors obtained from remotely operating time-lapse cameras. The re-construction process incorporated spatial and temporal variation in phenology and attendance by using data from cameras deployed at multiple sites over multiple years and propagating this uncertainty through to the final revised abundance estimates. Our re-constructed abundance estimates were consistently higher and more uncertain than published estimates. The re-constructed estimates alter the conclusions reached for some sites in east Antarctica in recent assessments of long-term Adélie penguin population change. Our approach is applicable to abundance data for a wide range of colonial, land-breeding marine species including other penguin species, flying seabirds and marine mammals.

A robust bayesian estimate of the concordance correlation coefficient.

PubMed

Feng, Dai; Baumgartner, Richard; Svetnik, Vladimir

2015-01-01

A need for assessment of agreement arises in many situations including statistical biomarker qualification or assay or method validation. Concordance correlation coefficient (CCC) is one of the most popular scaled indices reported in evaluation of agreement. Robust methods for CCC estimation currently present an important statistical challenge. Here, we propose a novel Bayesian method of robust estimation of CCC based on multivariate Student's t-distribution and compare it with its alternatives. Furthermore, we extend the method to practically relevant settings, enabling incorporation of confounding covariates and replications. The superiority of the new approach is demonstrated using simulation as well as real datasets from biomarker application in electroencephalography (EEG). This biomarker is relevant in neuroscience for development of treatments for insomnia.

Noise robustness of a combined phase retrieval and reconstruction method for phase-contrast tomography.

PubMed

Kongskov, Rasmus Dalgas; Jørgensen, Jakob Sauer; Poulsen, Henning Friis; Hansen, Per Christian

2016-04-01

Classical reconstruction methods for phase-contrast tomography consist of two stages: phase retrieval and tomographic reconstruction. A novel algebraic method combining the two was suggested by Kostenko et al. [Opt. Express21, 12185 (2013)OPEXFF1094-408710.1364/OE.21.012185], and preliminary results demonstrated improved reconstruction compared with a given two-stage method. Using simulated free-space propagation experiments with a single sample-detector distance, we thoroughly compare the novel method with the two-stage method to address limitations of the preliminary results. We demonstrate that the novel method is substantially more robust toward noise; our simulations point to a possible reduction in counting times by an order of magnitude.

Robust logistic regression to narrow down the winner's curse for rare and recessive susceptibility variants.

PubMed

Kesselmeier, Miriam; Lorenzo Bermejo, Justo

2017-11-01

Logistic regression is the most common technique used for genetic case-control association studies. A disadvantage of standard maximum likelihood estimators of the genotype relative risk (GRR) is their strong dependence on outlier subjects, for example, patients diagnosed at unusually young age. Robust methods are available to constrain outlier influence, but they are scarcely used in genetic studies. This article provides a non-intimidating introduction to robust logistic regression, and investigates its benefits and limitations in genetic association studies. We applied the bounded Huber and extended the R package 'robustbase' with the re-descending Hampel functions to down-weight outlier influence. Computer simulations were carried out to assess the type I error rate, mean squared error (MSE) and statistical power according to major characteristics of the genetic study and investigated markers. Simulations were complemented with the analysis of real data. Both standard and robust estimation controlled type I error rates. Standard logistic regression showed the highest power but standard GRR estimates also showed the largest bias and MSE, in particular for associated rare and recessive variants. For illustration, a recessive variant with a true GRR=6.32 and a minor allele frequency=0.05 investigated in a 1000 case/1000 control study by standard logistic regression resulted in power=0.60 and MSE=16.5. The corresponding figures for Huber-based estimation were power=0.51 and MSE=0.53. Overall, Hampel- and Huber-based GRR estimates did not differ much. Robust logistic regression may represent a valuable alternative to standard maximum likelihood estimation when the focus lies on risk prediction rather than identification of susceptibility variants. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Robust state estimation for uncertain fuzzy bidirectional associative memory networks with time-varying delays

NASA Astrophysics Data System (ADS)

Vadivel, P.; Sakthivel, R.; Mathiyalagan, K.; Arunkumar, A.

2013-09-01

This paper addresses the issue of robust state estimation for a class of fuzzy bidirectional associative memory (BAM) neural networks with time-varying delays and parameter uncertainties. By constructing the Lyapunov-Krasovskii functional, which contains the triple-integral term and using the free-weighting matrix technique, a set of sufficient conditions are derived in terms of linear matrix inequalities (LMIs) to estimate the neuron states through available output measurements such that the dynamics of the estimation error system is robustly asymptotically stable. In particular, we consider a generalized activation function in which the traditional assumptions on the boundedness, monotony and differentiability of the activation functions are removed. More precisely, the design of the state estimator for such BAM neural networks can be obtained by solving some LMIs, which are dependent on the size of the time derivative of the time-varying delays. Finally, a numerical example with simulation result is given to illustrate the obtained theoretical results.

Robust estimation of partially linear models for longitudinal data with dropouts and measurement error.

PubMed

Qin, Guoyou; Zhang, Jiajia; Zhu, Zhongyi; Fung, Wing

2016-12-20

Outliers, measurement error, and missing data are commonly seen in longitudinal data because of its data collection process. However, no method can address all three of these issues simultaneously. This paper focuses on the robust estimation of partially linear models for longitudinal data with dropouts and measurement error. A new robust estimating equation, simultaneously tackling outliers, measurement error, and missingness, is proposed. The asymptotic properties of the proposed estimator are established under some regularity conditions. The proposed method is easy to implement in practice by utilizing the existing standard generalized estimating equations algorithms. The comprehensive simulation studies show the strength of the proposed method in dealing with longitudinal data with all three features. Finally, the proposed method is applied to data from the Lifestyle Education for Activity and Nutrition study and confirms the effectiveness of the intervention in producing weight loss at month 9. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Doubly robust estimation of generalized partial linear models for longitudinal data with dropouts.

PubMed

Lin, Huiming; Fu, Bo; Qin, Guoyou; Zhu, Zhongyi

2017-12-01

We develop a doubly robust estimation of generalized partial linear models for longitudinal data with dropouts. Our method extends the highly efficient aggregate unbiased estimating function approach proposed in Qu et al. (2010) to a doubly robust one in the sense that under missing at random (MAR), our estimator is consistent when either the linear conditional mean condition is satisfied or a model for the dropout process is correctly specified. We begin with a generalized linear model for the marginal mean, and then move forward to a generalized partial linear model, allowing for nonparametric covariate effect by using the regression spline smoothing approximation. We establish the asymptotic theory for the proposed method and use simulation studies to compare its finite sample performance with that of Qu's method, the complete-case generalized estimating equation (GEE) and the inverse-probability weighted GEE. The proposed method is finally illustrated using data from a longitudinal cohort study. © 2017, The International Biometric Society.

Repeated count surveys help standardize multi-agency estimates of American Oystercatcher (Haematopus palliatus) abundance

USGS Publications Warehouse

Hostetter, Nathan J.; Gardner, Beth; Schweitzer, Sara H.; Boettcher, Ruth; Wilke, Alexandra L.; Addison, Lindsay; Swilling, William R.; Pollock, Kenneth H.; Simons, Theodore R.

2015-01-01

The extensive breeding range of many shorebird species can make integration of survey data problematic at regional spatial scales. We evaluated the effectiveness of standardized repeated count surveys coordinated across 8 agencies to estimate the abundance of American Oystercatcher (Haematopus palliatus) breeding pairs in the southeastern United States. Breeding season surveys were conducted across coastal North Carolina (90 plots) and the Eastern Shore of Virginia (3 plots). Plots were visited on 1–5 occasions during April–June 2013. N-mixture models were used to estimate abundance and detection probability in relation to survey date, tide stage, plot size, and plot location (coastal bay vs. barrier island). The estimated abundance of oystercatchers in the surveyed area was 1,048 individuals (95% credible interval: 851–1,408) and 470 pairs (384–637), substantially higher than estimates that did not account for detection probability (maximum counts of 674 individuals and 316 pairs). Detection probability was influenced by a quadratic function of survey date, and increased from mid-April (~0.60) to mid-May (~0.80), then remained relatively constant through June. Detection probability was also higher during high tide than during low, rising, or falling tides. Abundance estimates from N-mixture models were validated at 13 plots by exhaustive productivity studies (2–5 surveys wk−1). Intensive productivity studies identified 78 breeding pairs across 13 productivity plots while the N-mixture model abundance estimate was 74 pairs (62–119) using only 1–5 replicated surveys season−1. Our results indicate that standardized replicated count surveys coordinated across multiple agencies and conducted during a relatively short time window (closure assumption) provide tremendous potential to meet both agency-level (e.g., state) and regional-level (e.g., flyway) objectives in large-scale shorebird monitoring programs.

Estimating the Impact of Earlier ART Initiation and Increased Testing Coverage on HIV Transmission among Men Who Have Sex with Men in Mexico using a Mathematical Model.

PubMed

Caro-Vega, Yanink; del Rio, Carlos; Lima, Viviane Dias; Lopez-Cervantes, Malaquias; Crabtree-Ramirez, Brenda; Bautista-Arredondo, Sergio; Colchero, M Arantxa; Sierra-Madero, Juan

2015-01-01

To estimate the impact of late ART initiation on HIV transmission among men who have sex with men (MSM) in Mexico. An HIV transmission model was built to estimate the number of infections transmitted by HIV-infected men who have sex with men (MSM-HIV+) MSM-HIV+ in the short and long term. Sexual risk behavior data were estimated from a nationwide study of MSM. CD4+ counts at ART initiation from a representative national cohort were used to estimate time since infection. Number of MSM-HIV+ on treatment and suppressed were estimated from surveillance and government reports. Status quo scenario (SQ), and scenarios of early ART initiation and increased HIV testing were modeled. We estimated 14239 new HIV infections per year from MSM-HIV+ in Mexico. In SQ, MSM take an average 7.4 years since infection to initiate treatment with a median CD4+ count of 148 cells/mm3(25th-75th percentiles 52-266). In SQ, 68% of MSM-HIV+ are not aware of their HIV status and transmit 78% of new infections. Increasing the CD4+ count at ART initiation to 350 cells/mm3 shortened the time since infection to 2.8 years. Increasing HIV testing to cover 80% of undiagnosed MSM resulted in a reduction of 70% in new infections in 20 years. Initiating ART at 500 cells/mm3 and increasing HIV testing the reduction would be of 75% in 20 years. A substantial number of new HIV infections in Mexico are transmitted by undiagnosed and untreated MSM-HIV+. An aggressive increase in HIV testing coverage and initiating ART at a CD4 count of 500 cells/mm3 in this population would significantly benefit individuals and decrease the number of new HIV infections in Mexico.

Skeletal Correlates for Body Mass Estimation in Modern and Fossil Flying Birds

PubMed Central

Field, Daniel J.; Lynner, Colton; Brown, Christian; Darroch, Simon A. F.

2013-01-01

Scaling relationships between skeletal dimensions and body mass in extant birds are often used to estimate body mass in fossil crown-group birds, as well as in stem-group avialans. However, useful statistical measurements for constraining the precision and accuracy of fossil mass estimates are rarely provided, which prevents the quantification of robust upper and lower bound body mass estimates for fossils. Here, we generate thirteen body mass correlations and associated measures of statistical robustness using a sample of 863 extant flying birds. By providing robust body mass regressions with upper- and lower-bound prediction intervals for individual skeletal elements, we address the longstanding problem of body mass estimation for highly fragmentary fossil birds. We demonstrate that the most precise proxy for estimating body mass in the overall dataset, measured both as coefficient determination of ordinary least squares regression and percent prediction error, is the maximum diameter of the coracoid’s humeral articulation facet (the glenoid). We further demonstrate that this result is consistent among the majority of investigated avian orders (10 out of 18). As a result, we suggest that, in the majority of cases, this proxy may provide the most accurate estimates of body mass for volant fossil birds. Additionally, by presenting statistical measurements of body mass prediction error for thirteen different body mass regressions, this study provides a much-needed quantitative framework for the accurate estimation of body mass and associated ecological correlates in fossil birds. The application of these regressions will enhance the precision and robustness of many mass-based inferences in future paleornithological studies. PMID:24312392