Sample records for variance

  1. Increasing selection response by Bayesian modeling of heterogeneous environmental variances

    USDA-ARS?s Scientific Manuscript database

    Heterogeneity of environmental variance among genotypes reduces selection response because genotypes with higher variance are more likely to be selected than low-variance genotypes. Modeling heterogeneous variances to obtain weighted means corrected for heterogeneous variances is difficult in likel...

  2. Modelling heterogeneity variances in multiple treatment comparison meta-analysis--are informative priors the better solution?

    PubMed

    Thorlund, Kristian; Thabane, Lehana; Mills, Edward J

    2013-01-11

    Multiple treatment comparison (MTC) meta-analyses are commonly modeled in a Bayesian framework, and weakly informative priors are typically preferred to mirror familiar data driven frequentist approaches. Random-effects MTCs have commonly modeled heterogeneity under the assumption that the between-trial variance for all involved treatment comparisons are equal (i.e., the 'common variance' assumption). This approach 'borrows strength' for heterogeneity estimation across treatment comparisons, and thus, ads valuable precision when data is sparse. The homogeneous variance assumption, however, is unrealistic and can severely bias variance estimates. Consequently 95% credible intervals may not retain nominal coverage, and treatment rank probabilities may become distorted. Relaxing the homogeneous variance assumption may be equally problematic due to reduced precision. To regain good precision, moderately informative variance priors or additional mathematical assumptions may be necessary. In this paper we describe four novel approaches to modeling heterogeneity variance - two novel model structures, and two approaches for use of moderately informative variance priors. We examine the relative performance of all approaches in two illustrative MTC data sets. We particularly compare between-study heterogeneity estimates and model fits, treatment effect estimates and 95% credible intervals, and treatment rank probabilities. In both data sets, use of moderately informative variance priors constructed from the pair wise meta-analysis data yielded the best model fit and narrower credible intervals. Imposing consistency equations on variance estimates, assuming variances to be exchangeable, or using empirically informed variance priors also yielded good model fits and narrow credible intervals. The homogeneous variance model yielded high precision at all times, but overall inadequate estimates of between-trial variances. Lastly, treatment rankings were similar among the novel approaches, but considerably different when compared with the homogenous variance approach. MTC models using a homogenous variance structure appear to perform sub-optimally when between-trial variances vary between comparisons. Using informative variance priors, assuming exchangeability or imposing consistency between heterogeneity variances can all ensure sufficiently reliable and realistic heterogeneity estimation, and thus more reliable MTC inferences. All four approaches should be viable candidates for replacing or supplementing the conventional homogeneous variance MTC model, which is currently the most widely used in practice.

  3. Dominance Genetic Variance for Traits Under Directional Selection in Drosophila serrata

    PubMed Central

    Sztepanacz, Jacqueline L.; Blows, Mark W.

    2015-01-01

    In contrast to our growing understanding of patterns of additive genetic variance in single- and multi-trait combinations, the relative contribution of nonadditive genetic variance, particularly dominance variance, to multivariate phenotypes is largely unknown. While mechanisms for the evolution of dominance genetic variance have been, and to some degree remain, subject to debate, the pervasiveness of dominance is widely recognized and may play a key role in several evolutionary processes. Theoretical and empirical evidence suggests that the contribution of dominance variance to phenotypic variance may increase with the correlation between a trait and fitness; however, direct tests of this hypothesis are few. Using a multigenerational breeding design in an unmanipulated population of Drosophila serrata, we estimated additive and dominance genetic covariance matrices for multivariate wing-shape phenotypes, together with a comprehensive measure of fitness, to determine whether there is an association between directional selection and dominance variance. Fitness, a trait unequivocally under directional selection, had no detectable additive genetic variance, but significant dominance genetic variance contributing 32% of the phenotypic variance. For single and multivariate morphological traits, however, no relationship was observed between trait–fitness correlations and dominance variance. A similar proportion of additive and dominance variance was found to contribute to phenotypic variance for single traits, and double the amount of additive compared to dominance variance was found for the multivariate trait combination under directional selection. These data suggest that for many fitness components a positive association between directional selection and dominance genetic variance may not be expected. PMID:25783700

  4. VARIANCE ANISOTROPY IN KINETIC PLASMAS

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

    Parashar, Tulasi N.; Matthaeus, William H.; Oughton, Sean

    Solar wind fluctuations admit well-documented anisotropies of the variance matrix, or polarization, related to the mean magnetic field direction. Typically, one finds a ratio of perpendicular variance to parallel variance of the order of 9:1 for the magnetic field. Here we study the question of whether a kinetic plasma spontaneously generates and sustains parallel variances when initiated with only perpendicular variance. We find that parallel variance grows and saturates at about 5% of the perpendicular variance in a few nonlinear times irrespective of the Reynolds number. For sufficiently large systems (Reynolds numbers) the variance approaches values consistent with the solarmore » wind observations.« less

  5. Decomposing variation in male reproductive success: age-specific variances and covariances through extra-pair and within-pair reproduction.

    PubMed

    Lebigre, Christophe; Arcese, Peter; Reid, Jane M

    2013-07-01

    Age-specific variances and covariances in reproductive success shape the total variance in lifetime reproductive success (LRS), age-specific opportunities for selection, and population demographic variance and effective size. Age-specific (co)variances in reproductive success achieved through different reproductive routes must therefore be quantified to predict population, phenotypic and evolutionary dynamics in age-structured populations. While numerous studies have quantified age-specific variation in mean reproductive success, age-specific variances and covariances in reproductive success, and the contributions of different reproductive routes to these (co)variances, have not been comprehensively quantified in natural populations. We applied 'additive' and 'independent' methods of variance decomposition to complete data describing apparent (social) and realised (genetic) age-specific reproductive success across 11 cohorts of socially monogamous but genetically polygynandrous song sparrows (Melospiza melodia). We thereby quantified age-specific (co)variances in male within-pair and extra-pair reproductive success (WPRS and EPRS) and the contributions of these (co)variances to the total variances in age-specific reproductive success and LRS. 'Additive' decomposition showed that within-age and among-age (co)variances in WPRS across males aged 2-4 years contributed most to the total variance in LRS. Age-specific (co)variances in EPRS contributed relatively little. However, extra-pair reproduction altered age-specific variances in reproductive success relative to the social mating system, and hence altered the relative contributions of age-specific reproductive success to the total variance in LRS. 'Independent' decomposition showed that the (co)variances in age-specific WPRS, EPRS and total reproductive success, and the resulting opportunities for selection, varied substantially across males that survived to each age. Furthermore, extra-pair reproduction increased the variance in age-specific reproductive success relative to the social mating system to a degree that increased across successive age classes. This comprehensive decomposition of the total variances in age-specific reproductive success and LRS into age-specific (co)variances attributable to two reproductive routes showed that within-age and among-age covariances contributed substantially to the total variance and that extra-pair reproduction can alter the (co)variance structure of age-specific reproductive success. Such covariances and impacts should consequently be integrated into theoretical assessments of demographic and evolutionary processes in age-structured populations. © 2013 The Authors. Journal of Animal Ecology © 2013 British Ecological Society.

  6. Dominance genetic variance for traits under directional selection in Drosophila serrata.

    PubMed

    Sztepanacz, Jacqueline L; Blows, Mark W

    2015-05-01

    In contrast to our growing understanding of patterns of additive genetic variance in single- and multi-trait combinations, the relative contribution of nonadditive genetic variance, particularly dominance variance, to multivariate phenotypes is largely unknown. While mechanisms for the evolution of dominance genetic variance have been, and to some degree remain, subject to debate, the pervasiveness of dominance is widely recognized and may play a key role in several evolutionary processes. Theoretical and empirical evidence suggests that the contribution of dominance variance to phenotypic variance may increase with the correlation between a trait and fitness; however, direct tests of this hypothesis are few. Using a multigenerational breeding design in an unmanipulated population of Drosophila serrata, we estimated additive and dominance genetic covariance matrices for multivariate wing-shape phenotypes, together with a comprehensive measure of fitness, to determine whether there is an association between directional selection and dominance variance. Fitness, a trait unequivocally under directional selection, had no detectable additive genetic variance, but significant dominance genetic variance contributing 32% of the phenotypic variance. For single and multivariate morphological traits, however, no relationship was observed between trait-fitness correlations and dominance variance. A similar proportion of additive and dominance variance was found to contribute to phenotypic variance for single traits, and double the amount of additive compared to dominance variance was found for the multivariate trait combination under directional selection. These data suggest that for many fitness components a positive association between directional selection and dominance genetic variance may not be expected. Copyright © 2015 by the Genetics Society of America.

  7. Modelling heterogeneity variances in multiple treatment comparison meta-analysis – Are informative priors the better solution?

    PubMed Central

    2013-01-01

    Background Multiple treatment comparison (MTC) meta-analyses are commonly modeled in a Bayesian framework, and weakly informative priors are typically preferred to mirror familiar data driven frequentist approaches. Random-effects MTCs have commonly modeled heterogeneity under the assumption that the between-trial variance for all involved treatment comparisons are equal (i.e., the ‘common variance’ assumption). This approach ‘borrows strength’ for heterogeneity estimation across treatment comparisons, and thus, ads valuable precision when data is sparse. The homogeneous variance assumption, however, is unrealistic and can severely bias variance estimates. Consequently 95% credible intervals may not retain nominal coverage, and treatment rank probabilities may become distorted. Relaxing the homogeneous variance assumption may be equally problematic due to reduced precision. To regain good precision, moderately informative variance priors or additional mathematical assumptions may be necessary. Methods In this paper we describe four novel approaches to modeling heterogeneity variance - two novel model structures, and two approaches for use of moderately informative variance priors. We examine the relative performance of all approaches in two illustrative MTC data sets. We particularly compare between-study heterogeneity estimates and model fits, treatment effect estimates and 95% credible intervals, and treatment rank probabilities. Results In both data sets, use of moderately informative variance priors constructed from the pair wise meta-analysis data yielded the best model fit and narrower credible intervals. Imposing consistency equations on variance estimates, assuming variances to be exchangeable, or using empirically informed variance priors also yielded good model fits and narrow credible intervals. The homogeneous variance model yielded high precision at all times, but overall inadequate estimates of between-trial variances. Lastly, treatment rankings were similar among the novel approaches, but considerably different when compared with the homogenous variance approach. Conclusions MTC models using a homogenous variance structure appear to perform sub-optimally when between-trial variances vary between comparisons. Using informative variance priors, assuming exchangeability or imposing consistency between heterogeneity variances can all ensure sufficiently reliable and realistic heterogeneity estimation, and thus more reliable MTC inferences. All four approaches should be viable candidates for replacing or supplementing the conventional homogeneous variance MTC model, which is currently the most widely used in practice. PMID:23311298

  8. Variance component and breeding value estimation for genetic heterogeneity of residual variance in Swedish Holstein dairy cattle.

    PubMed

    Rönnegård, L; Felleki, M; Fikse, W F; Mulder, H A; Strandberg, E

    2013-04-01

    Trait uniformity, or micro-environmental sensitivity, may be studied through individual differences in residual variance. These differences appear to be heritable, and the need exists, therefore, to fit models to predict breeding values explaining differences in residual variance. The aim of this paper is to estimate breeding values for micro-environmental sensitivity (vEBV) in milk yield and somatic cell score, and their associated variance components, on a large dairy cattle data set having more than 1.6 million records. Estimation of variance components, ordinary breeding values, and vEBV was performed using standard variance component estimation software (ASReml), applying the methodology for double hierarchical generalized linear models. Estimation using ASReml took less than 7 d on a Linux server. The genetic standard deviations for residual variance were 0.21 and 0.22 for somatic cell score and milk yield, respectively, which indicate moderate genetic variance for residual variance and imply that a standard deviation change in vEBV for one of these traits would alter the residual variance by 20%. This study shows that estimation of variance components, estimated breeding values and vEBV, is feasible for large dairy cattle data sets using standard variance component estimation software. The possibility to select for uniformity in Holstein dairy cattle based on these estimates is discussed. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  9. 10 CFR 851.30 - Consideration of variances.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... DEPARTMENT OF ENERGY WORKER SAFETY AND HEALTH PROGRAM Variances § 851.30 Consideration of variances. (a) Variances shall be granted by the Under Secretary after considering the recommendation of the Chief Health, Safety and Security Officer. The authority to grant a variance cannot be delegated. (b) The application...

  10. Spectral Ambiguity of Allan Variance

    NASA Technical Reports Server (NTRS)

    Greenhall, C. A.

    1996-01-01

    We study the extent to which knowledge of Allan variance and other finite-difference variances determines the spectrum of a random process. The variance of first differences is known to determine the spectrum. We show that, in general, the Allan variance does not. A complete description of the ambiguity is given.

  11. Portfolio optimization with skewness and kurtosis

    NASA Astrophysics Data System (ADS)

    Lam, Weng Hoe; Jaaman, Saiful Hafizah Hj.; Isa, Zaidi

    2013-04-01

    Mean and variance of return distributions are two important parameters of the mean-variance model in portfolio optimization. However, the mean-variance model will become inadequate if the returns of assets are not normally distributed. Therefore, higher moments such as skewness and kurtosis cannot be ignored. Risk averse investors prefer portfolios with high skewness and low kurtosis so that the probability of getting negative rates of return will be reduced. The objective of this study is to compare the portfolio compositions as well as performances between the mean-variance model and mean-variance-skewness-kurtosis model by using the polynomial goal programming approach. The results show that the incorporation of skewness and kurtosis will change the optimal portfolio compositions. The mean-variance-skewness-kurtosis model outperforms the mean-variance model because the mean-variance-skewness-kurtosis model takes skewness and kurtosis into consideration. Therefore, the mean-variance-skewness-kurtosis model is more appropriate for the investors of Malaysia in portfolio optimization.

  12. Previous Estimates of Mitochondrial DNA Mutation Level Variance Did Not Account for Sampling Error: Comparing the mtDNA Genetic Bottleneck in Mice and Humans

    PubMed Central

    Wonnapinij, Passorn; Chinnery, Patrick F.; Samuels, David C.

    2010-01-01

    In cases of inherited pathogenic mitochondrial DNA (mtDNA) mutations, a mother and her offspring generally have large and seemingly random differences in the amount of mutated mtDNA that they carry. Comparisons of measured mtDNA mutation level variance values have become an important issue in determining the mechanisms that cause these large random shifts in mutation level. These variance measurements have been made with samples of quite modest size, which should be a source of concern because higher-order statistics, such as variance, are poorly estimated from small sample sizes. We have developed an analysis of the standard error of variance from a sample of size n, and we have defined error bars for variance measurements based on this standard error. We calculate variance error bars for several published sets of measurements of mtDNA mutation level variance and show how the addition of the error bars alters the interpretation of these experimental results. We compare variance measurements from human clinical data and from mouse models and show that the mutation level variance is clearly higher in the human data than it is in the mouse models at both the primary oocyte and offspring stages of inheritance. We discuss how the standard error of variance can be used in the design of experiments measuring mtDNA mutation level variance. Our results show that variance measurements based on fewer than 20 measurements are generally unreliable and ideally more than 50 measurements are required to reliably compare variances with less than a 2-fold difference. PMID:20362273

  13. Turbulence Variance Characteristics in the Unstable Atmospheric Boundary Layer above Flat Pine Forest

    NASA Astrophysics Data System (ADS)

    Asanuma, Jun

    Variances of the velocity components and scalars are important as indicators of the turbulence intensity. They also can be utilized to estimate surface fluxes in several types of "variance methods", and the estimated fluxes can be regional values if the variances from which they are calculated are regionally representative measurements. On these motivations, variances measured by an aircraft in the unstable ABL over a flat pine forest during HAPEX-Mobilhy were analyzed within the context of the similarity scaling arguments. The variances of temperature and vertical velocity within the atmospheric surface layer were found to follow closely the Monin-Obukhov similarity theory, and to yield reasonable estimates of the surface sensible heat fluxes when they are used in variance methods. This gives a validation to the variance methods with aircraft measurements. On the other hand, the specific humidity variances were influenced by the surface heterogeneity and clearly fail to obey MOS. A simple analysis based on the similarity law for free convection produced a comprehensible and quantitative picture regarding the effect of the surface flux heterogeneity on the statistical moments, and revealed that variances of the active and passive scalars become dissimilar because of their different roles in turbulence. The analysis also indicated that the mean quantities are also affected by the heterogeneity but to a less extent than the variances. The temperature variances in the mixed layer (ML) were examined by using a generalized top-down bottom-up diffusion model with some combinations of velocity scales and inversion flux models. The results showed that the surface shear stress exerts considerable influence on the lower ML. Also with the temperature and vertical velocity variances ML variance methods were tested, and their feasibility was investigated. Finally, the variances in the ML were analyzed in terms of the local similarity concept; the results confirmed the original hypothesis by Panofsky and McCormick that the local scaling in terms of the local buoyancy flux defines the lower bound of the moments.

  14. 40 CFR 142.307 - What terms and conditions must be included in a small system variance?

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... improvements to comply with the small system variance technology, secure an alternative source of water, or... included in a small system variance? 142.307 Section 142.307 Protection of Environment ENVIRONMENTAL... IMPLEMENTATION Variances for Small System Review of Small System Variance Application § 142.307 What terms and...

  15. 40 CFR 142.307 - What terms and conditions must be included in a small system variance?

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... improvements to comply with the small system variance technology, secure an alternative source of water, or... included in a small system variance? 142.307 Section 142.307 Protection of Environment ENVIRONMENTAL... IMPLEMENTATION Variances for Small System Review of Small System Variance Application § 142.307 What terms and...

  16. 40 CFR 142.307 - What terms and conditions must be included in a small system variance?

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... improvements to comply with the small system variance technology, secure an alternative source of water, or... included in a small system variance? 142.307 Section 142.307 Protection of Environment ENVIRONMENTAL... IMPLEMENTATION Variances for Small System Review of Small System Variance Application § 142.307 What terms and...

  17. 40 CFR 142.307 - What terms and conditions must be included in a small system variance?

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... improvements to comply with the small system variance technology, secure an alternative source of water, or... included in a small system variance? 142.307 Section 142.307 Protection of Environment ENVIRONMENTAL... IMPLEMENTATION Variances for Small System Review of Small System Variance Application § 142.307 What terms and...

  18. flowVS: channel-specific variance stabilization in flow cytometry.

    PubMed

    Azad, Ariful; Rajwa, Bartek; Pothen, Alex

    2016-07-28

    Comparing phenotypes of heterogeneous cell populations from multiple biological conditions is at the heart of scientific discovery based on flow cytometry (FC). When the biological signal is measured by the average expression of a biomarker, standard statistical methods require that variance be approximately stabilized in populations to be compared. Since the mean and variance of a cell population are often correlated in fluorescence-based FC measurements, a preprocessing step is needed to stabilize the within-population variances. We present a variance-stabilization algorithm, called flowVS, that removes the mean-variance correlations from cell populations identified in each fluorescence channel. flowVS transforms each channel from all samples of a data set by the inverse hyperbolic sine (asinh) transformation. For each channel, the parameters of the transformation are optimally selected by Bartlett's likelihood-ratio test so that the populations attain homogeneous variances. The optimum parameters are then used to transform the corresponding channels in every sample. flowVS is therefore an explicit variance-stabilization method that stabilizes within-population variances in each channel by evaluating the homoskedasticity of clusters with a likelihood-ratio test. With two publicly available datasets, we show that flowVS removes the mean-variance dependence from raw FC data and makes the within-population variance relatively homogeneous. We demonstrate that alternative transformation techniques such as flowTrans, flowScape, logicle, and FCSTrans might not stabilize variance. Besides flow cytometry, flowVS can also be applied to stabilize variance in microarray data. With a publicly available data set we demonstrate that flowVS performs as well as the VSN software, a state-of-the-art approach developed for microarrays. The homogeneity of variance in cell populations across FC samples is desirable when extracting features uniformly and comparing cell populations with different levels of marker expressions. The newly developed flowVS algorithm solves the variance-stabilization problem in FC and microarrays by optimally transforming data with the help of Bartlett's likelihood-ratio test. On two publicly available FC datasets, flowVS stabilizes within-population variances more evenly than the available transformation and normalization techniques. flowVS-based variance stabilization can help in performing comparison and alignment of phenotypically identical cell populations across different samples. flowVS and the datasets used in this paper are publicly available in Bioconductor.

  19. Characterizing nonconstant instrumental variance in emerging miniaturized analytical techniques.

    PubMed

    Noblitt, Scott D; Berg, Kathleen E; Cate, David M; Henry, Charles S

    2016-04-07

    Measurement variance is a crucial aspect of quantitative chemical analysis. Variance directly affects important analytical figures of merit, including detection limit, quantitation limit, and confidence intervals. Most reported analyses for emerging analytical techniques implicitly assume constant variance (homoskedasticity) by using unweighted regression calibrations. Despite the assumption of constant variance, it is known that most instruments exhibit heteroskedasticity, where variance changes with signal intensity. Ignoring nonconstant variance results in suboptimal calibrations, invalid uncertainty estimates, and incorrect detection limits. Three techniques where homoskedasticity is often assumed were covered in this work to evaluate if heteroskedasticity had a significant quantitative impact-naked-eye, distance-based detection using paper-based analytical devices (PADs), cathodic stripping voltammetry (CSV) with disposable carbon-ink electrode devices, and microchip electrophoresis (MCE) with conductivity detection. Despite these techniques representing a wide range of chemistries and precision, heteroskedastic behavior was confirmed for each. The general variance forms were analyzed, and recommendations for accounting for nonconstant variance discussed. Monte Carlo simulations of instrument responses were performed to quantify the benefits of weighted regression, and the sensitivity to uncertainty in the variance function was tested. Results show that heteroskedasticity should be considered during development of new techniques; even moderate uncertainty (30%) in the variance function still results in weighted regression outperforming unweighted regressions. We recommend utilizing the power model of variance because it is easy to apply, requires little additional experimentation, and produces higher-precision results and more reliable uncertainty estimates than assuming homoskedasticity. Copyright © 2016 Elsevier B.V. All rights reserved.

  20. Variance Reduction Factor of Nuclear Data for Integral Neutronics Parameters

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

    Chiba, G., E-mail: go_chiba@eng.hokudai.ac.jp; Tsuji, M.; Narabayashi, T.

    We propose a new quantity, a variance reduction factor, to identify nuclear data for which further improvements are required to reduce uncertainties of target integral neutronics parameters. Important energy ranges can be also identified with this variance reduction factor. Variance reduction factors are calculated for several integral neutronics parameters. The usefulness of the variance reduction factors is demonstrated.

  1. Variance Assistance Document: Land Disposal Restrictions Treatability Variances and Determinations of Equivalent Treatment

    EPA Pesticide Factsheets

    This document provides assistance to those seeking to submit a variance request for LDR treatability variances and determinations of equivalent treatment regarding the hazardous waste land disposal restrictions program.

  2. A Variance Distribution Model of Surface EMG Signals Based on Inverse Gamma Distribution.

    PubMed

    Hayashi, Hideaki; Furui, Akira; Kurita, Yuichi; Tsuji, Toshio

    2017-11-01

    Objective: This paper describes the formulation of a surface electromyogram (EMG) model capable of representing the variance distribution of EMG signals. Methods: In the model, EMG signals are handled based on a Gaussian white noise process with a mean of zero for each variance value. EMG signal variance is taken as a random variable that follows inverse gamma distribution, allowing the representation of noise superimposed onto this variance. Variance distribution estimation based on marginal likelihood maximization is also outlined in this paper. The procedure can be approximated using rectified and smoothed EMG signals, thereby allowing the determination of distribution parameters in real time at low computational cost. Results: A simulation experiment was performed to evaluate the accuracy of distribution estimation using artificially generated EMG signals, with results demonstrating that the proposed model's accuracy is higher than that of maximum-likelihood-based estimation. Analysis of variance distribution using real EMG data also suggested a relationship between variance distribution and signal-dependent noise. Conclusion: The study reported here was conducted to examine the performance of a proposed surface EMG model capable of representing variance distribution and a related distribution parameter estimation method. Experiments using artificial and real EMG data demonstrated the validity of the model. Significance: Variance distribution estimated using the proposed model exhibits potential in the estimation of muscle force. Objective: This paper describes the formulation of a surface electromyogram (EMG) model capable of representing the variance distribution of EMG signals. Methods: In the model, EMG signals are handled based on a Gaussian white noise process with a mean of zero for each variance value. EMG signal variance is taken as a random variable that follows inverse gamma distribution, allowing the representation of noise superimposed onto this variance. Variance distribution estimation based on marginal likelihood maximization is also outlined in this paper. The procedure can be approximated using rectified and smoothed EMG signals, thereby allowing the determination of distribution parameters in real time at low computational cost. Results: A simulation experiment was performed to evaluate the accuracy of distribution estimation using artificially generated EMG signals, with results demonstrating that the proposed model's accuracy is higher than that of maximum-likelihood-based estimation. Analysis of variance distribution using real EMG data also suggested a relationship between variance distribution and signal-dependent noise. Conclusion: The study reported here was conducted to examine the performance of a proposed surface EMG model capable of representing variance distribution and a related distribution parameter estimation method. Experiments using artificial and real EMG data demonstrated the validity of the model. Significance: Variance distribution estimated using the proposed model exhibits potential in the estimation of muscle force.

  3. Variance-Stable R-Estimators.

    DTIC Science & Technology

    1984-05-01

    By means of the concept of change-of variance function we investigate the stability properties of the asymptotic variance of R-estimators. This allows us to construct the optimal V-robust R-estimator that minimizes the asymptotic variance at the model, under the side condition of a bounded change-of variance function. Finally, we discuss the connection between this function and an influence function for two-sample rank tests introduced by Eplett (1980). (Author)

  4. Network Structure and Biased Variance Estimation in Respondent Driven Sampling

    PubMed Central

    Verdery, Ashton M.; Mouw, Ted; Bauldry, Shawn; Mucha, Peter J.

    2015-01-01

    This paper explores bias in the estimation of sampling variance in Respondent Driven Sampling (RDS). Prior methodological work on RDS has focused on its problematic assumptions and the biases and inefficiencies of its estimators of the population mean. Nonetheless, researchers have given only slight attention to the topic of estimating sampling variance in RDS, despite the importance of variance estimation for the construction of confidence intervals and hypothesis tests. In this paper, we show that the estimators of RDS sampling variance rely on a critical assumption that the network is First Order Markov (FOM) with respect to the dependent variable of interest. We demonstrate, through intuitive examples, mathematical generalizations, and computational experiments that current RDS variance estimators will always underestimate the population sampling variance of RDS in empirical networks that do not conform to the FOM assumption. Analysis of 215 observed university and school networks from Facebook and Add Health indicates that the FOM assumption is violated in every empirical network we analyze, and that these violations lead to substantially biased RDS estimators of sampling variance. We propose and test two alternative variance estimators that show some promise for reducing biases, but which also illustrate the limits of estimating sampling variance with only partial information on the underlying population social network. PMID:26679927

  5. Evaluation of three lidar scanning strategies for turbulence measurements

    NASA Astrophysics Data System (ADS)

    Newman, J. F.; Klein, P. M.; Wharton, S.; Sathe, A.; Bonin, T. A.; Chilson, P. B.; Muschinski, A.

    2015-11-01

    Several errors occur when a traditional Doppler-beam swinging (DBS) or velocity-azimuth display (VAD) strategy is used to measure turbulence with a lidar. To mitigate some of these errors, a scanning strategy was recently developed which employs six beam positions to independently estimate the u, v, and w velocity variances and covariances. In order to assess the ability of these different scanning techniques to measure turbulence, a Halo scanning lidar, WindCube v2 pulsed lidar and ZephIR continuous wave lidar were deployed at field sites in Oklahoma and Colorado with collocated sonic anemometers. Results indicate that the six-beam strategy mitigates some of the errors caused by VAD and DBS scans, but the strategy is strongly affected by errors in the variance measured at the different beam positions. The ZephIR and WindCube lidars overestimated horizontal variance values by over 60 % under unstable conditions as a result of variance contamination, where additional variance components contaminate the true value of the variance. A correction method was developed for the WindCube lidar that uses variance calculated from the vertical beam position to reduce variance contamination in the u and v variance components. The correction method reduced WindCube variance estimates by over 20 % at both the Oklahoma and Colorado sites under unstable conditions, when variance contamination is largest. This correction method can be easily applied to other lidars that contain a vertical beam position and is a promising method for accurately estimating turbulence with commercially available lidars.

  6. Evaluation of three lidar scanning strategies for turbulence measurements

    NASA Astrophysics Data System (ADS)

    Newman, Jennifer F.; Klein, Petra M.; Wharton, Sonia; Sathe, Ameya; Bonin, Timothy A.; Chilson, Phillip B.; Muschinski, Andreas

    2016-05-01

    Several errors occur when a traditional Doppler beam swinging (DBS) or velocity-azimuth display (VAD) strategy is used to measure turbulence with a lidar. To mitigate some of these errors, a scanning strategy was recently developed which employs six beam positions to independently estimate the u, v, and w velocity variances and covariances. In order to assess the ability of these different scanning techniques to measure turbulence, a Halo scanning lidar, WindCube v2 pulsed lidar, and ZephIR continuous wave lidar were deployed at field sites in Oklahoma and Colorado with collocated sonic anemometers.Results indicate that the six-beam strategy mitigates some of the errors caused by VAD and DBS scans, but the strategy is strongly affected by errors in the variance measured at the different beam positions. The ZephIR and WindCube lidars overestimated horizontal variance values by over 60 % under unstable conditions as a result of variance contamination, where additional variance components contaminate the true value of the variance. A correction method was developed for the WindCube lidar that uses variance calculated from the vertical beam position to reduce variance contamination in the u and v variance components. The correction method reduced WindCube variance estimates by over 20 % at both the Oklahoma and Colorado sites under unstable conditions, when variance contamination is largest. This correction method can be easily applied to other lidars that contain a vertical beam position and is a promising method for accurately estimating turbulence with commercially available lidars.

  7. Risk modelling in portfolio optimization

    NASA Astrophysics Data System (ADS)

    Lam, W. H.; Jaaman, Saiful Hafizah Hj.; Isa, Zaidi

    2013-09-01

    Risk management is very important in portfolio optimization. The mean-variance model has been used in portfolio optimization to minimize the investment risk. The objective of the mean-variance model is to minimize the portfolio risk and achieve the target rate of return. Variance is used as risk measure in the mean-variance model. The purpose of this study is to compare the portfolio composition as well as performance between the optimal portfolio of mean-variance model and equally weighted portfolio. Equally weighted portfolio means the proportions that are invested in each asset are equal. The results show that the portfolio composition of the mean-variance optimal portfolio and equally weighted portfolio are different. Besides that, the mean-variance optimal portfolio gives better performance because it gives higher performance ratio than the equally weighted portfolio.

  8. Ex Post Facto Monte Carlo Variance Reduction

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

    Booth, Thomas E.

    The variance in Monte Carlo particle transport calculations is often dominated by a few particles whose importance increases manyfold on a single transport step. This paper describes a novel variance reduction method that uses a large importance change as a trigger to resample the offending transport step. That is, the method is employed only after (ex post facto) a random walk attempts a transport step that would otherwise introduce a large variance in the calculation.Improvements in two Monte Carlo transport calculations are demonstrated empirically using an ex post facto method. First, the method is shown to reduce the variance inmore » a penetration problem with a cross-section window. Second, the method empirically appears to modify a point detector estimator from an infinite variance estimator to a finite variance estimator.« less

  9. 42 CFR 456.521 - Conditions for granting variance requests.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... SERVICES (CONTINUED) MEDICAL ASSISTANCE PROGRAMS UTILIZATION CONTROL Utilization Review Plans: FFP, Waivers, and Variances for Hospitals and Mental Hospitals Ur Plan: Remote Facility Variances from Time... is unable to meet the time requirements for which the variance is requested; and (2) A revised UR...

  10. Portfolio optimization using median-variance approach

    NASA Astrophysics Data System (ADS)

    Wan Mohd, Wan Rosanisah; Mohamad, Daud; Mohamed, Zulkifli

    2013-04-01

    Optimization models have been applied in many decision-making problems particularly in portfolio selection. Since the introduction of Markowitz's theory of portfolio selection, various approaches based on mathematical programming have been introduced such as mean-variance, mean-absolute deviation, mean-variance-skewness and conditional value-at-risk (CVaR) mainly to maximize return and minimize risk. However most of the approaches assume that the distribution of data is normal and this is not generally true. As an alternative, in this paper, we employ the median-variance approach to improve the portfolio optimization. This approach has successfully catered both types of normal and non-normal distribution of data. With this actual representation, we analyze and compare the rate of return and risk between the mean-variance and the median-variance based portfolio which consist of 30 stocks from Bursa Malaysia. The results in this study show that the median-variance approach is capable to produce a lower risk for each return earning as compared to the mean-variance approach.

  11. Integrating mean and variance heterogeneities to identify differentially expressed genes.

    PubMed

    Ouyang, Weiwei; An, Qiang; Zhao, Jinying; Qin, Huaizhen

    2016-12-06

    In functional genomics studies, tests on mean heterogeneity have been widely employed to identify differentially expressed genes with distinct mean expression levels under different experimental conditions. Variance heterogeneity (aka, the difference between condition-specific variances) of gene expression levels is simply neglected or calibrated for as an impediment. The mean heterogeneity in the expression level of a gene reflects one aspect of its distribution alteration; and variance heterogeneity induced by condition change may reflect another aspect. Change in condition may alter both mean and some higher-order characteristics of the distributions of expression levels of susceptible genes. In this report, we put forth a conception of mean-variance differentially expressed (MVDE) genes, whose expression means and variances are sensitive to the change in experimental condition. We mathematically proved the null independence of existent mean heterogeneity tests and variance heterogeneity tests. Based on the independence, we proposed an integrative mean-variance test (IMVT) to combine gene-wise mean heterogeneity and variance heterogeneity induced by condition change. The IMVT outperformed its competitors under comprehensive simulations of normality and Laplace settings. For moderate samples, the IMVT well controlled type I error rates, and so did existent mean heterogeneity test (i.e., the Welch t test (WT), the moderated Welch t test (MWT)) and the procedure of separate tests on mean and variance heterogeneities (SMVT), but the likelihood ratio test (LRT) severely inflated type I error rates. In presence of variance heterogeneity, the IMVT appeared noticeably more powerful than all the valid mean heterogeneity tests. Application to the gene profiles of peripheral circulating B raised solid evidence of informative variance heterogeneity. After adjusting for background data structure, the IMVT replicated previous discoveries and identified novel experiment-wide significant MVDE genes. Our results indicate tremendous potential gain of integrating informative variance heterogeneity after adjusting for global confounders and background data structure. The proposed informative integration test better summarizes the impacts of condition change on expression distributions of susceptible genes than do the existent competitors. Therefore, particular attention should be paid to explicitly exploit the variance heterogeneity induced by condition change in functional genomics analysis.

  12. Deterministic theory of Monte Carlo variance

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

    Ueki, T.; Larsen, E.W.

    1996-12-31

    The theoretical estimation of variance in Monte Carlo transport simulations, particularly those using variance reduction techniques, is a substantially unsolved problem. In this paper, the authors describe a theory that predicts the variance in a variance reduction method proposed by Dwivedi. Dwivedi`s method combines the exponential transform with angular biasing. The key element of this theory is a new modified transport problem, containing the Monte Carlo weight w as an extra independent variable, which simulates Dwivedi`s Monte Carlo scheme. The (deterministic) solution of this modified transport problem yields an expression for the variance. The authors give computational results that validatemore » this theory.« less

  13. Statistical study of EBR-II fuel elements manufactured by the cold line at Argonne-West and by Atomics International

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

    Harkness, A. L.

    1977-09-01

    Nine elements from each batch of fuel elements manufactured for the EBR-II reactor have been analyzed for /sup 235/U content by NDA methods. These values, together with those of the manufacturer, are used to estimate the product variance and the variances of the two measuring methods. These variances are compared with the variances computed from the stipulations of the contract. A method is derived for resolving the several variances into their within-batch and between-batch components. Some of these variance components have also been estimated by independent and more familiar conventional methods for comparison.

  14. R package MVR for Joint Adaptive Mean-Variance Regularization and Variance Stabilization

    PubMed Central

    Dazard, Jean-Eudes; Xu, Hua; Rao, J. Sunil

    2015-01-01

    We present an implementation in the R language for statistical computing of our recent non-parametric joint adaptive mean-variance regularization and variance stabilization procedure. The method is specifically suited for handling difficult problems posed by high-dimensional multivariate datasets (p ≫ n paradigm), such as in ‘omics’-type data, among which are that the variance is often a function of the mean, variable-specific estimators of variances are not reliable, and tests statistics have low powers due to a lack of degrees of freedom. The implementation offers a complete set of features including: (i) normalization and/or variance stabilization function, (ii) computation of mean-variance-regularized t and F statistics, (iii) generation of diverse diagnostic plots, (iv) synthetic and real ‘omics’ test datasets, (v) computationally efficient implementation, using C interfacing, and an option for parallel computing, (vi) manual and documentation on how to setup a cluster. To make each feature as user-friendly as possible, only one subroutine per functionality is to be handled by the end-user. It is available as an R package, called MVR (‘Mean-Variance Regularization’), downloadable from the CRAN. PMID:26819572

  15. 20 CFR 654.402 - Variances.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... subpart by filing a written application for such a variance with the local Job Service office serving the... practical difficulty or unnecessary hardship; and (3) Clearly set forth the specific alternative measures... variance. (b) Upon receipt of a written request for a variance under paragraph (a) of this section, the...

  16. 20 CFR 654.402 - Variances.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... subpart by filing a written application for such a variance with the local Job Service office serving the... practical difficulty or unnecessary hardship; and (3) Clearly set forth the specific alternative measures... variance. (b) Upon receipt of a written request for a variance under paragraph (a) of this section, the...

  17. 20 CFR 654.402 - Variances.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... subpart by filing a written application for such a variance with the local Job Service office serving the... practical difficulty or unnecessary hardship; and (3) Clearly set forth the specific alternative measures... variance. (b) Upon receipt of a written request for a variance under paragraph (a) of this section, the...

  18. 20 CFR 654.402 - Variances.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... subpart by filing a written application for such a variance with the local Job Service office serving the... practical difficulty or unnecessary hardship; and (3) Clearly set forth the specific alternative measures... variance. (b) Upon receipt of a written request for a variance under paragraph (a) of this section, the...

  19. A nonparametric mean-variance smoothing method to assess Arabidopsis cold stress transcriptional regulator CBF2 overexpression microarray data.

    PubMed

    Hu, Pingsha; Maiti, Tapabrata

    2011-01-01

    Microarray is a powerful tool for genome-wide gene expression analysis. In microarray expression data, often mean and variance have certain relationships. We present a non-parametric mean-variance smoothing method (NPMVS) to analyze differentially expressed genes. In this method, a nonlinear smoothing curve is fitted to estimate the relationship between mean and variance. Inference is then made upon shrinkage estimation of posterior means assuming variances are known. Different methods have been applied to simulated datasets, in which a variety of mean and variance relationships were imposed. The simulation study showed that NPMVS outperformed the other two popular shrinkage estimation methods in some mean-variance relationships; and NPMVS was competitive with the two methods in other relationships. A real biological dataset, in which a cold stress transcription factor gene, CBF2, was overexpressed, has also been analyzed with the three methods. Gene ontology and cis-element analysis showed that NPMVS identified more cold and stress responsive genes than the other two methods did. The good performance of NPMVS is mainly due to its shrinkage estimation for both means and variances. In addition, NPMVS exploits a non-parametric regression between mean and variance, instead of assuming a specific parametric relationship between mean and variance. The source code written in R is available from the authors on request.

  20. A Nonparametric Mean-Variance Smoothing Method to Assess Arabidopsis Cold Stress Transcriptional Regulator CBF2 Overexpression Microarray Data

    PubMed Central

    Hu, Pingsha; Maiti, Tapabrata

    2011-01-01

    Microarray is a powerful tool for genome-wide gene expression analysis. In microarray expression data, often mean and variance have certain relationships. We present a non-parametric mean-variance smoothing method (NPMVS) to analyze differentially expressed genes. In this method, a nonlinear smoothing curve is fitted to estimate the relationship between mean and variance. Inference is then made upon shrinkage estimation of posterior means assuming variances are known. Different methods have been applied to simulated datasets, in which a variety of mean and variance relationships were imposed. The simulation study showed that NPMVS outperformed the other two popular shrinkage estimation methods in some mean-variance relationships; and NPMVS was competitive with the two methods in other relationships. A real biological dataset, in which a cold stress transcription factor gene, CBF2, was overexpressed, has also been analyzed with the three methods. Gene ontology and cis-element analysis showed that NPMVS identified more cold and stress responsive genes than the other two methods did. The good performance of NPMVS is mainly due to its shrinkage estimation for both means and variances. In addition, NPMVS exploits a non-parametric regression between mean and variance, instead of assuming a specific parametric relationship between mean and variance. The source code written in R is available from the authors on request. PMID:21611181

  1. Estimating the encounter rate variance in distance sampling

    USGS Publications Warehouse

    Fewster, R.M.; Buckland, S.T.; Burnham, K.P.; Borchers, D.L.; Jupp, P.E.; Laake, J.L.; Thomas, L.

    2009-01-01

    The dominant source of variance in line transect sampling is usually the encounter rate variance. Systematic survey designs are often used to reduce the true variability among different realizations of the design, but estimating the variance is difficult and estimators typically approximate the variance by treating the design as a simple random sample of lines. We explore the properties of different encounter rate variance estimators under random and systematic designs. We show that a design-based variance estimator improves upon the model-based estimator of Buckland et al. (2001, Introduction to Distance Sampling. Oxford: Oxford University Press, p. 79) when transects are positioned at random. However, if populations exhibit strong spatial trends, both estimators can have substantial positive bias under systematic designs. We show that poststratification is effective in reducing this bias. ?? 2008, The International Biometric Society.

  2. Utility functions predict variance and skewness risk preferences in monkeys

    PubMed Central

    Genest, Wilfried; Stauffer, William R.; Schultz, Wolfram

    2016-01-01

    Utility is the fundamental variable thought to underlie economic choices. In particular, utility functions are believed to reflect preferences toward risk, a key decision variable in many real-life situations. To assess the validity of utility representations, it is therefore important to examine risk preferences. In turn, this approach requires formal definitions of risk. A standard approach is to focus on the variance of reward distributions (variance-risk). In this study, we also examined a form of risk related to the skewness of reward distributions (skewness-risk). Thus, we tested the extent to which empirically derived utility functions predicted preferences for variance-risk and skewness-risk in macaques. The expected utilities calculated for various symmetrical and skewed gambles served to define formally the direction of stochastic dominance between gambles. In direct choices, the animals’ preferences followed both second-order (variance) and third-order (skewness) stochastic dominance. Specifically, for gambles with different variance but identical expected values (EVs), the monkeys preferred high-variance gambles at low EVs and low-variance gambles at high EVs; in gambles with different skewness but identical EVs and variances, the animals preferred positively over symmetrical and negatively skewed gambles in a strongly transitive fashion. Thus, the utility functions predicted the animals’ preferences for variance-risk and skewness-risk. Using these well-defined forms of risk, this study shows that monkeys’ choices conform to the internal reward valuations suggested by their utility functions. This result implies a representation of utility in monkeys that accounts for both variance-risk and skewness-risk preferences. PMID:27402743

  3. Evaluation of three lidar scanning strategies for turbulence measurements

    DOE PAGES

    Newman, Jennifer F.; Klein, Petra M.; Wharton, Sonia; ...

    2016-05-03

    Several errors occur when a traditional Doppler beam swinging (DBS) or velocity–azimuth display (VAD) strategy is used to measure turbulence with a lidar. To mitigate some of these errors, a scanning strategy was recently developed which employs six beam positions to independently estimate the u, v, and w velocity variances and covariances. In order to assess the ability of these different scanning techniques to measure turbulence, a Halo scanning lidar, WindCube v2 pulsed lidar, and ZephIR continuous wave lidar were deployed at field sites in Oklahoma and Colorado with collocated sonic anemometers.Results indicate that the six-beam strategy mitigates some of the errors caused bymore » VAD and DBS scans, but the strategy is strongly affected by errors in the variance measured at the different beam positions. The ZephIR and WindCube lidars overestimated horizontal variance values by over 60 % under unstable conditions as a result of variance contamination, where additional variance components contaminate the true value of the variance. A correction method was developed for the WindCube lidar that uses variance calculated from the vertical beam position to reduce variance contamination in the u and v variance components. The correction method reduced WindCube variance estimates by over 20 % at both the Oklahoma and Colorado sites under unstable conditions, when variance contamination is largest. This correction method can be easily applied to other lidars that contain a vertical beam position and is a promising method for accurately estimating turbulence with commercially available lidars.« less

  4. Evaluation of three lidar scanning strategies for turbulence measurements

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

    Newman, Jennifer F.; Klein, Petra M.; Wharton, Sonia

    Several errors occur when a traditional Doppler beam swinging (DBS) or velocity–azimuth display (VAD) strategy is used to measure turbulence with a lidar. To mitigate some of these errors, a scanning strategy was recently developed which employs six beam positions to independently estimate the u, v, and w velocity variances and covariances. In order to assess the ability of these different scanning techniques to measure turbulence, a Halo scanning lidar, WindCube v2 pulsed lidar, and ZephIR continuous wave lidar were deployed at field sites in Oklahoma and Colorado with collocated sonic anemometers.Results indicate that the six-beam strategy mitigates some of the errors caused bymore » VAD and DBS scans, but the strategy is strongly affected by errors in the variance measured at the different beam positions. The ZephIR and WindCube lidars overestimated horizontal variance values by over 60 % under unstable conditions as a result of variance contamination, where additional variance components contaminate the true value of the variance. A correction method was developed for the WindCube lidar that uses variance calculated from the vertical beam position to reduce variance contamination in the u and v variance components. The correction method reduced WindCube variance estimates by over 20 % at both the Oklahoma and Colorado sites under unstable conditions, when variance contamination is largest. This correction method can be easily applied to other lidars that contain a vertical beam position and is a promising method for accurately estimating turbulence with commercially available lidars.« less

  5. An apparent contradiction: increasing variability to achieve greater precision?

    PubMed

    Rosenblatt, Noah J; Hurt, Christopher P; Latash, Mark L; Grabiner, Mark D

    2014-02-01

    To understand the relationship between variability of foot placement in the frontal plane and stability of gait patterns, we explored how constraining mediolateral foot placement during walking affects the structure of kinematic variance in the lower-limb configuration space during the swing phase of gait. Ten young subjects walked under three conditions: (1) unconstrained (normal walking), (2) constrained (walking overground with visual guides for foot placement to achieve the measured unconstrained step width) and, (3) beam (walking on elevated beams spaced to achieve the measured unconstrained step width). The uncontrolled manifold analysis of the joint configuration variance was used to quantify two variance components, one that did not affect the mediolateral trajectory of the foot in the frontal plane ("good variance") and one that affected this trajectory ("bad variance"). Based on recent studies, we hypothesized that across conditions (1) the index of the synergy stabilizing the mediolateral trajectory of the foot (the normalized difference between the "good variance" and "bad variance") would systematically increase and (2) the changes in the synergy index would be associated with a disproportionate increase in the "good variance." Both hypotheses were confirmed. We conclude that an increase in the "good variance" component of the joint configuration variance may be an effective method of ensuring high stability of gait patterns during conditions requiring increased control of foot placement, particularly if a postural threat is present. Ultimately, designing interventions that encourage a larger amount of "good variance" may be a promising method of improving stability of gait patterns in populations such as older adults and neurological patients.

  6. A two step Bayesian approach for genomic prediction of breeding values.

    PubMed

    Shariati, Mohammad M; Sørensen, Peter; Janss, Luc

    2012-05-21

    In genomic models that assign an individual variance to each marker, the contribution of one marker to the posterior distribution of the marker variance is only one degree of freedom (df), which introduces many variance parameters with only little information per variance parameter. A better alternative could be to form clusters of markers with similar effects where markers in a cluster have a common variance. Therefore, the influence of each marker group of size p on the posterior distribution of the marker variances will be p df. The simulated data from the 15th QTL-MAS workshop were analyzed such that SNP markers were ranked based on their effects and markers with similar estimated effects were grouped together. In step 1, all markers with minor allele frequency more than 0.01 were included in a SNP-BLUP prediction model. In step 2, markers were ranked based on their estimated variance on the trait in step 1 and each 150 markers were assigned to one group with a common variance. In further analyses, subsets of 1500 and 450 markers with largest effects in step 2 were kept in the prediction model. Grouping markers outperformed SNP-BLUP model in terms of accuracy of predicted breeding values. However, the accuracies of predicted breeding values were lower than Bayesian methods with marker specific variances. Grouping markers is less flexible than allowing each marker to have a specific marker variance but, by grouping, the power to estimate marker variances increases. A prior knowledge of the genetic architecture of the trait is necessary for clustering markers and appropriate prior parameterization.

  7. Utility functions predict variance and skewness risk preferences in monkeys.

    PubMed

    Genest, Wilfried; Stauffer, William R; Schultz, Wolfram

    2016-07-26

    Utility is the fundamental variable thought to underlie economic choices. In particular, utility functions are believed to reflect preferences toward risk, a key decision variable in many real-life situations. To assess the validity of utility representations, it is therefore important to examine risk preferences. In turn, this approach requires formal definitions of risk. A standard approach is to focus on the variance of reward distributions (variance-risk). In this study, we also examined a form of risk related to the skewness of reward distributions (skewness-risk). Thus, we tested the extent to which empirically derived utility functions predicted preferences for variance-risk and skewness-risk in macaques. The expected utilities calculated for various symmetrical and skewed gambles served to define formally the direction of stochastic dominance between gambles. In direct choices, the animals' preferences followed both second-order (variance) and third-order (skewness) stochastic dominance. Specifically, for gambles with different variance but identical expected values (EVs), the monkeys preferred high-variance gambles at low EVs and low-variance gambles at high EVs; in gambles with different skewness but identical EVs and variances, the animals preferred positively over symmetrical and negatively skewed gambles in a strongly transitive fashion. Thus, the utility functions predicted the animals' preferences for variance-risk and skewness-risk. Using these well-defined forms of risk, this study shows that monkeys' choices conform to the internal reward valuations suggested by their utility functions. This result implies a representation of utility in monkeys that accounts for both variance-risk and skewness-risk preferences.

  8. 10 CFR 851.31 - Variance process.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... OF ENERGY WORKER SAFETY AND HEALTH PROGRAM Variances § 851.31 Variance process. (a) Application. Contractors desiring a variance from a safety and health standard, or portion thereof, may submit a written...) The CSO may forward the application to the Chief Health, Safety and Security Officer. (2) If the CSO...

  9. Hidden Item Variance in Multiple Mini-Interview Scores

    ERIC Educational Resources Information Center

    Zaidi, Nikki L.; Swoboda, Christopher M.; Kelcey, Benjamin M.; Manuel, R. Stephen

    2017-01-01

    The extant literature has largely ignored a potentially significant source of variance in multiple mini-interview (MMI) scores by "hiding" the variance attributable to the sample of attributes used on an evaluation form. This potential source of hidden variance can be defined as rating items, which typically comprise an MMI evaluation…

  10. Modeling Heterogeneous Variance-Covariance Components in Two-Level Models

    ERIC Educational Resources Information Center

    Leckie, George; French, Robert; Charlton, Chris; Browne, William

    2014-01-01

    Applications of multilevel models to continuous outcomes nearly always assume constant residual variance and constant random effects variances and covariances. However, modeling heterogeneity of variance can prove a useful indicator of model misspecification, and in some educational and behavioral studies, it may even be of direct substantive…

  11. Speed Variance and Its Influence on Accidents.

    ERIC Educational Resources Information Center

    Garber, Nicholas J.; Gadirau, Ravi

    A study was conducted to investigate the traffic engineering factors that influence speed variance and to determine to what extent speed variance affects accident rates. Detailed analyses were carried out to relate speed variance with posted speed limit, design speeds, and other traffic variables. The major factor identified was the difference…

  12. 44 CFR 60.6 - Variances and exceptions.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program CRITERIA FOR LAND MANAGEMENT AND USE Requirements for Flood Plain Management Regulations § 60.6 Variances and... variances from the criteria set forth in §§ 60.3, 60.4, and 60.5. The issuance of a variance is for flood...

  13. 44 CFR 60.6 - Variances and exceptions.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program CRITERIA FOR LAND MANAGEMENT AND USE Requirements for Flood Plain Management Regulations § 60.6 Variances and... variances from the criteria set forth in §§ 60.3, 60.4, and 60.5. The issuance of a variance is for flood...

  14. Feasibility Study for Design of a Biocybernetic Communication System

    DTIC Science & Technology

    1975-08-01

    electrode for the Within Words variance and Between Words variance for each of the 255 data samples in the 6-sec epoch. If a given sample point was not...contributing to the computer classification of the word, the ratio of the two variances (i.e., the F-statistic) should be small. On the other hand...if the Between Word variance was signifi- cantly higher than the Within Word variance for a given sample point, we can assume with some confidence

  15. Enhancing target variance in personality impressions: highlighting the person in person perception.

    PubMed

    Paulhus, D L; Reynolds, S

    1995-12-01

    D. A. Kenny (1994) estimated the components of personality rating variance to be 15, 20, and 20% for target, rater, and relationship, respectively. To enhance trait variance and minimize rater variance, we designed a series of studies of personality perception in discussion groups (N = 79, 58, and 59). After completing a Big Five questionnaire, participants met 7 times in small groups. After Meetings 1 and 7, group members rated each other. By applying the Social Relations Model (D. A. Kenny and L. La Voie, 1984) to each Big Five dimension at each point in time, we were able to evaluate 6 rating effects as well as rating validity. Among the findings were that (a) target variance was the largest component (almost 30%), whereas rater variance was small (less than 11%); (b) rating validity improved significantly with acquaintance, although target variance did not; and (c) no reciprocity was found, but projection was significant for Agreeableness.

  16. Age-related variation in genetic control of height growth in Douglas-fir.

    PubMed

    Namkoong, G; Usanis, R A; Silen, R R

    1972-01-01

    The development of genetic variances in height growth of Douglas-fir over a 53-year period is analyzed and found to fall into three periods. In the juvenile period, variances in environmental error increase logarithmically, genetic variance within populations exists at moderate levels, and variance among populations is low but increasing. In the early reproductive period, the response to environmental sources of error variance is restricted, genetic variance within populations disappears, and populational differences strongly emerge but do not increase as expected. In the later period, environmental error again increases rapidly, but genetic variance within populations does not reappear and population differences are maintained at about the same level as established in the early reproductive period. The change between the juvenile and early reproductive periods is perhaps associated with the onset of ecological dominance and significant allocations of energy to reproduction.

  17. 40 CFR 142.302 - Who can issue a small system variance?

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 40 Protection of Environment 22 2010-07-01 2010-07-01 false Who can issue a small system variance? 142.302 Section 142.302 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER... General Provisions § 142.302 Who can issue a small system variance? A small system variance under this...

  18. A New Nonparametric Levene Test for Equal Variances

    ERIC Educational Resources Information Center

    Nordstokke, David W.; Zumbo, Bruno D.

    2010-01-01

    Tests of the equality of variances are sometimes used on their own to compare variability across groups of experimental or non-experimental conditions but they are most often used alongside other methods to support assumptions made about variances. A new nonparametric test of equality of variances is described and compared to current "gold…

  19. 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.

  20. On the Likely Utility of Hybrid Weights Optimized for Variances in Hybrid Error Covariance Models

    NASA Astrophysics Data System (ADS)

    Satterfield, E.; Hodyss, D.; Kuhl, D.; Bishop, C. H.

    2017-12-01

    Because of imperfections in ensemble data assimilation schemes, one cannot assume that the ensemble covariance is equal to the true error covariance of a forecast. Previous work demonstrated how information about the distribution of true error variances given an ensemble sample variance can be revealed from an archive of (observation-minus-forecast, ensemble-variance) data pairs. Here, we derive a simple and intuitively compelling formula to obtain the mean of this distribution of true error variances given an ensemble sample variance from (observation-minus-forecast, ensemble-variance) data pairs produced by a single run of a data assimilation system. This formula takes the form of a Hybrid weighted average of the climatological forecast error variance and the ensemble sample variance. Here, we test the extent to which these readily obtainable weights can be used to rapidly optimize the covariance weights used in Hybrid data assimilation systems that employ weighted averages of static covariance models and flow-dependent ensemble based covariance models. Univariate data assimilation and multi-variate cycling ensemble data assimilation are considered. In both cases, it is found that our computationally efficient formula gives Hybrid weights that closely approximate the optimal weights found through the simple but computationally expensive process of testing every plausible combination of weights.

  1. Individual and collective bodies: using measures of variance and association in contextual epidemiology.

    PubMed

    Merlo, J; Ohlsson, H; Lynch, K F; Chaix, B; Subramanian, S V

    2009-12-01

    Social epidemiology investigates both individuals and their collectives. Although the limits that define the individual bodies are very apparent, the collective body's geographical or cultural limits (eg "neighbourhood") are more difficult to discern. Also, epidemiologists normally investigate causation as changes in group means. However, many variables of interest in epidemiology may cause a change in the variance of the distribution of the dependent variable. In spite of that, variance is normally considered a measure of uncertainty or a nuisance rather than a source of substantive information. This reasoning is also true in many multilevel investigations, whereas understanding the distribution of variance across levels should be fundamental. This means-centric reductionism is mostly concerned with risk factors and creates a paradoxical situation, as social medicine is not only interested in increasing the (mean) health of the population, but also in understanding and decreasing inappropriate health and health care inequalities (variance). Critical essay and literature review. The present study promotes (a) the application of measures of variance and clustering to evaluate the boundaries one uses in defining collective levels of analysis (eg neighbourhoods), (b) the combined use of measures of variance and means-centric measures of association, and (c) the investigation of causes of health variation (variance-altering causation). Both measures of variance and means-centric measures of association need to be included when performing contextual analyses. The variance approach, a new aspect of contextual analysis that cannot be interpreted in means-centric terms, allows perspectives to be expanded.

  2. A General Definition of the Heritable Variation That Determines the Potential of a Population to Respond to Selection

    PubMed Central

    Bijma, Piter

    2011-01-01

    Genetic selection is a major force shaping life on earth. In classical genetic theory, response to selection is the product of the strength of selection and the additive genetic variance in a trait. The additive genetic variance reflects a population’s intrinsic potential to respond to selection. The ordinary additive genetic variance, however, ignores the social organization of life. With social interactions among individuals, individual trait values may depend on genes in others, a phenomenon known as indirect genetic effects. Models accounting for indirect genetic effects, however, lack a general definition of heritable variation. Here I propose a general definition of the heritable variation that determines the potential of a population to respond to selection. This generalizes the concept of heritable variance to any inheritance model and level of organization. The result shows that heritable variance determining potential response to selection is the variance among individuals in the heritable quantity that determines the population mean trait value, rather than the usual additive genetic component of phenotypic variance. It follows, therefore, that heritable variance may exceed phenotypic variance among individuals, which is impossible in classical theory. This work also provides a measure of the utilization of heritable variation for response to selection and integrates two well-known models of maternal genetic effects. The result shows that relatedness between the focal individual and the individuals affecting its fitness is a key determinant of the utilization of heritable variance for response to selection. PMID:21926298

  3. A general definition of the heritable variation that determines the potential of a population to respond to selection.

    PubMed

    Bijma, Piter

    2011-12-01

    Genetic selection is a major force shaping life on earth. In classical genetic theory, response to selection is the product of the strength of selection and the additive genetic variance in a trait. The additive genetic variance reflects a population's intrinsic potential to respond to selection. The ordinary additive genetic variance, however, ignores the social organization of life. With social interactions among individuals, individual trait values may depend on genes in others, a phenomenon known as indirect genetic effects. Models accounting for indirect genetic effects, however, lack a general definition of heritable variation. Here I propose a general definition of the heritable variation that determines the potential of a population to respond to selection. This generalizes the concept of heritable variance to any inheritance model and level of organization. The result shows that heritable variance determining potential response to selection is the variance among individuals in the heritable quantity that determines the population mean trait value, rather than the usual additive genetic component of phenotypic variance. It follows, therefore, that heritable variance may exceed phenotypic variance among individuals, which is impossible in classical theory. This work also provides a measure of the utilization of heritable variation for response to selection and integrates two well-known models of maternal genetic effects. The result shows that relatedness between the focal individual and the individuals affecting its fitness is a key determinant of the utilization of heritable variance for response to selection.

  4. Risk factors for near-miss events and safety incidents in pediatric radiation therapy.

    PubMed

    Baig, Nimrah; Wang, Jiangxia; Elnahal, Shereef; McNutt, Todd; Wright, Jean; DeWeese, Theodore; Terezakis, Stephanie

    2018-05-01

    Factors contributing to safety- or quality-related incidents (e.g. variances) in children are unknown. We identified clinical and RT treatment variables associated with risk for variances in a pediatric cohort. Using our institution's incident learning system, 81 patients age ≤21 years old who experienced variances were compared to 191 pediatric patients without variances. Clinical and RT treatment variables were evaluated as potential predictors for variances using univariate and multivariate analyses. Variances were primarily documentation errors (n = 46, 57%) and were most commonly detected during treatment planning (n = 14, 21%). Treatment planning errors constituted the majority (n = 16 out of 29, 55%) of near-misses and safety incidents (NMSI), which excludes workflow incidents. Therapists reported the majority of variances (n = 50, 62%). Physician cross-coverage (OR = 2.1, 95% CI = 1.04-4.38) and 3D conformal RT (OR = 2.3, 95% CI = 1.11-4.69) increased variance risk. Conversely, age >14 years (OR = 0.5, 95% CI = 0.28-0.88) and diagnosis of abdominal tumor (OR = 0.2, 95% CI = 0.04-0.59) decreased variance risk. Variances in children occurred in early treatment phases, but were detected at later workflow stages. Quality measures should be implemented during early treatment phases with a focus on younger children and those cared for by cross-covering physicians. Copyright © 2018 Elsevier B.V. All rights reserved.

  5. Gender differences in psychosocial predictors of texting while driving.

    PubMed

    Struckman-Johnson, Cindy; Gaster, Samuel; Struckman-Johnson, Dave; Johnson, Melissa; May-Shinagle, Gabby

    2015-01-01

    A sample of 158 male and 357 female college students at a midwestern university participated in an on-line study of psychosocial motives for texting while driving. Men and women did not differ in self-reported ratings of how often they texted while driving. However, more women sent texts of less than a sentence while more men sent texts of 1-5 sentences. More women than men said they would quit texting while driving due to police warnings, receiving information about texting dangers, being shown graphic pictures of texting accidents, and being in a car accident. A hierarchical regression for men's data revealed that lower levels of feeling distracted by texting while driving (20% of the variance), higher levels of cell phone dependence (11.5% of the variance), risky behavioral tendencies (6.5% of the variance) and impulsivity (2.3%) of the variance) were significantly associated with more texting while driving (total model variance=42%). A separate regression for women revealed that higher levels of cell phone dependence (10.4% of the variance), risky behavioral tendencies (9.9% of the variance), texting distractibility (6.2%), crash risk estimates (2.2% of the variance) and driving confidence (1.3% of the variance) were significantly associated with more texting while driving (total model variance=31%.) Friendship potential and need for intimacy were not related to men's or women's texting while driving. Implications of the results for gender-specific prevention strategies are discussed. Copyright © 2014 Elsevier Ltd. All rights reserved.

  6. Planning additional drilling campaign using two-space genetic algorithm: A game theoretical approach

    NASA Astrophysics Data System (ADS)

    Kumral, Mustafa; Ozer, Umit

    2013-03-01

    Grade and tonnage are the most important technical uncertainties in mining ventures because of the use of estimations/simulations, which are mostly generated from drill data. Open pit mines are planned and designed on the basis of the blocks representing the entire orebody. Each block has different estimation/simulation variance reflecting uncertainty to some extent. The estimation/simulation realizations are submitted to mine production scheduling process. However, the use of a block model with varying estimation/simulation variances will lead to serious risk in the scheduling. In the medium of multiple simulations, the dispersion variances of blocks can be thought to regard technical uncertainties. However, the dispersion variance cannot handle uncertainty associated with varying estimation/simulation variances of blocks. This paper proposes an approach that generates the configuration of the best additional drilling campaign to generate more homogenous estimation/simulation variances of blocks. In other words, the objective is to find the best drilling configuration in such a way as to minimize grade uncertainty under budget constraint. Uncertainty measure of the optimization process in this paper is interpolation variance, which considers data locations and grades. The problem is expressed as a minmax problem, which focuses on finding the best worst-case performance i.e., minimizing interpolation variance of the block generating maximum interpolation variance. Since the optimization model requires computing the interpolation variances of blocks being simulated/estimated in each iteration, the problem cannot be solved by standard optimization tools. This motivates to use two-space genetic algorithm (GA) approach to solve the problem. The technique has two spaces: feasible drill hole configuration with minimization of interpolation variance and drill hole simulations with maximization of interpolation variance. Two-space interacts to find a minmax solution iteratively. A case study was conducted to demonstrate the performance of approach. The findings showed that the approach could be used to plan a new drilling campaign.

  7. Genetic control of residual variance of yearling weight in Nellore beef cattle.

    PubMed

    Iung, L H S; Neves, H H R; Mulder, H A; Carvalheiro, R

    2017-04-01

    There is evidence for genetic variability in residual variance of livestock traits, which offers the potential for selection for increased uniformity of production. Different statistical approaches have been employed to study this topic; however, little is known about the concordance between them. The aim of our study was to investigate the genetic heterogeneity of residual variance on yearling weight (YW; 291.15 ± 46.67) in a Nellore beef cattle population; to compare the results of the statistical approaches, the two-step approach and the double hierarchical generalized linear model (DHGLM); and to evaluate the effectiveness of power transformation to accommodate scale differences. The comparison was based on genetic parameters, accuracy of EBV for residual variance, and cross-validation to assess predictive performance of both approaches. A total of 194,628 yearling weight records from 625 sires were used in the analysis. The results supported the hypothesis of genetic heterogeneity of residual variance on YW in Nellore beef cattle and the opportunity of selection, measured through the genetic coefficient of variation of residual variance (0.10 to 0.12 for the two-step approach and 0.17 for DHGLM, using an untransformed data set). However, low estimates of genetic variance associated with positive genetic correlations between mean and residual variance (about 0.20 for two-step and 0.76 for DHGLM for an untransformed data set) limit the genetic response to selection for uniformity of production while simultaneously increasing YW itself. Moreover, large sire families are needed to obtain accurate estimates of genetic merit for residual variance, as indicated by the low heritability estimates (<0.007). Box-Cox transformation was able to decrease the dependence of the variance on the mean and decreased the estimates of genetic parameters for residual variance. The transformation reduced but did not eliminate all the genetic heterogeneity of residual variance, highlighting its presence beyond the scale effect. The DHGLM showed higher predictive ability of EBV for residual variance and therefore should be preferred over the two-step approach.

  8. Genetic variance in micro-environmental sensitivity for milk and milk quality in Walloon Holstein cattle.

    PubMed

    Vandenplas, J; Bastin, C; Gengler, N; Mulder, H A

    2013-09-01

    Animals that are robust to environmental changes are desirable in the current dairy industry. Genetic differences in micro-environmental sensitivity can be studied through heterogeneity of residual variance between animals. However, residual variance between animals is usually assumed to be homogeneous in traditional genetic evaluations. The aim of this study was to investigate genetic heterogeneity of residual variance by estimating variance components in residual variance for milk yield, somatic cell score, contents in milk (g/dL) of 2 groups of milk fatty acids (i.e., saturated and unsaturated fatty acids), and the content in milk of one individual fatty acid (i.e., oleic acid, C18:1 cis-9), for first-parity Holstein cows in the Walloon Region of Belgium. A total of 146,027 test-day records from 26,887 cows in 747 herds were available. All cows had at least 3 records and a known sire. These sires had at least 10 cows with records and each herd × test-day had at least 5 cows. The 5 traits were analyzed separately based on fixed lactation curve and random regression test-day models for the mean. Estimation of variance components was performed by running iteratively expectation maximization-REML algorithm by the implementation of double hierarchical generalized linear models. Based on fixed lactation curve test-day mean models, heritability for residual variances ranged between 1.01×10(-3) and 4.17×10(-3) for all traits. The genetic standard deviation in residual variance (i.e., approximately the genetic coefficient of variation of residual variance) ranged between 0.12 and 0.17. Therefore, some genetic variance in micro-environmental sensitivity existed in the Walloon Holstein dairy cattle for the 5 studied traits. The standard deviations due to herd × test-day and permanent environment in residual variance ranged between 0.36 and 0.45 for herd × test-day effect and between 0.55 and 0.97 for permanent environmental effect. Therefore, nongenetic effects also contributed substantially to micro-environmental sensitivity. Addition of random regressions to the mean model did not reduce heterogeneity in residual variance and that genetic heterogeneity of residual variance was not simply an effect of an incomplete mean model. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  9. 29 CFR 1905.11 - Variances and other relief under section 6(d).

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 29 Labor 5 2010-07-01 2010-07-01 false Variances and other relief under section 6(d). 1905.11... section 6(d). (a) Application for variance. Any employer, or class of employers, desiring a variance authorized by section 6(d) of the Act may file a written application containing the information specified in...

  10. 76 FR 30027 - Land Disposal Restrictions: Site-Specific Treatment Variance for Hazardous Selenium-Bearing Waste...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-05-24

    ... Restrictions: Site-Specific Treatment Variance for Hazardous Selenium-Bearing Waste Treated by U.S. Ecology.... Ecology Nevada in Beatty, Nevada and withdrew an existing site- specific treatment variance issued to... 268.44(o)) by granting a site-specific treatment variance to U.S. Ecology Nevada in Beatty, Nevada and...

  11. 40 CFR 260.33 - Procedures for variances from classification as a solid waste, for variances to be classified as...

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... classification as a solid waste, for variances to be classified as a boiler, or for non-waste determinations. 260.33 Section 260.33 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) SOLID WASTES (CONTINUED) HAZARDOUS WASTE MANAGEMENT SYSTEM: GENERAL Rulemaking Petitions § 260.33 Procedures for variances...

  12. 40 CFR 260.33 - Procedures for variances from classification as a solid waste, for variances to be classified as...

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... classification as a solid waste, for variances to be classified as a boiler, or for non-waste determinations. 260.33 Section 260.33 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) SOLID WASTES (CONTINUED) HAZARDOUS WASTE MANAGEMENT SYSTEM: GENERAL Rulemaking Petitions § 260.33 Procedures for variances...

  13. 40 CFR 260.33 - Procedures for variances from classification as a solid waste, for variances to be classified as...

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... classification as a solid waste, for variances to be classified as a boiler, or for non-waste determinations. 260.33 Section 260.33 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) SOLID WASTES (CONTINUED) HAZARDOUS WASTE MANAGEMENT SYSTEM: GENERAL Rulemaking Petitions § 260.33 Procedures for variances...

  14. Improving the precision of lake ecosystem metabolism estimates by identifying predictors of model uncertainty

    USGS Publications Warehouse

    Rose, Kevin C.; Winslow, Luke A.; Read, Jordan S.; Read, Emily K.; Solomon, Christopher T.; Adrian, Rita; Hanson, Paul C.

    2014-01-01

    Diel changes in dissolved oxygen are often used to estimate gross primary production (GPP) and ecosystem respiration (ER) in aquatic ecosystems. Despite the widespread use of this approach to understand ecosystem metabolism, we are only beginning to understand the degree and underlying causes of uncertainty for metabolism model parameter estimates. Here, we present a novel approach to improve the precision and accuracy of ecosystem metabolism estimates by identifying physical metrics that indicate when metabolism estimates are highly uncertain. Using datasets from seventeen instrumented GLEON (Global Lake Ecological Observatory Network) lakes, we discovered that many physical characteristics correlated with uncertainty, including PAR (photosynthetically active radiation, 400-700 nm), daily variance in Schmidt stability, and wind speed. Low PAR was a consistent predictor of high variance in GPP model parameters, but also corresponded with low ER model parameter variance. We identified a threshold (30% of clear sky PAR) below which GPP parameter variance increased rapidly and was significantly greater in nearly all lakes compared with variance on days with PAR levels above this threshold. The relationship between daily variance in Schmidt stability and GPP model parameter variance depended on trophic status, whereas daily variance in Schmidt stability was consistently positively related to ER model parameter variance. Wind speeds in the range of ~0.8-3 m s–1 were consistent predictors of high variance for both GPP and ER model parameters, with greater uncertainty in eutrophic lakes. Our findings can be used to reduce ecosystem metabolism model parameter uncertainty and identify potential sources of that uncertainty.

  15. Understanding and comparisons of different sampling approaches for the Fourier Amplitudes Sensitivity Test (FAST)

    PubMed Central

    Xu, Chonggang; Gertner, George

    2013-01-01

    Fourier Amplitude Sensitivity Test (FAST) is one of the most popular uncertainty and sensitivity analysis techniques. It uses a periodic sampling approach and a Fourier transformation to decompose the variance of a model output into partial variances contributed by different model parameters. Until now, the FAST analysis is mainly confined to the estimation of partial variances contributed by the main effects of model parameters, but does not allow for those contributed by specific interactions among parameters. In this paper, we theoretically show that FAST analysis can be used to estimate partial variances contributed by both main effects and interaction effects of model parameters using different sampling approaches (i.e., traditional search-curve based sampling, simple random sampling and random balance design sampling). We also analytically calculate the potential errors and biases in the estimation of partial variances. Hypothesis tests are constructed to reduce the effect of sampling errors on the estimation of partial variances. Our results show that compared to simple random sampling and random balance design sampling, sensitivity indices (ratios of partial variances to variance of a specific model output) estimated by search-curve based sampling generally have higher precision but larger underestimations. Compared to simple random sampling, random balance design sampling generally provides higher estimation precision for partial variances contributed by the main effects of parameters. The theoretical derivation of partial variances contributed by higher-order interactions and the calculation of their corresponding estimation errors in different sampling schemes can help us better understand the FAST method and provide a fundamental basis for FAST applications and further improvements. PMID:24143037

  16. Understanding and comparisons of different sampling approaches for the Fourier Amplitudes Sensitivity Test (FAST).

    PubMed

    Xu, Chonggang; Gertner, George

    2011-01-01

    Fourier Amplitude Sensitivity Test (FAST) is one of the most popular uncertainty and sensitivity analysis techniques. It uses a periodic sampling approach and a Fourier transformation to decompose the variance of a model output into partial variances contributed by different model parameters. Until now, the FAST analysis is mainly confined to the estimation of partial variances contributed by the main effects of model parameters, but does not allow for those contributed by specific interactions among parameters. In this paper, we theoretically show that FAST analysis can be used to estimate partial variances contributed by both main effects and interaction effects of model parameters using different sampling approaches (i.e., traditional search-curve based sampling, simple random sampling and random balance design sampling). We also analytically calculate the potential errors and biases in the estimation of partial variances. Hypothesis tests are constructed to reduce the effect of sampling errors on the estimation of partial variances. Our results show that compared to simple random sampling and random balance design sampling, sensitivity indices (ratios of partial variances to variance of a specific model output) estimated by search-curve based sampling generally have higher precision but larger underestimations. Compared to simple random sampling, random balance design sampling generally provides higher estimation precision for partial variances contributed by the main effects of parameters. The theoretical derivation of partial variances contributed by higher-order interactions and the calculation of their corresponding estimation errors in different sampling schemes can help us better understand the FAST method and provide a fundamental basis for FAST applications and further improvements.

  17. Repeat sample intraocular pressure variance in induced and naturally ocular hypertensive monkeys.

    PubMed

    Dawson, William W; Dawson, Judyth C; Hope, George M; Brooks, Dennis E; Percicot, Christine L

    2005-12-01

    To compare repeat-sample means variance of laser induced ocular hypertension (OH) in rhesus monkeys with the repeat-sample mean variance of natural OH in age-range matched monkeys of similar and dissimilar pedigrees. Multiple monocular, retrospective, intraocular pressure (IOP) measures were recorded repeatedly during a short sampling interval (SSI, 1-5 months) and a long sampling interval (LSI, 6-36 months). There were 5-13 eyes in each SSI and LSI subgroup. Each interval contained subgroups from the Florida with natural hypertension (NHT), induced hypertension (IHT1) Florida monkeys, unrelated (Strasbourg, France) induced hypertensives (IHT2), and Florida age-range matched controls (C). Repeat-sample individual variance means and related IOPs were analyzed by a parametric analysis of variance (ANOV) and results compared to non-parametric Kruskal-Wallis ANOV. As designed, all group intraocular pressure distributions were significantly different (P < or = 0.009) except for the two (Florida/Strasbourg) induced OH groups. A parametric 2 x 4 design ANOV for mean variance showed large significant effects due to treatment group and sampling interval. Similar results were produced by the nonparametric ANOV. Induced OH sample variance (LSI) was 43x the natural OH sample variance-mean. The same relationship for the SSI was 12x. Laser induced ocular hypertension in rhesus monkeys produces large IOP repeat-sample variance mean results compared to controls and natural OH.

  18. Relating the Hadamard Variance to MCS Kalman Filter Clock Estimation

    NASA Technical Reports Server (NTRS)

    Hutsell, Steven T.

    1996-01-01

    The Global Positioning System (GPS) Master Control Station (MCS) currently makes significant use of the Allan Variance. This two-sample variance equation has proven excellent as a handy, understandable tool, both for time domain analysis of GPS cesium frequency standards, and for fine tuning the MCS's state estimation of these atomic clocks. The Allan Variance does not explicitly converge for the nose types of alpha less than or equal to minus 3 and can be greatly affected by frequency drift. Because GPS rubidium frequency standards exhibit non-trivial aging and aging noise characteristics, the basic Allan Variance analysis must be augmented in order to (a) compensate for a dynamic frequency drift, and (b) characterize two additional noise types, specifically alpha = minus 3, and alpha = minus 4. As the GPS program progresses, we will utilize a larger percentage of rubidium frequency standards than ever before. Hence, GPS rubidium clock characterization will require more attention than ever before. The three sample variance, commonly referred to as a renormalized Hadamard Variance, is unaffected by linear frequency drift, converges for alpha is greater than minus 5, and thus has utility for modeling noise in GPS rubidium frequency standards. This paper demonstrates the potential of Hadamard Variance analysis in GPS operations, and presents an equation that relates the Hadamard Variance to the MCS's Kalman filter process noises.

  19. Is residual memory variance a valid method for quantifying cognitive reserve? A longitudinal application.

    PubMed

    Zahodne, Laura B; Manly, Jennifer J; Brickman, Adam M; Narkhede, Atul; Griffith, Erica Y; Guzman, Vanessa A; Schupf, Nicole; Stern, Yaakov

    2015-10-01

    Cognitive reserve describes the mismatch between brain integrity and cognitive performance. Older adults with high cognitive reserve are more resilient to age-related brain pathology. Traditionally, cognitive reserve is indexed indirectly via static proxy variables (e.g., years of education). More recently, cross-sectional studies have suggested that reserve can be expressed as residual variance in episodic memory performance that remains after accounting for demographic factors and brain pathology (whole brain, hippocampal, and white matter hyperintensity volumes). The present study extends these methods to a longitudinal framework in a community-based cohort of 244 older adults who underwent two comprehensive neuropsychological and structural magnetic resonance imaging sessions over 4.6 years. On average, residual memory variance decreased over time, consistent with the idea that cognitive reserve is depleted over time. Individual differences in change in residual memory variance predicted incident dementia, independent of baseline residual memory variance. Multiple-group latent difference score models revealed tighter coupling between brain and language changes among individuals with decreasing residual memory variance. These results suggest that changes in residual memory variance may capture a dynamic aspect of cognitive reserve and could be a useful way to summarize individual cognitive responses to brain changes. Change in residual memory variance among initially non-demented older adults was a better predictor of incident dementia than residual memory variance measured at one time-point. Copyright © 2015. Published by Elsevier Ltd.

  20. Is residual memory variance a valid method for quantifying cognitive reserve? A longitudinal application

    PubMed Central

    Zahodne, Laura B.; Manly, Jennifer J.; Brickman, Adam M.; Narkhede, Atul; Griffith, Erica Y.; Guzman, Vanessa A.; Schupf, Nicole; Stern, Yaakov

    2016-01-01

    Cognitive reserve describes the mismatch between brain integrity and cognitive performance. Older adults with high cognitive reserve are more resilient to age-related brain pathology. Traditionally, cognitive reserve is indexed indirectly via static proxy variables (e.g., years of education). More recently, cross-sectional studies have suggested that reserve can be expressed as residual variance in episodic memory performance that remains after accounting for demographic factors and brain pathology (whole brain, hippocampal, and white matter hyperintensity volumes). The present study extends these methods to a longitudinal framework in a community-based cohort of 244 older adults who underwent two comprehensive neuropsychological and structural magnetic resonance imaging sessions over 4.6 years. On average, residual memory variance decreased over time, consistent with the idea that cognitive reserve is depleted over time. Individual differences in change in residual memory variance predicted incident dementia, independent of baseline residual memory variance. Multiple-group latent difference score models revealed tighter coupling between brain and language changes among individuals with decreasing residual memory variance. These results suggest that changes in residual memory variance may capture a dynamic aspect of cognitive reserve and could be a useful way to summarize individual cognitive responses to brain changes. Change in residual memory variance among initially non-demented older adults was a better predictor of incident dementia than residual memory variance measured at one time-point. PMID:26348002

  1. 42 CFR 456.521 - Conditions for granting variance requests.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... SERVICES (CONTINUED) MEDICAL ASSISTANCE PROGRAMS UTILIZATION CONTROL Utilization Review Plans: FFP, Waivers, and Variances for Hospitals and Mental Hospitals Ur Plan: Remote Facility Variances from Time...

  2. 42 CFR 456.525 - Request for renewal of variance.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... SERVICES (CONTINUED) MEDICAL ASSISTANCE PROGRAMS UTILIZATION CONTROL Utilization Review Plans: FFP, Waivers, and Variances for Hospitals and Mental Hospitals Ur Plan: Remote Facility Variances from Time...

  3. 42 CFR 456.525 - Request for renewal of variance.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... SERVICES (CONTINUED) MEDICAL ASSISTANCE PROGRAMS UTILIZATION CONTROL Utilization Review Plans: FFP, Waivers, and Variances for Hospitals and Mental Hospitals Ur Plan: Remote Facility Variances from Time...

  4. Developing the Noncentrality Parameter for Calculating Group Sample Sizes in Heterogeneous Analysis of Variance

    ERIC Educational Resources Information Center

    Luh, Wei-Ming; Guo, Jiin-Huarng

    2011-01-01

    Sample size determination is an important issue in planning research. In the context of one-way fixed-effect analysis of variance, the conventional sample size formula cannot be applied for the heterogeneous variance cases. This study discusses the sample size requirement for the Welch test in the one-way fixed-effect analysis of variance with…

  5. 40 CFR 260.33 - Procedures for variances from classification as a solid waste, for variances to be classified as...

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... classification as a solid waste, for variances to be classified as a boiler, or for non-waste determinations. 260.33 Section 260.33 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) SOLID WASTES... from classification as a solid waste, for variances to be classified as a boiler, or for non-waste...

  6. 40 CFR 260.33 - Procedures for variances from classification as a solid waste, for variances to be classified as...

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... classification as a solid waste, for variances to be classified as a boiler, or for non-waste determinations. 260.33 Section 260.33 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) SOLID WASTES... from classification as a solid waste, for variances to be classified as a boiler, or for non-waste...

  7. Why risk is not variance: an expository note.

    PubMed

    Cox, Louis Anthony Tony

    2008-08-01

    Variance (or standard deviation) of return is widely used as a measure of risk in financial investment risk analysis applications, where mean-variance analysis is applied to calculate efficient frontiers and undominated portfolios. Why, then, do health, safety, and environmental (HS&E) and reliability engineering risk analysts insist on defining risk more flexibly, as being determined by probabilities and consequences, rather than simply by variances? This note suggests an answer by providing a simple proof that mean-variance decision making violates the principle that a rational decisionmaker should prefer higher to lower probabilities of receiving a fixed gain, all else being equal. Indeed, simply hypothesizing a continuous increasing indifference curve for mean-variance combinations at the origin is enough to imply that a decisionmaker must find unacceptable some prospects that offer a positive probability of gain and zero probability of loss. Unlike some previous analyses of limitations of variance as a risk metric, this expository note uses only simple mathematics and does not require the additional framework of von Neumann Morgenstern utility theory.

  8. The latitude dependence of the variance of zonally averaged quantities. [in polar meteorology with attention to geometrical effects of earth

    NASA Technical Reports Server (NTRS)

    North, G. R.; Bell, T. L.; Cahalan, R. F.; Moeng, F. J.

    1982-01-01

    Geometric characteristics of the spherical earth are shown to be responsible for the increase of variance with latitude of zonally averaged meteorological statistics. An analytic model is constructed to display the effect of a spherical geometry on zonal averages, employing a sphere labeled with radial unit vectors in a real, stochastic field expanded in complex spherical harmonics. The variance of a zonally averaged field is found to be expressible in terms of the spectrum of the vector field of the spherical harmonics. A maximum variance is then located at the poles, and the ratio of the variance to the zonally averaged grid-point variance, weighted by the cosine of the latitude, yields the zonal correlation typical of the latitude. An example is provided for the 500 mb level in the Northern Hemisphere compared to 15 years of data. Variance is determined to increase north of 60 deg latitude.

  9. A method to estimate the contribution of regional genetic associations to complex traits from summary association statistics.

    PubMed

    Pare, Guillaume; Mao, Shihong; Deng, Wei Q

    2016-06-08

    Despite considerable efforts, known genetic associations only explain a small fraction of predicted heritability. Regional associations combine information from multiple contiguous genetic variants and can improve variance explained at established association loci. However, regional associations are not easily amenable to estimation using summary association statistics because of sensitivity to linkage disequilibrium (LD). We now propose a novel method, LD Adjusted Regional Genetic Variance (LARGV), to estimate phenotypic variance explained by regional associations using summary statistics while accounting for LD. Our method is asymptotically equivalent to a multiple linear regression model when no interaction or haplotype effects are present. It has several applications, such as ranking of genetic regions according to variance explained or comparison of variance explained by two or more regions. Using height and BMI data from the Health Retirement Study (N = 7,776), we show that most genetic variance lies in a small proportion of the genome and that previously identified linkage peaks have higher than expected regional variance.

  10. Impact of an equality constraint on the class-specific residual variances in regression mixtures: A Monte Carlo simulation study

    PubMed Central

    Kim, Minjung; Lamont, Andrea E.; Jaki, Thomas; Feaster, Daniel; Howe, George; Van Horn, M. Lee

    2015-01-01

    Regression mixture models are a novel approach for modeling heterogeneous effects of predictors on an outcome. In the model building process residual variances are often disregarded and simplifying assumptions made without thorough examination of the consequences. This simulation study investigated the impact of an equality constraint on the residual variances across latent classes. We examine the consequence of constraining the residual variances on class enumeration (finding the true number of latent classes) and parameter estimates under a number of different simulation conditions meant to reflect the type of heterogeneity likely to exist in applied analyses. Results showed that bias in class enumeration increased as the difference in residual variances between the classes increased. Also, an inappropriate equality constraint on the residual variances greatly impacted estimated class sizes and showed the potential to greatly impact parameter estimates in each class. Results suggest that it is important to make assumptions about residual variances with care and to carefully report what assumptions were made. PMID:26139512

  11. A method to estimate the contribution of regional genetic associations to complex traits from summary association statistics

    PubMed Central

    Pare, Guillaume; Mao, Shihong; Deng, Wei Q.

    2016-01-01

    Despite considerable efforts, known genetic associations only explain a small fraction of predicted heritability. Regional associations combine information from multiple contiguous genetic variants and can improve variance explained at established association loci. However, regional associations are not easily amenable to estimation using summary association statistics because of sensitivity to linkage disequilibrium (LD). We now propose a novel method, LD Adjusted Regional Genetic Variance (LARGV), to estimate phenotypic variance explained by regional associations using summary statistics while accounting for LD. Our method is asymptotically equivalent to a multiple linear regression model when no interaction or haplotype effects are present. It has several applications, such as ranking of genetic regions according to variance explained or comparison of variance explained by two or more regions. Using height and BMI data from the Health Retirement Study (N = 7,776), we show that most genetic variance lies in a small proportion of the genome and that previously identified linkage peaks have higher than expected regional variance. PMID:27273519

  12. Environmental stress, inbreeding, and the nature of phenotypic and genetic variance in Drosophila melanogaster.

    PubMed Central

    Fowler, Kevin; Whitlock, Michael C

    2002-01-01

    Fifty-two lines of Drosophila melanogaster founded by single-pair population bottlenecks were used to study the effects of inbreeding and environmental stress on phenotypic variance, genetic variance and survivorship. Cold temperature and high density cause reduced survivorship, but these stresses do not cause repeatable changes in the phenotypic variance of most wing morphological traits. Wing area, however, does show increased phenotypic variance under both types of environmental stress. This increase is no greater in inbred than in outbred lines, showing that inbreeding does not increase the developmental effects of stress. Conversely, environmental stress does not increase the extent of inbreeding depression. Genetic variance is not correlated with environmental stress, although the amount of genetic variation varies significantly among environments and lines vary significantly in their response to environmental change. Drastic changes in the environment can cause changes in phenotypic and genetic variance, but not in a way reliably predicted by the notion of 'stress'. PMID:11934358

  13. Analysis of Wind Tunnel Polar Replicates Using the Modern Design of Experiments

    NASA Technical Reports Server (NTRS)

    Deloach, Richard; Micol, John R.

    2010-01-01

    The role of variance in a Modern Design of Experiments analysis of wind tunnel data is reviewed, with distinctions made between explained and unexplained variance. The partitioning of unexplained variance into systematic and random components is illustrated, with examples of the elusive systematic component provided for various types of real-world tests. The importance of detecting and defending against systematic unexplained variance in wind tunnel testing is discussed, and the random and systematic components of unexplained variance are examined for a representative wind tunnel data set acquired in a test in which a missile is used as a test article. The adverse impact of correlated (non-independent) experimental errors is described, and recommendations are offered for replication strategies that facilitate the quantification of random and systematic unexplained variance.

  14. A class of multi-period semi-variance portfolio for petroleum exploration and development

    NASA Astrophysics Data System (ADS)

    Guo, Qiulin; Li, Jianzhong; Zou, Caineng; Guo, Yujuan; Yan, Wei

    2012-10-01

    Variance is substituted by semi-variance in Markowitz's portfolio selection model. For dynamic valuation on exploration and development projects, one period portfolio selection is extended to multi-period. In this article, a class of multi-period semi-variance exploration and development portfolio model is formulated originally. Besides, a hybrid genetic algorithm, which makes use of the position displacement strategy of the particle swarm optimiser as a mutation operation, is applied to solve the multi-period semi-variance model. For this class of portfolio model, numerical results show that the mode is effective and feasible.

  15. 29 CFR 1905.10 - Variances and other relief under section 6(b)(6)(A).

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 29 Labor 5 2010-07-01 2010-07-01 false Variances and other relief under section 6(b)(6)(A). 1905... section 6(b)(6)(A). (a) Application for variance. Any employer, or class of employers, desiring a variance from a standard, or portion thereof, authorized by section 6(b)(6)(A) of the Act may file a written...

  16. A Cosmic Variance Cookbook

    NASA Astrophysics Data System (ADS)

    Moster, Benjamin P.; Somerville, Rachel S.; Newman, Jeffrey A.; Rix, Hans-Walter

    2011-04-01

    Deep pencil beam surveys (<1 deg2) are of fundamental importance for studying the high-redshift universe. However, inferences about galaxy population properties (e.g., the abundance of objects) are in practice limited by "cosmic variance." This is the uncertainty in observational estimates of the number density of galaxies arising from the underlying large-scale density fluctuations. This source of uncertainty can be significant, especially for surveys which cover only small areas and for massive high-redshift galaxies. Cosmic variance for a given galaxy population can be determined using predictions from cold dark matter theory and the galaxy bias. In this paper, we provide tools for experiment design and interpretation. For a given survey geometry, we present the cosmic variance of dark matter as a function of mean redshift \\bar{z} and redshift bin size Δz. Using a halo occupation model to predict galaxy clustering, we derive the galaxy bias as a function of mean redshift for galaxy samples of a given stellar mass range. In the linear regime, the cosmic variance of these galaxy samples is the product of the galaxy bias and the dark matter cosmic variance. We present a simple recipe using a fitting function to compute cosmic variance as a function of the angular dimensions of the field, \\bar{z}, Δz, and stellar mass m *. We also provide tabulated values and a software tool. The accuracy of the resulting cosmic variance estimates (δσ v /σ v ) is shown to be better than 20%. We find that for GOODS at \\bar{z}=2 and with Δz = 0.5, the relative cosmic variance of galaxies with m *>1011 M sun is ~38%, while it is ~27% for GEMS and ~12% for COSMOS. For galaxies of m * ~ 1010 M sun, the relative cosmic variance is ~19% for GOODS, ~13% for GEMS, and ~6% for COSMOS. This implies that cosmic variance is a significant source of uncertainty at \\bar{z}=2 for small fields and massive galaxies, while for larger fields and intermediate mass galaxies, cosmic variance is less serious.

  17. Quantifying cosmic variance

    NASA Astrophysics Data System (ADS)

    Driver, Simon P.; Robotham, Aaron S. G.

    2010-10-01

    We determine an expression for the cosmic variance of any `normal' galaxy survey based on examination of M* +/- 1 mag galaxies in the Sloan Digital Sky Survey (SDSS) Data Release 7 (DR7) data cube. We find that cosmic variance will depend on a number of factors principally: total survey volume, survey aspect ratio and whether the area surveyed is contiguous or comprising independent sightlines. As a rule of thumb cosmic variance falls below 10 per cent once a volume of 107h-30.7Mpc3 is surveyed for a single contiguous region with a 1:1 aspect ratio. Cosmic variance will be lower for higher aspect ratios and/or non-contiguous surveys. Extrapolating outside our test region we infer that cosmic variance in the entire SDSS DR7 main survey region is ~7 per cent to z < 0.1. The equation obtained from the SDSS DR7 region can be generalized to estimate the cosmic variance for any density measurement determined from normal galaxies (e.g. luminosity densities, stellar mass densities and cosmic star formation rates) within the volume range 103-107h-30.7Mpc3. We apply our equation to show that two sightlines are required to ensure that cosmic variance is <10 per cent in any ASKAP galaxy survey (divided into Δ z ~ 0.1 intervals, i.e. ~1Gyr intervals for z < 0.5). Likewise 10 MeerKAT sightlines will be required to meet the same conditions. GAMA, VVDS and zCOSMOS all suffer less than 10 per cent cosmic variance (~3-8 per cent) in Δ z intervals of 0.1, 0.25 and 0.5, respectively. Finally we show that cosmic variance is potentially at the 50-70 per cent level, or greater, in the Hubble Space Telescope (HST) Ultra Deep Field depending on assumptions as to the evolution of clustering. 100 or 10 independent sightlines will be required to reduce cosmic variance to a manageable level (<10 per cent) for HST ACS or HST WFC3 surveys, respectively (in Δ z ~ 1 intervals). Cosmic variance is therefore a significant factor in the z > 6 HST studies currently underway.

  18. Estimation of genetic connectedness diagnostics based on prediction errors without the prediction error variance-covariance matrix.

    PubMed

    Holmes, John B; Dodds, Ken G; Lee, Michael A

    2017-03-02

    An important issue in genetic evaluation is the comparability of random effects (breeding values), particularly between pairs of animals in different contemporary groups. This is usually referred to as genetic connectedness. While various measures of connectedness have been proposed in the literature, there is general agreement that the most appropriate measure is some function of the prediction error variance-covariance matrix. However, obtaining the prediction error variance-covariance matrix is computationally demanding for large-scale genetic evaluations. Many alternative statistics have been proposed that avoid the computational cost of obtaining the prediction error variance-covariance matrix, such as counts of genetic links between contemporary groups, gene flow matrices, and functions of the variance-covariance matrix of estimated contemporary group fixed effects. In this paper, we show that a correction to the variance-covariance matrix of estimated contemporary group fixed effects will produce the exact prediction error variance-covariance matrix averaged by contemporary group for univariate models in the presence of single or multiple fixed effects and one random effect. We demonstrate the correction for a series of models and show that approximations to the prediction error matrix based solely on the variance-covariance matrix of estimated contemporary group fixed effects are inappropriate in certain circumstances. Our method allows for the calculation of a connectedness measure based on the prediction error variance-covariance matrix by calculating only the variance-covariance matrix of estimated fixed effects. Since the number of fixed effects in genetic evaluation is usually orders of magnitudes smaller than the number of random effect levels, the computational requirements for our method should be reduced.

  19. Once upon Multivariate Analyses: When They Tell Several Stories about Biological Evolution.

    PubMed

    Renaud, Sabrina; Dufour, Anne-Béatrice; Hardouin, Emilie A; Ledevin, Ronan; Auffray, Jean-Christophe

    2015-01-01

    Geometric morphometrics aims to characterize of the geometry of complex traits. It is therefore by essence multivariate. The most popular methods to investigate patterns of differentiation in this context are (1) the Principal Component Analysis (PCA), which is an eigenvalue decomposition of the total variance-covariance matrix among all specimens; (2) the Canonical Variate Analysis (CVA, a.k.a. linear discriminant analysis (LDA) for more than two groups), which aims at separating the groups by maximizing the between-group to within-group variance ratio; (3) the between-group PCA (bgPCA) which investigates patterns of between-group variation, without standardizing by the within-group variance. Standardizing within-group variance, as performed in the CVA, distorts the relationships among groups, an effect that is particularly strong if the variance is similarly oriented in a comparable way in all groups. Such shared direction of main morphological variance may occur and have a biological meaning, for instance corresponding to the most frequent standing genetic variation in a population. Here we undertake a case study of the evolution of house mouse molar shape across various islands, based on the real dataset and simulations. We investigated how patterns of main variance influence the depiction of among-group differentiation according to the interpretation of the PCA, bgPCA and CVA. Without arguing about a method performing 'better' than another, it rather emerges that working on the total or between-group variance (PCA and bgPCA) will tend to put the focus on the role of direction of main variance as line of least resistance to evolution. Standardizing by the within-group variance (CVA), by dampening the expression of this line of least resistance, has the potential to reveal other relevant patterns of differentiation that may otherwise be blurred.

  20. Efficient design of cluster randomized trials with treatment-dependent costs and treatment-dependent unknown variances.

    PubMed

    van Breukelen, Gerard J P; Candel, Math J J M

    2018-06-10

    Cluster randomized trials evaluate the effect of a treatment on persons nested within clusters, where treatment is randomly assigned to clusters. Current equations for the optimal sample size at the cluster and person level assume that the outcome variances and/or the study costs are known and homogeneous between treatment arms. This paper presents efficient yet robust designs for cluster randomized trials with treatment-dependent costs and treatment-dependent unknown variances, and compares these with 2 practical designs. First, the maximin design (MMD) is derived, which maximizes the minimum efficiency (minimizes the maximum sampling variance) of the treatment effect estimator over a range of treatment-to-control variance ratios. The MMD is then compared with the optimal design for homogeneous variances and costs (balanced design), and with that for homogeneous variances and treatment-dependent costs (cost-considered design). The results show that the balanced design is the MMD if the treatment-to control cost ratio is the same at both design levels (cluster, person) and within the range for the treatment-to-control variance ratio. It still is highly efficient and better than the cost-considered design if the cost ratio is within the range for the squared variance ratio. Outside that range, the cost-considered design is better and highly efficient, but it is not the MMD. An example shows sample size calculation for the MMD, and the computer code (SPSS and R) is provided as supplementary material. The MMD is recommended for trial planning if the study costs are treatment-dependent and homogeneity of variances cannot be assumed. © 2018 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

  1. Genetic and environmental factors affecting birth size variation: a pooled individual-based analysis of secular trends and global geographical differences using 26 twin cohorts.

    PubMed

    Yokoyama, Yoshie; Jelenkovic, Aline; Hur, Yoon-Mi; Sund, Reijo; Fagnani, Corrado; Stazi, Maria A; Brescianini, Sonia; Ji, Fuling; Ning, Feng; Pang, Zengchang; Knafo-Noam, Ariel; Mankuta, David; Abramson, Lior; Rebato, Esther; Hopper, John L; Cutler, Tessa L; Saudino, Kimberly J; Nelson, Tracy L; Whitfield, Keith E; Corley, Robin P; Huibregtse, Brooke M; Derom, Catherine A; Vlietinck, Robert F; Loos, Ruth J F; Llewellyn, Clare H; Fisher, Abigail; Bjerregaard-Andersen, Morten; Beck-Nielsen, Henning; Sodemann, Morten; Krueger, Robert F; McGue, Matt; Pahlen, Shandell; Bartels, Meike; van Beijsterveldt, Catharina E M; Willemsen, Gonneke; Harris, Jennifer R; Brandt, Ingunn; Nilsen, Thomas S; Craig, Jeffrey M; Saffery, Richard; Dubois, Lise; Boivin, Michel; Brendgen, Mara; Dionne, Ginette; Vitaro, Frank; Haworth, Claire M A; Plomin, Robert; Bayasgalan, Gombojav; Narandalai, Danshiitsoodol; Rasmussen, Finn; Tynelius, Per; Tarnoki, Adam D; Tarnoki, David L; Ooki, Syuichi; Rose, Richard J; Pietiläinen, Kirsi H; Sørensen, Thorkild I A; Boomsma, Dorret I; Kaprio, Jaakko; Silventoinen, Karri

    2018-05-19

    The genetic architecture of birth size may differ geographically and over time. We examined differences in the genetic and environmental contributions to birthweight, length and ponderal index (PI) across geographical-cultural regions (Europe, North America and Australia, and East Asia) and across birth cohorts, and how gestational age modifies these effects. Data from 26 twin cohorts in 16 countries including 57 613 monozygotic and dizygotic twin pairs were pooled. Genetic and environmental variations of birth size were estimated using genetic structural equation modelling. The variance of birthweight and length was predominantly explained by shared environmental factors, whereas the variance of PI was explained both by shared and unique environmental factors. Genetic variance contributing to birth size was small. Adjusting for gestational age decreased the proportions of shared environmental variance and increased the propositions of unique environmental variance. Genetic variance was similar in the geographical-cultural regions, but shared environmental variance was smaller in East Asia than in Europe and North America and Australia. The total variance and shared environmental variance of birth length and PI were greater from the birth cohort 1990-99 onwards compared with the birth cohorts from 1970-79 to 1980-89. The contribution of genetic factors to birth size is smaller than that of shared environmental factors, which is partly explained by gestational age. Shared environmental variances of birth length and PI were greater in the latest birth cohorts and differed also across geographical-cultural regions. Shared environmental factors are important when explaining differences in the variation of birth size globally and over time.

  2. Adaptive Prior Variance Calibration in the Bayesian Continual Reassessment Method

    PubMed Central

    Zhang, Jin; Braun, Thomas M.; Taylor, Jeremy M.G.

    2012-01-01

    Use of the Continual Reassessment Method (CRM) and other model-based approaches to design in Phase I clinical trials has increased due to the ability of the CRM to identify the maximum tolerated dose (MTD) better than the 3+3 method. However, the CRM can be sensitive to the variance selected for the prior distribution of the model parameter, especially when a small number of patients are enrolled. While methods have emerged to adaptively select skeletons and to calibrate the prior variance only at the beginning of a trial, there has not been any approach developed to adaptively calibrate the prior variance throughout a trial. We propose three systematic approaches to adaptively calibrate the prior variance during a trial and compare them via simulation to methods proposed to calibrate the variance at the beginning of a trial. PMID:22987660

  3. Portfolio optimization with mean-variance model

    NASA Astrophysics Data System (ADS)

    Hoe, Lam Weng; Siew, Lam Weng

    2016-06-01

    Investors wish to achieve the target rate of return at the minimum level of risk in their investment. Portfolio optimization is an investment strategy that can be used to minimize the portfolio risk and can achieve the target rate of return. The mean-variance model has been proposed in portfolio optimization. The mean-variance model is an optimization model that aims to minimize the portfolio risk which is the portfolio variance. The objective of this study is to construct the optimal portfolio using the mean-variance model. The data of this study consists of weekly returns of 20 component stocks of FTSE Bursa Malaysia Kuala Lumpur Composite Index (FBMKLCI). The results of this study show that the portfolio composition of the stocks is different. Moreover, investors can get the return at minimum level of risk with the constructed optimal mean-variance portfolio.

  4. Stratum variance estimation for sample allocation in crop surveys. [Great Plains Corridor

    NASA Technical Reports Server (NTRS)

    Perry, C. R., Jr.; Chhikara, R. S. (Principal Investigator)

    1980-01-01

    The problem of determining stratum variances needed in achieving an optimum sample allocation for crop surveys by remote sensing is investigated by considering an approach based on the concept of stratum variance as a function of the sampling unit size. A methodology using the existing and easily available information of historical crop statistics is developed for obtaining initial estimates of tratum variances. The procedure is applied to estimate stratum variances for wheat in the U.S. Great Plains and is evaluated based on the numerical results thus obtained. It is shown that the proposed technique is viable and performs satisfactorily, with the use of a conservative value for the field size and the crop statistics from the small political subdivision level, when the estimated stratum variances were compared to those obtained using the LANDSAT data.

  5. Increased gender variance in autism spectrum disorders and attention deficit hyperactivity disorder.

    PubMed

    Strang, John F; Kenworthy, Lauren; Dominska, Aleksandra; Sokoloff, Jennifer; Kenealy, Laura E; Berl, Madison; Walsh, Karin; Menvielle, Edgardo; Slesaransky-Poe, Graciela; Kim, Kyung-Eun; Luong-Tran, Caroline; Meagher, Haley; Wallace, Gregory L

    2014-11-01

    Evidence suggests over-representation of autism spectrum disorders (ASDs) and behavioral difficulties among people referred for gender issues, but rates of the wish to be the other gender (gender variance) among different neurodevelopmental disorders are unknown. This chart review study explored rates of gender variance as reported by parents on the Child Behavior Checklist (CBCL) in children with different neurodevelopmental disorders: ASD (N = 147, 24 females and 123 males), attention deficit hyperactivity disorder (ADHD; N = 126, 38 females and 88 males), or a medical neurodevelopmental disorder (N = 116, 57 females and 59 males), were compared with two non-referred groups [control sample (N = 165, 61 females and 104 males) and non-referred participants in the CBCL standardization sample (N = 1,605, 754 females and 851 males)]. Significantly greater proportions of participants with ASD (5.4%) or ADHD (4.8%) had parent reported gender variance than in the combined medical group (1.7%) or non-referred comparison groups (0-0.7%). As compared to non-referred comparisons, participants with ASD were 7.59 times more likely to express gender variance; participants with ADHD were 6.64 times more likely to express gender variance. The medical neurodevelopmental disorder group did not differ from non-referred samples in likelihood to express gender variance. Gender variance was related to elevated emotional symptoms in ADHD, but not in ASD. After accounting for sex ratio differences between the neurodevelopmental disorder and non-referred comparison groups, gender variance occurred equally in females and males.

  6. 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.

  7. Trait and State Variance in Oppositional Defiant Disorder Symptoms: A Multi-Source Investigation with Spanish Children

    PubMed Central

    Preszler, Jonathan; Burns, G. Leonard; Litson, Kaylee; Geiser, Christian; Servera, Mateu

    2016-01-01

    The objective was to determine and compare the trait and state components of oppositional defiant disorder (ODD) symptom reports across multiple informants. Mothers, fathers, primary teachers, and secondary teachers rated the occurrence of the ODD symptoms in 810 Spanish children (55% boys) on two occasions (end first and second grades). Single source latent state-trait (LST) analyses revealed that ODD symptom ratings from all four sources showed more trait (M = 63%) than state residual (M = 37%) variance. A multiple source LST analysis revealed substantial convergent validity of mothers’ and fathers’ trait variance components (M = 68%) and modest convergent validity of state residual variance components (M = 35%). In contrast, primary and secondary teachers showed low convergent validity relative to mothers for trait variance (Ms = 31%, 32%, respectively) and essentially zero convergent validity relative to mothers for state residual variance (Ms = 1%, 3%, respectively). Although ODD symptom ratings reflected slightly more trait- than state-like constructs within each of the four sources separately across occasions, strong convergent validity for the trait variance only occurred within settings (i.e., mothers with fathers; primary with secondary teachers) with the convergent validity of the trait and state residual variance components being low to non-existent across settings. These results suggest that ODD symptom reports are trait-like across time for individual sources with this trait variance, however, only having convergent validity within settings. Implications for assessment of ODD are discussed. PMID:27148784

  8. Stress in junior enlisted air force women with and without children.

    PubMed

    Hopkins-Chadwick, Denise L; Ryan-Wenger, Nancy

    2009-04-01

    The objective was to determine if there are differences between young enlisted military women with and without preschool children on role strain, stress, health, and military career aspiration and to identify the best predictors of these variables. The study used a cross-sectional descriptive design of 50 junior Air Force women with preschool children and 50 women without children. There were no differences between women with and without children in role strain, stress, health, and military career aspiration. In all women, higher stress was moderately predictive of higher role strain (39.9% of variance explained) but a poor predictor of career aspiration (3.8% of variance explained). Lower mental health scores were predicted by high stress symptoms (27.9% of variance explained), low military career aspiration (4.1% of variance explained), high role strain (4.0% of variance explained), and being non-White (3.9% of variance explained). Aspiration for a military career was predicted by high perceived availability of military resources (16.8% of variance explained), low family of origin socioeconomic status (4.5% of variance explained), and better mental health status (3.3% of variance explained). Contrary to theoretical expectations, in this sample, motherhood was not a significant variable. Increased role strain, stress, and decreased health as well as decreased military career aspiration were evident in both groups and may have more to do with individual coping skills and other unmeasured resources. More research is needed to determine what nursing interventions are needed to best support both groups of women.

  9. Estimation of Additive, Dominance, and Imprinting Genetic Variance Using Genomic Data

    PubMed Central

    Lopes, Marcos S.; Bastiaansen, John W. M.; Janss, Luc; Knol, Egbert F.; Bovenhuis, Henk

    2015-01-01

    Traditionally, exploration of genetic variance in humans, plants, and livestock species has been limited mostly to the use of additive effects estimated using pedigree data. However, with the development of dense panels of single-nucleotide polymorphisms (SNPs), the exploration of genetic variation of complex traits is moving from quantifying the resemblance between family members to the dissection of genetic variation at individual loci. With SNPs, we were able to quantify the contribution of additive, dominance, and imprinting variance to the total genetic variance by using a SNP regression method. The method was validated in simulated data and applied to three traits (number of teats, backfat, and lifetime daily gain) in three purebred pig populations. In simulated data, the estimates of additive, dominance, and imprinting variance were very close to the simulated values. In real data, dominance effects account for a substantial proportion of the total genetic variance (up to 44%) for these traits in these populations. The contribution of imprinting to the total phenotypic variance of the evaluated traits was relatively small (1–3%). Our results indicate a strong relationship between additive variance explained per chromosome and chromosome length, which has been described previously for other traits in other species. We also show that a similar linear relationship exists for dominance and imprinting variance. These novel results improve our understanding of the genetic architecture of the evaluated traits and shows promise to apply the SNP regression method to other traits and species, including human diseases. PMID:26438289

  10. On the additive and dominant variance and covariance of individuals within the genomic selection scope.

    PubMed

    Vitezica, Zulma G; Varona, Luis; Legarra, Andres

    2013-12-01

    Genomic evaluation models can fit additive and dominant SNP effects. Under quantitative genetics theory, additive or "breeding" values of individuals are generated by substitution effects, which involve both "biological" additive and dominant effects of the markers. Dominance deviations include only a portion of the biological dominant effects of the markers. Additive variance includes variation due to the additive and dominant effects of the markers. We describe a matrix of dominant genomic relationships across individuals, D, which is similar to the G matrix used in genomic best linear unbiased prediction. This matrix can be used in a mixed-model context for genomic evaluations or to estimate dominant and additive variances in the population. From the "genotypic" value of individuals, an alternative parameterization defines additive and dominance as the parts attributable to the additive and dominant effect of the markers. This approach underestimates the additive genetic variance and overestimates the dominance variance. Transforming the variances from one model into the other is trivial if the distribution of allelic frequencies is known. We illustrate these results with mouse data (four traits, 1884 mice, and 10,946 markers) and simulated data (2100 individuals and 10,000 markers). Variance components were estimated correctly in the model, considering breeding values and dominance deviations. For the model considering genotypic values, the inclusion of dominant effects biased the estimate of additive variance. Genomic models were more accurate for the estimation of variance components than their pedigree-based counterparts.

  11. Meta-analysis with missing study-level sample variance data.

    PubMed

    Chowdhry, Amit K; Dworkin, Robert H; McDermott, Michael P

    2016-07-30

    We consider a study-level meta-analysis with a normally distributed outcome variable and possibly unequal study-level variances, where the object of inference is the difference in means between a treatment and control group. A common complication in such an analysis is missing sample variances for some studies. A frequently used approach is to impute the weighted (by sample size) mean of the observed variances (mean imputation). Another approach is to include only those studies with variances reported (complete case analysis). Both mean imputation and complete case analysis are only valid under the missing-completely-at-random assumption, and even then the inverse variance weights produced are not necessarily optimal. We propose a multiple imputation method employing gamma meta-regression to impute the missing sample variances. Our method takes advantage of study-level covariates that may be used to provide information about the missing data. Through simulation studies, we show that multiple imputation, when the imputation model is correctly specified, is superior to competing methods in terms of confidence interval coverage probability and type I error probability when testing a specified group difference. Finally, we describe a similar approach to handling missing variances in cross-over studies. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  12. Noise and drift analysis of non-equally spaced timing data

    NASA Technical Reports Server (NTRS)

    Vernotte, F.; Zalamansky, G.; Lantz, E.

    1994-01-01

    Generally, it is possible to obtain equally spaced timing data from oscillators. The measurement of the drifts and noises affecting oscillators is then performed by using a variance (Allan variance, modified Allan variance, or time variance) or a system of several variances (multivariance method). However, in some cases, several samples, or even several sets of samples, are missing. In the case of millisecond pulsar timing data, for instance, observations are quite irregularly spaced in time. Nevertheless, since some observations are very close together (one minute) and since the timing data sequence is very long (more than ten years), information on both short-term and long-term stability is available. Unfortunately, a direct variance analysis is not possible without interpolating missing data. Different interpolation algorithms (linear interpolation, cubic spline) are used to calculate variances in order to verify that they neither lose information nor add erroneous information. A comparison of the results of the different algorithms is given. Finally, the multivariance method was adapted to the measurement sequence of the millisecond pulsar timing data: the responses of each variance of the system are calculated for each type of noise and drift, with the same missing samples as in the pulsar timing sequence. An estimation of precision, dynamics, and separability of this method is given.

  13. Comparing estimates of genetic variance across different relationship models.

    PubMed

    Legarra, Andres

    2016-02-01

    Use of relationships between individuals to estimate genetic variances and heritabilities via mixed models is standard practice in human, plant and livestock genetics. Different models or information for relationships may give different estimates of genetic variances. However, comparing these estimates across different relationship models is not straightforward as the implied base populations differ between relationship models. In this work, I present a method to compare estimates of variance components across different relationship models. I suggest referring genetic variances obtained using different relationship models to the same reference population, usually a set of individuals in the population. Expected genetic variance of this population is the estimated variance component from the mixed model times a statistic, Dk, which is the average self-relationship minus the average (self- and across-) relationship. For most typical models of relationships, Dk is close to 1. However, this is not true for very deep pedigrees, for identity-by-state relationships, or for non-parametric kernels, which tend to overestimate the genetic variance and the heritability. Using mice data, I show that heritabilities from identity-by-state and kernel-based relationships are overestimated. Weighting these estimates by Dk scales them to a base comparable to genomic or pedigree relationships, avoiding wrong comparisons, for instance, "missing heritabilities". Copyright © 2015 Elsevier Inc. All rights reserved.

  14. Aquatic community structure in Mediterranean edge-of-field waterbodies as explained by environmental factors and the presence of pesticide mixtures.

    PubMed

    Pereira, Ana Santos; Dâmaso-Rodrigues, Maria Luísa; Amorim, Ana; Daam, Michiel A; Cerejeira, Maria José

    2018-06-16

    Studies addressing the predicted effects of pesticides in combination with abiotic and biotic factors on aquatic biota in ditches associated with typical Mediterranean agroecosystems are scarce. The current study aimed to evaluate the predicted effects of pesticides along with environmental factors and biota interactions on macroinvertebrate, zooplankton and phytoplankton community compositions in ditches adjacent to Portuguese maize and tomato crop areas. Data was analysed with the variance partitioning procedure based on redundancy analysis (RDA). The total variance in biological community composition was divided into the variance explained by the multi-substance potentially affected fraction [(msPAF) arthropods and primary producers], environmental factors (water chemistry parameters), biotic interactions, shared variance, and unexplained variance. The total explained variance reached 39.4% and the largest proportion of this explained variance was attributed to msPAF (23.7%). When each group (phytoplankton, zooplankton and macroinvertebrates) was analysed separately, biota interactions and environmental factors explained the largest proportion of variance. Results of this study indicate that besides the presence of pesticide mixtures, environmental factors and biotic interactions also considerably influence field freshwater communities. Subsequently, to increase our understanding of the risk of pesticide mixtures on ecosystem communities in edge-of-field water bodies, variations in environmental and biological factors should also be considered.

  15. Estimating integrated variance in the presence of microstructure noise using linear regression

    NASA Astrophysics Data System (ADS)

    Holý, Vladimír

    2017-07-01

    Using financial high-frequency data for estimation of integrated variance of asset prices is beneficial but with increasing number of observations so-called microstructure noise occurs. This noise can significantly bias the realized variance estimator. We propose a method for estimation of the integrated variance robust to microstructure noise as well as for testing the presence of the noise. Our method utilizes linear regression in which realized variances estimated from different data subsamples act as dependent variable while the number of observations act as explanatory variable. We compare proposed estimator with other methods on simulated data for several microstructure noise structures.

  16. RR-Interval variance of electrocardiogram for atrial fibrillation detection

    NASA Astrophysics Data System (ADS)

    Nuryani, N.; Solikhah, M.; Nugoho, A. S.; Afdala, A.; Anzihory, E.

    2016-11-01

    Atrial fibrillation is a serious heart problem originated from the upper chamber of the heart. The common indication of atrial fibrillation is irregularity of R peak-to-R-peak time interval, which is shortly called RR interval. The irregularity could be represented using variance or spread of RR interval. This article presents a system to detect atrial fibrillation using variances. Using clinical data of patients with atrial fibrillation attack, it is shown that the variance of electrocardiographic RR interval are higher during atrial fibrillation, compared to the normal one. Utilizing a simple detection technique and variances of RR intervals, we find a good performance of atrial fibrillation detection.

  17. Analytic variance estimates of Swank and Fano factors

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

    Gutierrez, Benjamin; Badano, Aldo; Samuelson, Frank, E-mail: frank.samuelson@fda.hhs.gov

    Purpose: Variance estimates for detector energy resolution metrics can be used as stopping criteria in Monte Carlo simulations for the purpose of ensuring a small uncertainty of those metrics and for the design of variance reduction techniques. Methods: The authors derive an estimate for the variance of two energy resolution metrics, the Swank factor and the Fano factor, in terms of statistical moments that can be accumulated without significant computational overhead. The authors examine the accuracy of these two estimators and demonstrate how the estimates of the coefficient of variation of the Swank and Fano factors behave with data frommore » a Monte Carlo simulation of an indirect x-ray imaging detector. Results: The authors' analyses suggest that the accuracy of their variance estimators is appropriate for estimating the actual variances of the Swank and Fano factors for a variety of distributions of detector outputs. Conclusions: The variance estimators derived in this work provide a computationally convenient way to estimate the error or coefficient of variation of the Swank and Fano factors during Monte Carlo simulations of radiation imaging systems.« less

  18. An application of the LC-LSTM framework to the self-esteem instability case.

    PubMed

    Alessandri, Guido; Vecchione, Michele; Donnellan, Brent M; Tisak, John

    2013-10-01

    The present research evaluates the stability of self-esteem as assessed by a daily version of the Rosenberg (Society and the adolescent self-image, Princeton University Press, Princeton, 1965) general self-esteem scale (RGSE). The scale was administered to 391 undergraduates for five consecutive days. The longitudinal data were analyzed using the integrated LC-LSTM framework that allowed us to evaluate: (1) the measurement invariance of the RGSE, (2) its stability and change across the 5-day assessment period, (3) the amount of variance attributable to stable and transitory latent factors, and (4) the criterion-related validity of these factors. Results provided evidence for measurement invariance, mean-level stability, and rank-order stability of daily self-esteem. Latent state-trait analyses revealed that variances in scores of the RGSE can be decomposed into six components: stable self-esteem (40 %), ephemeral (or temporal-state) variance (36 %), stable negative method variance (9 %), stable positive method variance (4 %), specific variance (1 %) and random error variance (10 %). Moreover, latent factors associated with daily self-esteem were associated with measures of depression, implicit self-esteem, and grade point average.

  19. Impact of an equality constraint on the class-specific residual variances in regression mixtures: A Monte Carlo simulation study.

    PubMed

    Kim, Minjung; Lamont, Andrea E; Jaki, Thomas; Feaster, Daniel; Howe, George; Van Horn, M Lee

    2016-06-01

    Regression mixture models are a novel approach to modeling the heterogeneous effects of predictors on an outcome. In the model-building process, often residual variances are disregarded and simplifying assumptions are made without thorough examination of the consequences. In this simulation study, we investigated the impact of an equality constraint on the residual variances across latent classes. We examined the consequences of constraining the residual variances on class enumeration (finding the true number of latent classes) and on the parameter estimates, under a number of different simulation conditions meant to reflect the types of heterogeneity likely to exist in applied analyses. The results showed that bias in class enumeration increased as the difference in residual variances between the classes increased. Also, an inappropriate equality constraint on the residual variances greatly impacted on the estimated class sizes and showed the potential to greatly affect the parameter estimates in each class. These results suggest that it is important to make assumptions about residual variances with care and to carefully report what assumptions are made.

  20. Is Romantic Desire Predictable? Machine Learning Applied to Initial Romantic Attraction.

    PubMed

    Joel, Samantha; Eastwick, Paul W; Finkel, Eli J

    2017-10-01

    Matchmaking companies and theoretical perspectives on close relationships suggest that initial attraction is, to some extent, a product of two people's self-reported traits and preferences. We used machine learning to test how well such measures predict people's overall tendencies to romantically desire other people (actor variance) and to be desired by other people (partner variance), as well as people's desire for specific partners above and beyond actor and partner variance (relationship variance). In two speed-dating studies, romantically unattached individuals completed more than 100 self-report measures about traits and preferences that past researchers have identified as being relevant to mate selection. Each participant met each opposite-sex participant attending a speed-dating event for a 4-min speed date. Random forests models predicted 4% to 18% of actor variance and 7% to 27% of partner variance; crucially, however, they were unable to predict relationship variance using any combination of traits and preferences reported before the dates. These results suggest that compatibility elements of human mating are challenging to predict before two people meet.

  1. Measuring self-rated productivity: factor structure and variance component analysis of the Health and Work Questionnaire.

    PubMed

    von Thiele Schwarz, Ulrica; Sjöberg, Anders; Hasson, Henna; Tafvelin, Susanne

    2014-12-01

    To test the factor structure and variance components of the productivity subscales of the Health and Work Questionnaire (HWQ). A total of 272 individuals from one company answered the HWQ scale, including three dimensions (efficiency, quality, and quantity) that the respondent rated from three perspectives: their own, their supervisor's, and their coworkers'. A confirmatory factor analysis was performed, and common and unique variance components evaluated. A common factor explained 81% of the variance (reliability 0.95). All dimensions and rater perspectives contributed with unique variance. The final model provided a perfect fit to the data. Efficiency, quality, and quantity and three rater perspectives are valid parts of the self-rated productivity measurement model, but with a large common factor. Thus, the HWQ can be analyzed either as one factor or by extracting the unique variance for each subdimension.

  2. Applications of non-parametric statistics and analysis of variance on sample variances

    NASA Technical Reports Server (NTRS)

    Myers, R. H.

    1981-01-01

    Nonparametric methods that are available for NASA-type applications are discussed. An attempt will be made here to survey what can be used, to attempt recommendations as to when each would be applicable, and to compare the methods, when possible, with the usual normal-theory procedures that are avavilable for the Gaussion analog. It is important here to point out the hypotheses that are being tested, the assumptions that are being made, and limitations of the nonparametric procedures. The appropriateness of doing analysis of variance on sample variances are also discussed and studied. This procedure is followed in several NASA simulation projects. On the surface this would appear to be reasonably sound procedure. However, difficulties involved center around the normality problem and the basic homogeneous variance assumption that is mase in usual analysis of variance problems. These difficulties discussed and guidelines given for using the methods.

  3. Variance analysis of forecasted streamflow maxima in a wet temperate climate

    NASA Astrophysics Data System (ADS)

    Al Aamery, Nabil; Fox, James F.; Snyder, Mark; Chandramouli, Chandra V.

    2018-05-01

    Coupling global climate models, hydrologic models and extreme value analysis provides a method to forecast streamflow maxima, however the elusive variance structure of the results hinders confidence in application. Directly correcting the bias of forecasts using the relative change between forecast and control simulations has been shown to marginalize hydrologic uncertainty, reduce model bias, and remove systematic variance when predicting mean monthly and mean annual streamflow, prompting our investigation for maxima streamflow. We assess the variance structure of streamflow maxima using realizations of emission scenario, global climate model type and project phase, downscaling methods, bias correction, extreme value methods, and hydrologic model inputs and parameterization. Results show that the relative change of streamflow maxima was not dependent on systematic variance from the annual maxima versus peak over threshold method applied, albeit we stress that researchers strictly adhere to rules from extreme value theory when applying the peak over threshold method. Regardless of which method is applied, extreme value model fitting does add variance to the projection, and the variance is an increasing function of the return period. Unlike the relative change of mean streamflow, results show that the variance of the maxima's relative change was dependent on all climate model factors tested as well as hydrologic model inputs and calibration. Ensemble projections forecast an increase of streamflow maxima for 2050 with pronounced forecast standard error, including an increase of +30(±21), +38(±34) and +51(±85)% for 2, 20 and 100 year streamflow events for the wet temperate region studied. The variance of maxima projections was dominated by climate model factors and extreme value analyses.

  4. Variance partitioning of stream diatom, fish, and invertebrate indicators of biological condition

    USGS Publications Warehouse

    Zuellig, Robert E.; Carlisle, Daren M.; Meador, Michael R.; Potapova, Marina

    2012-01-01

    Stream indicators used to make assessments of biological condition are influenced by many possible sources of variability. To examine this issue, we used multiple-year and multiple-reach diatom, fish, and invertebrate data collected from 20 least-disturbed and 46 developed stream segments between 1993 and 2004 as part of the US Geological Survey National Water Quality Assessment Program. We used a variance-component model to summarize the relative and absolute magnitude of 4 variance components (among-site, among-year, site × year interaction, and residual) in indicator values (observed/expected ratio [O/E] and regional multimetric indices [MMI]) among assemblages and between basin types (least-disturbed and developed). We used multiple-reach samples to evaluate discordance in site assessments of biological condition caused by sampling variability. Overall, patterns in variance partitioning were similar among assemblages and basin types with one exception. Among-site variance dominated the relative contribution to the total variance (64–80% of total variance), residual variance (sampling variance) accounted for more variability (8–26%) than interaction variance (5–12%), and among-year variance was always negligible (0–0.2%). The exception to this general pattern was for invertebrates at least-disturbed sites where variability in O/E indicators was partitioned between among-site and residual (sampling) variance (among-site  =  36%, residual  =  64%). This pattern was not observed for fish and diatom indicators (O/E and regional MMI). We suspect that unexplained sampling variability is what largely remained after the invertebrate indicators (O/E predictive models) had accounted for environmental differences among least-disturbed sites. The influence of sampling variability on discordance of within-site assessments was assemblage or basin-type specific. Discordance among assessments was nearly 2× greater in developed basins (29–31%) than in least-disturbed sites (15–16%) for invertebrates and diatoms, whereas discordance among assessments based on fish did not differ between basin types (least-disturbed  =  16%, developed  =  17%). Assessments made using invertebrate and diatom indicators from a single reach disagreed with other samples collected within the same stream segment nearly ⅓ of the time in developed basins, compared to ⅙ for all other cases.

  5. The patterns of genomic variances and covariances across genome for milk production traits between Chinese and Nordic Holstein populations.

    PubMed

    Li, Xiujin; Lund, Mogens Sandø; Janss, Luc; Wang, Chonglong; Ding, Xiangdong; Zhang, Qin; Su, Guosheng

    2017-03-15

    With the development of SNP chips, SNP information provides an efficient approach to further disentangle different patterns of genomic variances and covariances across the genome for traits of interest. Due to the interaction between genotype and environment as well as possible differences in genetic background, it is reasonable to treat the performances of a biological trait in different populations as different but genetic correlated traits. In the present study, we performed an investigation on the patterns of region-specific genomic variances, covariances and correlations between Chinese and Nordic Holstein populations for three milk production traits. Variances and covariances between Chinese and Nordic Holstein populations were estimated for genomic regions at three different levels of genome region (all SNP as one region, each chromosome as one region and every 100 SNP as one region) using a novel multi-trait random regression model which uses latent variables to model heterogeneous variance and covariance. In the scenario of the whole genome as one region, the genomic variances, covariances and correlations obtained from the new multi-trait Bayesian method were comparable to those obtained from a multi-trait GBLUP for all the three milk production traits. In the scenario of each chromosome as one region, BTA 14 and BTA 5 accounted for very large genomic variance, covariance and correlation for milk yield and fat yield, whereas no specific chromosome showed very large genomic variance, covariance and correlation for protein yield. In the scenario of every 100 SNP as one region, most regions explained <0.50% of genomic variance and covariance for milk yield and fat yield, and explained <0.30% for protein yield, while some regions could present large variance and covariance. Although overall correlations between two populations for the three traits were positive and high, a few regions still showed weakly positive or highly negative genomic correlations for milk yield and fat yield. The new multi-trait Bayesian method using latent variables to model heterogeneous variance and covariance could work well for estimating the genomic variances and covariances for all genome regions simultaneously. Those estimated genomic parameters could be useful to improve the genomic prediction accuracy for Chinese and Nordic Holstein populations using a joint reference data in the future.

  6. Direct and indirect genetic and fine-scale location effects on breeding date in song sparrows.

    PubMed

    Germain, Ryan R; Wolak, Matthew E; Arcese, Peter; Losdat, Sylvain; Reid, Jane M

    2016-11-01

    Quantifying direct and indirect genetic effects of interacting females and males on variation in jointly expressed life-history traits is central to predicting microevolutionary dynamics. However, accurately estimating sex-specific additive genetic variances in such traits remains difficult in wild populations, especially if related individuals inhabit similar fine-scale environments. Breeding date is a key life-history trait that responds to environmental phenology and mediates individual and population responses to environmental change. However, no studies have estimated female (direct) and male (indirect) additive genetic and inbreeding effects on breeding date, and estimated the cross-sex genetic correlation, while simultaneously accounting for fine-scale environmental effects of breeding locations, impeding prediction of microevolutionary dynamics. We fitted animal models to 38 years of song sparrow (Melospiza melodia) phenology and pedigree data to estimate sex-specific additive genetic variances in breeding date, and the cross-sex genetic correlation, thereby estimating the total additive genetic variance while simultaneously estimating sex-specific inbreeding depression. We further fitted three forms of spatial animal model to explicitly estimate variance in breeding date attributable to breeding location, overlap among breeding locations and spatial autocorrelation. We thereby quantified fine-scale location variances in breeding date and quantified the degree to which estimating such variances affected the estimated additive genetic variances. The non-spatial animal model estimated nonzero female and male additive genetic variances in breeding date (sex-specific heritabilities: 0·07 and 0·02, respectively) and a strong, positive cross-sex genetic correlation (0·99), creating substantial total additive genetic variance (0·18). Breeding date varied with female, but not male inbreeding coefficient, revealing direct, but not indirect, inbreeding depression. All three spatial animal models estimated small location variance in breeding date, but because relatedness and breeding location were virtually uncorrelated, modelling location variance did not alter the estimated additive genetic variances. Our results show that sex-specific additive genetic effects on breeding date can be strongly positively correlated, which would affect any predicted rates of microevolutionary change in response to sexually antagonistic or congruent selection. Further, we show that inbreeding effects on breeding date can also be sex specific and that genetic effects can exceed phenotypic variation stemming from fine-scale location-based variation within a wild population. © 2016 The Authors. Journal of Animal Ecology © 2016 British Ecological Society.

  7. Optimal control of LQG problem with an explicit trade-off between mean and variance

    NASA Astrophysics Data System (ADS)

    Qian, Fucai; Xie, Guo; Liu, Ding; Xie, Wenfang

    2011-12-01

    For discrete-time linear-quadratic Gaussian (LQG) control problems, a utility function on the expectation and the variance of the conventional performance index is considered. The utility function is viewed as an overall objective of the system and can perform the optimal trade-off between the mean and the variance of performance index. The nonlinear utility function is first converted into an auxiliary parameters optimisation problem about the expectation and the variance. Then an optimal closed-loop feedback controller for the nonseparable mean-variance minimisation problem is designed by nonlinear mathematical programming. Finally, simulation results are given to verify the algorithm's effectiveness obtained in this article.

  8. flowVS: channel-specific variance stabilization in flow cytometry

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

    Azad, Ariful; Rajwa, Bartek; Pothen, Alex

    Comparing phenotypes of heterogeneous cell populations from multiple biological conditions is at the heart of scientific discovery based on flow cytometry (FC). When the biological signal is measured by the average expression of a biomarker, standard statistical methods require that variance be approximately stabilized in populations to be compared. Since the mean and variance of a cell population are often correlated in fluorescence-based FC measurements, a preprocessing step is needed to stabilize the within-population variances.

  9. flowVS: channel-specific variance stabilization in flow cytometry

    DOE PAGES

    Azad, Ariful; Rajwa, Bartek; Pothen, Alex

    2016-07-28

    Comparing phenotypes of heterogeneous cell populations from multiple biological conditions is at the heart of scientific discovery based on flow cytometry (FC). When the biological signal is measured by the average expression of a biomarker, standard statistical methods require that variance be approximately stabilized in populations to be compared. Since the mean and variance of a cell population are often correlated in fluorescence-based FC measurements, a preprocessing step is needed to stabilize the within-population variances.

  10. Automatic Bayes Factors for Testing Equality- and Inequality-Constrained Hypotheses on Variances.

    PubMed

    Böing-Messing, Florian; Mulder, Joris

    2018-05-03

    In comparing characteristics of independent populations, researchers frequently expect a certain structure of the population variances. These expectations can be formulated as hypotheses with equality and/or inequality constraints on the variances. In this article, we consider the Bayes factor for testing such (in)equality-constrained hypotheses on variances. Application of Bayes factors requires specification of a prior under every hypothesis to be tested. However, specifying subjective priors for variances based on prior information is a difficult task. We therefore consider so-called automatic or default Bayes factors. These methods avoid the need for the user to specify priors by using information from the sample data. We present three automatic Bayes factors for testing variances. The first is a Bayes factor with equal priors on all variances, where the priors are specified automatically using a small share of the information in the sample data. The second is the fractional Bayes factor, where a fraction of the likelihood is used for automatic prior specification. The third is an adjustment of the fractional Bayes factor such that the parsimony of inequality-constrained hypotheses is properly taken into account. The Bayes factors are evaluated by investigating different properties such as information consistency and large sample consistency. Based on this evaluation, it is concluded that the adjusted fractional Bayes factor is generally recommendable for testing equality- and inequality-constrained hypotheses on variances.

  11. Thermospheric mass density model error variance as a function of time scale

    NASA Astrophysics Data System (ADS)

    Emmert, J. T.; Sutton, E. K.

    2017-12-01

    In the increasingly crowded low-Earth orbit environment, accurate estimation of orbit prediction uncertainties is essential for collision avoidance. Poor characterization of such uncertainty can result in unnecessary and costly avoidance maneuvers (false positives) or disregard of a collision risk (false negatives). Atmospheric drag is a major source of orbit prediction uncertainty, and is particularly challenging to account for because it exerts a cumulative influence on orbital trajectories and is therefore not amenable to representation by a single uncertainty parameter. To address this challenge, we examine the variance of measured accelerometer-derived and orbit-derived mass densities with respect to predictions by thermospheric empirical models, using the data-minus-model variance as a proxy for model uncertainty. Our analysis focuses mainly on the power spectrum of the residuals, and we construct an empirical model of the variance as a function of time scale (from 1 hour to 10 years), altitude, and solar activity. We find that the power spectral density approximately follows a power-law process but with an enhancement near the 27-day solar rotation period. The residual variance increases monotonically with altitude between 250 and 550 km. There are two components to the variance dependence on solar activity: one component is 180 degrees out of phase (largest variance at solar minimum), and the other component lags 2 years behind solar maximum (largest variance in the descending phase of the solar cycle).

  12. Additive genetic variance in polyandry enables its evolution, but polyandry is unlikely to evolve through sexy or good sperm processes.

    PubMed

    Travers, L M; Simmons, L W; Garcia-Gonzalez, F

    2016-05-01

    Polyandry is widespread despite its costs. The sexually selected sperm hypotheses ('sexy' and 'good' sperm) posit that sperm competition plays a role in the evolution of polyandry. Two poorly studied assumptions of these hypotheses are the presence of additive genetic variance in polyandry and sperm competitiveness. Using a quantitative genetic breeding design in a natural population of Drosophila melanogaster, we first established the potential for polyandry to respond to selection. We then investigated whether polyandry can evolve through sexually selected sperm processes. We measured lifetime polyandry and offensive sperm competitiveness (P2 ) while controlling for sampling variance due to male × male × female interactions. We also measured additive genetic variance in egg-to-adult viability and controlled for its effect on P2 estimates. Female lifetime polyandry showed significant and substantial additive genetic variance and evolvability. In contrast, we found little genetic variance or evolvability in P2 or egg-to-adult viability. Additive genetic variance in polyandry highlights its potential to respond to selection. However, the low levels of genetic variance in sperm competitiveness suggest that the evolution of polyandry may not be driven by sexy sperm or good sperm processes. © 2016 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2016 European Society For Evolutionary Biology.

  13. Beyond mean allelic effects: A locus at the major color gene MC1R associates also with differing levels of phenotypic and genetic (co)variance for coloration in barn owls.

    PubMed

    San-Jose, Luis M; Ducret, Valérie; Ducrest, Anne-Lyse; Simon, Céline; Roulin, Alexandre

    2017-10-01

    The mean phenotypic effects of a discovered variant help to predict major aspects of the evolution and inheritance of a phenotype. However, differences in the phenotypic variance associated to distinct genotypes are often overlooked despite being suggestive of processes that largely influence phenotypic evolution, such as interactions between the genotypes with the environment or the genetic background. We present empirical evidence for a mutation at the melanocortin-1-receptor gene, a major vertebrate coloration gene, affecting phenotypic variance in the barn owl, Tyto alba. The white MC1R allele, which associates with whiter plumage coloration, also associates with a pronounced phenotypic and additive genetic variance for distinct color traits. Contrarily, the rufous allele, associated with a rufous coloration, relates to a lower phenotypic and additive genetic variance, suggesting that this allele may be epistatic over other color loci. Variance differences between genotypes entailed differences in the strength of phenotypic and genetic associations between color traits, suggesting that differences in variance also alter the level of integration between traits. This study highlights that addressing variance differences of genotypes in wild populations provides interesting new insights into the evolutionary mechanisms and the genetic architecture underlying the phenotype. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

  14. 76 FR 1145 - Alabama Power Company; Notice of Application for Amendment of License and Soliciting Comments...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-01-07

    ... drought-based temporary variance of the Martin Project rule curve and minimum flow releases at the Yates... requesting a drought- based temporary variance to the Martin Project rule curve. The rule curve variance...

  15. 40 CFR 59.106 - Variance.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... VOLATILE ORGANIC COMPOUND EMISSION STANDARDS FOR CONSUMER AND COMMERCIAL PRODUCTS National Volatile Organic Compound Emission Standards for Automobile Refinish Coatings § 59.106 Variance. (a) Any regulated entity... confidential information in reaching a decision on a variance application. Interested members of the public...

  16. Gender variance in childhood and sexual orientation in adulthood: a prospective study.

    PubMed

    Steensma, Thomas D; van der Ende, Jan; Verhulst, Frank C; Cohen-Kettenis, Peggy T

    2013-11-01

    Several retrospective and prospective studies have reported on the association between childhood gender variance and sexual orientation and gender discomfort in adulthood. In most of the retrospective studies, samples were drawn from the general population. The samples in the prospective studies consisted of clinically referred children. In understanding the extent to which the association applies for the general population, prospective studies using random samples are needed. This prospective study examined the association between childhood gender variance, and sexual orientation and gender discomfort in adulthood in the general population. In 1983, we measured childhood gender variance, in 406 boys and 473 girls. In 2007, sexual orientation and gender discomfort were assessed. Childhood gender variance was measured with two items from the Child Behavior Checklist/4-18. Sexual orientation was measured for four parameters of sexual orientation (attraction, fantasy, behavior, and identity). Gender discomfort was assessed by four questions (unhappiness and/or uncertainty about one's gender, wish or desire to be of the other gender, and consideration of living in the role of the other gender). For both men and women, the presence of childhood gender variance was associated with homosexuality for all four parameters of sexual orientation, but not with bisexuality. The report of adulthood homosexuality was 8 to 15 times higher for participants with a history of gender variance (10.2% to 12.2%), compared to participants without a history of gender variance (1.2% to 1.7%). The presence of childhood gender variance was not significantly associated with gender discomfort in adulthood. This study clearly showed a significant association between childhood gender variance and a homosexual sexual orientation in adulthood in the general population. In contrast to the findings in clinically referred gender-variant children, the presence of a homosexual sexual orientation in adulthood was substantially lower. © 2012 International Society for Sexual Medicine.

  17. Spectral analysis of the Earth's topographic potential via 2D-DFT: a new data-based degree variance model to degree 90,000

    NASA Astrophysics Data System (ADS)

    Rexer, Moritz; Hirt, Christian

    2015-09-01

    Classical degree variance models (such as Kaula's rule or the Tscherning-Rapp model) often rely on low-resolution gravity data and so are subject to extrapolation when used to describe the decay of the gravity field at short spatial scales. This paper presents a new degree variance model based on the recently published GGMplus near-global land areas 220 m resolution gravity maps (Geophys Res Lett 40(16):4279-4283, 2013). We investigate and use a 2D-DFT (discrete Fourier transform) approach to transform GGMplus gravity grids into degree variances. The method is described in detail and its approximation errors are studied using closed-loop experiments. Focus is placed on tiling, azimuth averaging, and windowing effects in the 2D-DFT method and on analytical fitting of degree variances. Approximation errors of the 2D-DFT procedure on the (spherical harmonic) degree variance are found to be at the 10-20 % level. The importance of the reference surface (sphere, ellipsoid or topography) of the gravity data for correct interpretation of degree variance spectra is highlighted. The effect of the underlying mass arrangement (spherical or ellipsoidal approximation) on the degree variances is found to be crucial at short spatial scales. A rule-of-thumb for transformation of spectra between spherical and ellipsoidal approximation is derived. Application of the 2D-DFT on GGMplus gravity maps yields a new degree variance model to degree 90,000. The model is supported by GRACE, GOCE, EGM2008 and forward-modelled gravity at 3 billion land points over all land areas within the SRTM data coverage and provides gravity signal variances at the surface of the topography. The model yields omission errors of 9 mGal for gravity (1.5 cm for geoid effects) at scales of 10 km, 4 mGal (1 mm) at 2-km scales, and 2 mGal (0.2 mm) at 1-km scales.

  18. Neuroticism explains unwanted variance in Implicit Association Tests of personality: possible evidence for an affective valence confound.

    PubMed

    Fleischhauer, Monika; Enge, Sören; Miller, Robert; Strobel, Alexander; Strobel, Anja

    2013-01-01

    Meta-analytic data highlight the value of the Implicit Association Test (IAT) as an indirect measure of personality. Based on evidence suggesting that confounding factors such as cognitive abilities contribute to the IAT effect, this study provides a first investigation of whether basic personality traits explain unwanted variance in the IAT. In a gender-balanced sample of 204 volunteers, the Big-Five dimensions were assessed via self-report, peer-report, and IAT. By means of structural equation modeling (SEM), latent Big-Five personality factors (based on self- and peer-report) were estimated and their predictive value for unwanted variance in the IAT was examined. In a first analysis, unwanted variance was defined in the sense of method-specific variance which may result from differences in task demands between the two IAT block conditions and which can be mirrored by the absolute size of the IAT effects. In a second analysis, unwanted variance was examined in a broader sense defined as those systematic variance components in the raw IAT scores that are not explained by the latent implicit personality factors. In contrast to the absolute IAT scores, this also considers biases associated with the direction of IAT effects (i.e., whether they are positive or negative in sign), biases that might result, for example, from the IAT's stimulus or category features. None of the explicit Big-Five factors was predictive for method-specific variance in the IATs (first analysis). However, when considering unwanted variance that goes beyond pure method-specific variance (second analysis), a substantial effect of neuroticism occurred that may have been driven by the affective valence of IAT attribute categories and the facilitated processing of negative stimuli, typically associated with neuroticism. The findings thus point to the necessity of using attribute category labels and stimuli of similar affective valence in personality IATs to avoid confounding due to recoding.

  19. Consequences of environmental and biological variances for range margins: a spatially explicit theoretical model

    NASA Astrophysics Data System (ADS)

    Malanson, G. P.; DeRose, R. J.; Bekker, M. F.

    2016-12-01

    The consequences of increasing climatic variance while including variability among individuals and populations are explored for range margins of species with a spatially explicit simulation. The model has a single environmental gradient and a single species then extended to two species. Species response to the environment is a Gaussian function with a peak of 1.0 at their peak fitness on the gradient. The variance in the environment is taken from the total variance in the tree ring series of 399 individuals of Pinus edulis in FIA plots in the western USA. The variability is increased by a multiplier of the standard deviation for various doubling times. The variance of individuals in the simulation is drawn from these same series. Inheritance of individual variability is based on the geographic locations of the individuals. The variance for P. edulis is recomputed as time-dependent conditional standard deviations using the GARCH procedure. Establishment and mortality are simulated in a Monte Carlo process with individual variance. Variance for P. edulis does not show a consistent pattern of heteroscedasticity. An obvious result is that increasing variance has deleterious effects on species persistence because extreme events that result in extinctions cannot be balanced by positive anomalies, but even less extreme negative events cannot be balanced by positive anomalies because of biological and spatial constraints. In the two species model the superior competitor is more affected by increasing climatic variance because its response function is steeper at the point of intersection with the other species and so the uncompensated effects of negative anomalies are greater for it. These theoretical results can guide the anticipated need to mitigate the effects of increasing climatic variability on P. edulis range margins. The trailing edge, here subject to increasing drought stress with increasing temperatures, will be more affected by negative anomalies.

  20. Is There a Common Summary Statistical Process for Representing the Mean and Variance? A Study Using Illustrations of Familiar Items.

    PubMed

    Yang, Yi; Tokita, Midori; Ishiguchi, Akira

    2018-01-01

    A number of studies revealed that our visual system can extract different types of summary statistics, such as the mean and variance, from sets of items. Although the extraction of such summary statistics has been studied well in isolation, the relationship between these statistics remains unclear. In this study, we explored this issue using an individual differences approach. Observers viewed illustrations of strawberries and lollypops varying in size or orientation and performed four tasks in a within-subject design, namely mean and variance discrimination tasks with size and orientation domains. We found that the performances in the mean and variance discrimination tasks were not correlated with each other and demonstrated that extractions of the mean and variance are mediated by different representation mechanisms. In addition, we tested the relationship between performances in size and orientation domains for each summary statistic (i.e. mean and variance) and examined whether each summary statistic has distinct processes across perceptual domains. The results illustrated that statistical summary representations of size and orientation may share a common mechanism for representing the mean and possibly for representing variance. Introspections for each observer performing the tasks were also examined and discussed.

  1. Detection of gene-environment interaction in pedigree data using genome-wide genotypes.

    PubMed

    Nivard, Michel G; Middeldorp, Christel M; Lubke, Gitta; Hottenga, Jouke-Jan; Abdellaoui, Abdel; Boomsma, Dorret I; Dolan, Conor V

    2016-12-01

    Heritability may be estimated using phenotypic data collected in relatives or in distantly related individuals using genome-wide single nucleotide polymorphism (SNP) data. We combined these approaches by re-parameterizing the model proposed by Zaitlen et al and extended this model to include moderation of (total and SNP-based) genetic and environmental variance components by a measured moderator. By means of data simulation, we demonstrated that the type 1 error rates of the proposed test are correct and parameter estimates are accurate. As an application, we considered the moderation by age or year of birth of variance components associated with body mass index (BMI), height, attention problems (AP), and symptoms of anxiety and depression. The genetic variance of BMI was found to increase with age, but the environmental variance displayed a greater increase with age, resulting in a proportional decrease of the heritability of BMI. Environmental variance of height increased with year of birth. The environmental variance of AP increased with age. These results illustrate the assessment of moderation of environmental and genetic effects, when estimating heritability from combined SNP and family data. The assessment of moderation of genetic and environmental variance will enhance our understanding of the genetic architecture of complex traits.

  2. Family members' unique perspectives of the family: examining their scope, size, and relations to individual adjustment.

    PubMed

    Jager, Justin; Bornstein, Marc H; Putnick, Diane L; Hendricks, Charlene

    2012-06-01

    Using the McMaster Family Assessment Device (Epstein, Baldwin, & Bishop, 1983) and incorporating the perspectives of adolescent, mother, and father, this study examined each family member's "unique perspective" or nonshared, idiosyncratic view of the family. We used a modified multitrait-multimethod confirmatory factor analysis that (a) isolated for each family member's 6 reports of family dysfunction the nonshared variance (a combination of variance idiosyncratic to the individual and measurement error) from variance shared by 1 or more family members and (b) extracted common variance across each family member's set of nonshared variances. The sample included 128 families from a U.S. East Coast metropolitan area. Each family member's unique perspective generalized across his or her different reports of family dysfunction and accounted for a sizable proportion of his or her own variance in reports of family dysfunction. In addition, after holding level of dysfunction constant across families and controlling for a family's shared variance (agreement regarding family dysfunction), each family member's unique perspective was associated with his or her own adjustment. Future applications and competing alternatives for what these "unique perspectives" reflect about the family are discussed. PsycINFO Database Record (c) 2012 APA, all rights reserved.

  3. Family Members' Unique Perspectives of the Family: Examining their Scope, Size, and Relations to Individual Adjustment

    PubMed Central

    Jager, Justin; Bornstein, Marc H.; Diane, L. Putnick; Hendricks, Charlene

    2012-01-01

    Using the Family Assessment Device (FAD; Epstein, Baldwin, & Bishop, 1983) and incorporating the perspectives of adolescent, mother, and father, this study examined each family member's “unique perspective” or non-shared, idiosyncratic view of the family. To do so we used a modified multitrait-multimethod confirmatory factor analysis that (1) isolated for each family member's six reports of family dysfunction the non-shared variance (a combination of variance idiosyncratic to the individual and measurement error) from variance shared by one or more family members and (2) extracted common variance across each family member's set of non-shared variances. The sample included 128 families from a U.S. East Coast metropolitan area. Each family member's unique perspective generalized across his or her different reports of family dysfunction and accounted for a sizable proportion of his or her own variance in reports of family dysfunction. Additionally, after holding level of dysfunction constant across families and controlling for a family's shared variance (agreement regarding family dysfunction), each family member's unique perspective was associated with his or her own adjustment. Future applications and competing alternatives for what these “unique perspectives” reflect about the family are discussed. PMID:22545933

  4. A general unified framework to assess the sampling variance of heritability estimates using pedigree or marker-based relationships.

    PubMed

    Visscher, Peter M; Goddard, Michael E

    2015-01-01

    Heritability is a population parameter of importance in evolution, plant and animal breeding, and human medical genetics. It can be estimated using pedigree designs and, more recently, using relationships estimated from markers. We derive the sampling variance of the estimate of heritability for a wide range of experimental designs, assuming that estimation is by maximum likelihood and that the resemblance between relatives is solely due to additive genetic variation. We show that well-known results for balanced designs are special cases of a more general unified framework. For pedigree designs, the sampling variance is inversely proportional to the variance of relationship in the pedigree and it is proportional to 1/N, whereas for population samples it is approximately proportional to 1/N(2), where N is the sample size. Variation in relatedness is a key parameter in the quantification of the sampling variance of heritability. Consequently, the sampling variance is high for populations with large recent effective population size (e.g., humans) because this causes low variation in relationship. However, even using human population samples, low sampling variance is possible with high N. Copyright © 2015 by the Genetics Society of America.

  5. 40 CFR 142.41 - Variance request.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ....41 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS IMPLEMENTATION Variances Issued by the Administrator Under Section 1415(a) of the Act § 142.41 Variance request. A supplier of water may request the granting of a...

  6. 40 CFR 142.41 - Variance request.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ....41 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS IMPLEMENTATION Variances Issued by the Administrator Under Section 1415(a) of the Act § 142.41 Variance request. A supplier of water may request the granting of a...

  7. 40 CFR 142.301 - What is a small system variance?

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ....301 Section 142.301 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS IMPLEMENTATION Variances for Small System... procedures and criteria for obtaining these variances. The regulations in this subpart shall take effect on...

  8. 40 CFR 142.301 - What is a small system variance?

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ....301 Section 142.301 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS IMPLEMENTATION Variances for Small System... procedures and criteria for obtaining these variances. The regulations in this subpart shall take effect on...

  9. 40 CFR 142.301 - What is a small system variance?

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ....301 Section 142.301 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS IMPLEMENTATION Variances for Small System... procedures and criteria for obtaining these variances. The regulations in this subpart shall take effect on...

  10. 40 CFR 142.301 - What is a small system variance?

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ....301 Section 142.301 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS IMPLEMENTATION Variances for Small System... procedures and criteria for obtaining these variances. The regulations in this subpart shall take effect on...

  11. 40 CFR 142.301 - What is a small system variance?

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ....301 Section 142.301 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS IMPLEMENTATION Variances for Small System... procedures and criteria for obtaining these variances. The regulations in this subpart shall take effect on...

  12. 40 CFR 59.206 - Variances.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... VOLATILE ORGANIC COMPOUND EMISSION STANDARDS FOR CONSUMER AND COMMERCIAL PRODUCTS National Volatile Organic Compound Emission Standards for Consumer Products § 59.206 Variances. (a) Any regulated entity who cannot... reaching a decision on a variance application. Interested members of the public will be allowed a...

  13. Data Analysis and Its Impact on Predicting Schedule & Cost Risk

    DTIC Science & Technology

    2006-03-01

    variance of the error term by performing a Breusch - Pagan test for constant variance (Neter et al., 1996:239). In order to test the normality of...is constant variance. Using Microsoft Excel®, we calculate a p- 68 value of 0.225678 for the Breusch - Pagan test . We again compare this p-value to...calculate a p-value of 0.121211092 Breusch - Pagan test . We again compare this p-value to an alpha of 0.05 indicating our assumption of constant variance

  14. Procedures for estimating confidence intervals for selected method performance parameters.

    PubMed

    McClure, F D; Lee, J K

    2001-01-01

    Procedures for estimating confidence intervals (CIs) for the repeatability variance (sigmar2), reproducibility variance (sigmaR2 = sigmaL2 + sigmar2), laboratory component (sigmaL2), and their corresponding standard deviations sigmar, sigmaR, and sigmaL, respectively, are presented. In addition, CIs for the ratio of the repeatability component to the reproducibility variance (sigmar2/sigmaR2) and the ratio of the laboratory component to the reproducibility variance (sigmaL2/sigmaR2) are also presented.

  15. Genetic basis of between-individual and within-individual variance of docility.

    PubMed

    Martin, J G A; Pirotta, E; Petelle, M B; Blumstein, D T

    2017-04-01

    Between-individual variation in phenotypes within a population is the basis of evolution. However, evolutionary and behavioural ecologists have mainly focused on estimating between-individual variance in mean trait and neglected variation in within-individual variance, or predictability of a trait. In fact, an important assumption of mixed-effects models used to estimate between-individual variance in mean traits is that within-individual residual variance (predictability) is identical across individuals. Individual heterogeneity in the predictability of behaviours is a potentially important effect but rarely estimated and accounted for. We used 11 389 measures of docility behaviour from 1576 yellow-bellied marmots (Marmota flaviventris) to estimate between-individual variation in both mean docility and its predictability. We then implemented a double hierarchical animal model to decompose the variances of both mean trait and predictability into their environmental and genetic components. We found that individuals differed both in their docility and in their predictability of docility with a negative phenotypic covariance. We also found significant genetic variance for both mean docility and its predictability but no genetic covariance between the two. This analysis is one of the first to estimate the genetic basis of both mean trait and within-individual variance in a wild population. Our results indicate that equal within-individual variance should not be assumed. We demonstrate the evolutionary importance of the variation in the predictability of docility and illustrate potential bias in models ignoring variation in predictability. We conclude that the variability in the predictability of a trait should not be ignored, and present a coherent approach for its quantification. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.

  16. Some variance reduction methods for numerical stochastic homogenization

    PubMed Central

    Blanc, X.; Le Bris, C.; Legoll, F.

    2016-01-01

    We give an overview of a series of recent studies devoted to variance reduction techniques for numerical stochastic homogenization. Numerical homogenization requires that a set of problems is solved at the microscale, the so-called corrector problems. In a random environment, these problems are stochastic and therefore need to be repeatedly solved, for several configurations of the medium considered. An empirical average over all configurations is then performed using the Monte Carlo approach, so as to approximate the effective coefficients necessary to determine the macroscopic behaviour. Variance severely affects the accuracy and the cost of such computations. Variance reduction approaches, borrowed from other contexts in the engineering sciences, can be useful. Some of these variance reduction techniques are presented, studied and tested here. PMID:27002065

  17. Markowitz portfolio optimization model employing fuzzy measure

    NASA Astrophysics Data System (ADS)

    Ramli, Suhailywati; Jaaman, Saiful Hafizah

    2017-04-01

    Markowitz in 1952 introduced the mean-variance methodology for the portfolio selection problems. His pioneering research has shaped the portfolio risk-return model and become one of the most important research fields in modern finance. This paper extends the classical Markowitz's mean-variance portfolio selection model applying the fuzzy measure to determine the risk and return. In this paper, we apply the original mean-variance model as a benchmark, fuzzy mean-variance model with fuzzy return and the model with return are modeled by specific types of fuzzy number for comparison. The model with fuzzy approach gives better performance as compared to the mean-variance approach. The numerical examples are included to illustrate these models by employing Malaysian share market data.

  18. 42 CFR 456.522 - Content of request for variance.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... SERVICES (CONTINUED) MEDICAL ASSISTANCE PROGRAMS UTILIZATION CONTROL Utilization Review Plans: FFP, Waivers, and Variances for Hospitals and Mental Hospitals Ur Plan: Remote Facility Variances from Time..., mental hospital, and ICF located within a 50-mile radius of the facility; (e) The distance and average...

  19. 42 CFR 456.522 - Content of request for variance.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... SERVICES (CONTINUED) MEDICAL ASSISTANCE PROGRAMS UTILIZATION CONTROL Utilization Review Plans: FFP, Waivers, and Variances for Hospitals and Mental Hospitals Ur Plan: Remote Facility Variances from Time... travel time between the remote facility and each facility listed in paragraph (e) of this section; (f...

  20. 29 CFR 1905.5 - Effect of variances.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ...-STEIGER OCCUPATIONAL SAFETY AND HEALTH ACT OF 1970 General § 1905.5 Effect of variances. All variances... Regulations Relating to Labor (Continued) OCCUPATIONAL SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR... concerning a proposed penalty or period of abatement is pending before the Occupational Safety and Health...

  1. 44 CFR 60.6 - Variances and exceptions.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program CRITERIA FOR... risk and will not be modified by the granting of a variance. The community, after examining the... review a community's findings justifying the granting of variances, and if that review indicates a...

  2. 44 CFR 60.6 - Variances and exceptions.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program CRITERIA FOR... risk and will not be modified by the granting of a variance. The community, after examining the... review a community's findings justifying the granting of variances, and if that review indicates a...

  3. How the Weak Variance of Momentum Can Turn Out to be Negative

    NASA Astrophysics Data System (ADS)

    Feyereisen, M. R.

    2015-05-01

    Weak values are average quantities, therefore investigating their associated variance is crucial in understanding their place in quantum mechanics. We develop the concept of a position-postselected weak variance of momentum as cohesively as possible, building primarily on material from Moyal (Mathematical Proceedings of the Cambridge Philosophical Society, Cambridge University Press, Cambridge, 1949) and Sonego (Found Phys 21(10):1135, 1991) . The weak variance is defined in terms of the Wigner function, using a standard construction from probability theory. We show this corresponds to a measurable quantity, which is not itself a weak value. It also leads naturally to a connection between the imaginary part of the weak value of momentum and the quantum potential. We study how the negativity of the Wigner function causes negative weak variances, and the implications this has on a class of `subquantum' theories. We also discuss the role of weak variances in studying determinism, deriving the classical limit from a variational principle.

  4. A stochastic hybrid model for pricing forward-start variance swaps

    NASA Astrophysics Data System (ADS)

    Roslan, Teh Raihana Nazirah

    2017-11-01

    Recently, market players have been exposed to the astounding increase in the trading volume of variance swaps. In this paper, the forward-start nature of a variance swap is being inspected, where hybridizations of equity and interest rate models are used to evaluate the price of discretely-sampled forward-start variance swaps. The Heston stochastic volatility model is being extended to incorporate the dynamics of the Cox-Ingersoll-Ross (CIR) stochastic interest rate model. This is essential since previous studies on variance swaps were mainly focusing on instantaneous-start variance swaps without considering the interest rate effects. This hybrid model produces an efficient semi-closed form pricing formula through the development of forward characteristic functions. The performance of this formula is investigated via simulations to demonstrate how the formula performs for different sampling times and against the real market scenario. Comparison done with the Monte Carlo simulation which was set as our main reference point reveals that our pricing formula gains almost the same precision in a shorter execution time.

  5. Estimating Variances of Horizontal Wind Fluctuations in Stable Conditions

    NASA Astrophysics Data System (ADS)

    Luhar, Ashok K.

    2010-05-01

    Information concerning the average wind speed and the variances of lateral and longitudinal wind velocity fluctuations is required by dispersion models to characterise turbulence in the atmospheric boundary layer. When the winds are weak, the scalar average wind speed and the vector average wind speed need to be clearly distinguished and both lateral and longitudinal wind velocity fluctuations assume equal importance in dispersion calculations. We examine commonly-used methods of estimating these variances from wind-speed and wind-direction statistics measured separately, for example, by a cup anemometer and a wind vane, and evaluate the implied relationship between the scalar and vector wind speeds, using measurements taken under low-wind stable conditions. We highlight several inconsistencies inherent in the existing formulations and show that the widely-used assumption that the lateral velocity variance is equal to the longitudinal velocity variance is not necessarily true. We derive improved relations for the two variances, and although data under stable stratification are considered for comparison, our analysis is applicable more generally.

  6. Comparison of the efficiency between two sampling plans for aflatoxins analysis in maize

    PubMed Central

    Mallmann, Adriano Olnei; Marchioro, Alexandro; Oliveira, Maurício Schneider; Rauber, Ricardo Hummes; Dilkin, Paulo; Mallmann, Carlos Augusto

    2014-01-01

    Variance and performance of two sampling plans for aflatoxins quantification in maize were evaluated. Eight lots of maize were sampled using two plans: manual, using sampling spear for kernels; and automatic, using a continuous flow to collect milled maize. Total variance and sampling, preparation, and analysis variance were determined and compared between plans through multifactor analysis of variance. Four theoretical distribution models were used to compare aflatoxins quantification distributions in eight maize lots. The acceptance and rejection probabilities for a lot under certain aflatoxin concentration were determined using variance and the information on the selected distribution model to build the operational characteristic curves (OC). Sampling and total variance were lower at the automatic plan. The OC curve from the automatic plan reduced both consumer and producer risks in comparison to the manual plan. The automatic plan is more efficient than the manual one because it expresses more accurately the real aflatoxin contamination in maize. PMID:24948911

  7. Mixed model approaches for diallel analysis based on a bio-model.

    PubMed

    Zhu, J; Weir, B S

    1996-12-01

    A MINQUE(1) procedure, which is minimum norm quadratic unbiased estimation (MINQUE) method with 1 for all the prior values, is suggested for estimating variance and covariance components in a bio-model for diallel crosses. Unbiasedness and efficiency of estimation were compared for MINQUE(1), restricted maximum likelihood (REML) and MINQUE theta which has parameter values for the prior values. MINQUE(1) is almost as efficient as MINQUE theta for unbiased estimation of genetic variance and covariance components. The bio-model is efficient and robust for estimating variance and covariance components for maternal and paternal effects as well as for nuclear effects. A procedure of adjusted unbiased prediction (AUP) is proposed for predicting random genetic effects in the bio-model. The jack-knife procedure is suggested for estimation of sampling variances of estimated variance and covariance components and of predicted genetic effects. Worked examples are given for estimation of variance and covariance components and for prediction of genetic merits.

  8. Survival estimation and the effects of dependency among animals

    USGS Publications Warehouse

    Schmutz, Joel A.; Ward, David H.; Sedinger, James S.; Rexstad, Eric A.

    1995-01-01

    Survival models assume that fates of individuals are independent, yet the robustness of this assumption has been poorly quantified. We examine how empirically derived estimates of the variance of survival rates are affected by dependency in survival probability among individuals. We used Monte Carlo simulations to generate known amounts of dependency among pairs of individuals and analyzed these data with Kaplan-Meier and Cormack-Jolly-Seber models. Dependency significantly increased these empirical variances as compared to theoretically derived estimates of variance from the same populations. Using resighting data from 168 pairs of black brant, we used a resampling procedure and program RELEASE to estimate empirical and mean theoretical variances. We estimated that the relationship between paired individuals caused the empirical variance of the survival rate to be 155% larger than the empirical variance for unpaired individuals. Monte Carlo simulations and use of this resampling strategy can provide investigators with information on how robust their data are to this common assumption of independent survival probabilities.

  9. Genetic Variance in Homophobia: Evidence from Self- and Peer Reports.

    PubMed

    Zapko-Willmes, Alexandra; Kandler, Christian

    2018-01-01

    The present twin study combined self- and peer assessments of twins' general homophobia targeting gay men in order to replicate previous behavior genetic findings across different rater perspectives and to disentangle self-rater-specific variance from common variance in self- and peer-reported homophobia (i.e., rater-consistent variance). We hypothesized rater-consistent variance in homophobia to be attributable to genetic and nonshared environmental effects, and self-rater-specific variance to be partially accounted for by genetic influences. A sample of 869 twins and 1329 peer raters completed a seven item scale containing cognitive, affective, and discriminatory homophobic tendencies. After correction for age and sex differences, we found most of the genetic contributions (62%) and significant nonshared environmental contributions (16%) to individual differences in self-reports on homophobia to be also reflected in peer-reported homophobia. A significant genetic component, however, was self-report-specific (38%), suggesting that self-assessments alone produce inflated heritability estimates to some degree. Different explanations are discussed.

  10. The genetic variance but not the genetic covariance of life-history traits changes towards the north in a time-constrained insect.

    PubMed

    Sniegula, Szymon; Golab, Maria J; Drobniak, Szymon M; Johansson, Frank

    2018-06-01

    Seasonal time constraints are usually stronger at higher than lower latitudes and can exert strong selection on life-history traits and the correlations among these traits. To predict the response of life-history traits to environmental change along a latitudinal gradient, information must be obtained about genetic variance in traits and also genetic correlation between traits, that is the genetic variance-covariance matrix, G. Here, we estimated G for key life-history traits in an obligate univoltine damselfly that faces seasonal time constraints. We exposed populations to simulated native temperatures and photoperiods and common garden environmental conditions in a laboratory set-up. Despite differences in genetic variance in these traits between populations (lower variance at northern latitudes), there was no evidence for latitude-specific covariance of the life-history traits. At simulated native conditions, all populations showed strong genetic and phenotypic correlations between traits that shaped growth and development. The variance-covariance matrix changed considerably when populations were exposed to common garden conditions compared with the simulated natural conditions, showing the importance of environmentally induced changes in multivariate genetic structure. Our results highlight the importance of estimating variance-covariance matrixes in environments that mimic selection pressures and not only trait variances or mean trait values in common garden conditions for understanding the trait evolution across populations and environments. © 2018 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2018 European Society For Evolutionary Biology.

  11. Modeling rainfall-runoff relationship using multivariate GARCH model

    NASA Astrophysics Data System (ADS)

    Modarres, R.; Ouarda, T. B. M. J.

    2013-08-01

    The traditional hydrologic time series approaches are used for modeling, simulating and forecasting conditional mean of hydrologic variables but neglect their time varying variance or the second order moment. This paper introduces the multivariate Generalized Autoregressive Conditional Heteroscedasticity (MGARCH) modeling approach to show how the variance-covariance relationship between hydrologic variables varies in time. These approaches are also useful to estimate the dynamic conditional correlation between hydrologic variables. To illustrate the novelty and usefulness of MGARCH models in hydrology, two major types of MGARCH models, the bivariate diagonal VECH and constant conditional correlation (CCC) models are applied to show the variance-covariance structure and cdynamic correlation in a rainfall-runoff process. The bivariate diagonal VECH-GARCH(1,1) and CCC-GARCH(1,1) models indicated both short-run and long-run persistency in the conditional variance-covariance matrix of the rainfall-runoff process. The conditional variance of rainfall appears to have a stronger persistency, especially long-run persistency, than the conditional variance of streamflow which shows a short-lived drastic increasing pattern and a stronger short-run persistency. The conditional covariance and conditional correlation coefficients have different features for each bivariate rainfall-runoff process with different degrees of stationarity and dynamic nonlinearity. The spatial and temporal pattern of variance-covariance features may reflect the signature of different physical and hydrological variables such as drainage area, topography, soil moisture and ground water fluctuations on the strength, stationarity and nonlinearity of the conditional variance-covariance for a rainfall-runoff process.

  12. 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.

  13. 42 CFR 456.524 - Notification of Administrator's action and duration of variance.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ..., DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL ASSISTANCE PROGRAMS UTILIZATION CONTROL Utilization Review Plans: FFP, Waivers, and Variances for Hospitals and Mental Hospitals Ur Plan: Remote Facility Variances from Time Requirements § 456.524 Notification of Administrator's action and duration of...

  14. Evaluation of Mean and Variance Integrals without Integration

    ERIC Educational Resources Information Center

    Joarder, A. H.; Omar, M. H.

    2007-01-01

    The mean and variance of some continuous distributions, in particular the exponentially decreasing probability distribution and the normal distribution, are considered. Since they involve integration by parts, many students do not feel comfortable. In this note, a technique is demonstrated for deriving mean and variance through differential…

  15. 42 CFR 488.64 - Remote facility variances for utilization review requirements.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... 42 Public Health 5 2014-10-01 2014-10-01 false Remote facility variances for utilization review requirements. 488.64 Section 488.64 Public Health CENTERS FOR MEDICARE & MEDICAID SERVICES, DEPARTMENT OF... PROCEDURES Special Requirements § 488.64 Remote facility variances for utilization review requirements. (a...

  16. 42 CFR 488.64 - Remote facility variances for utilization review requirements.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 42 Public Health 5 2012-10-01 2012-10-01 false Remote facility variances for utilization review requirements. 488.64 Section 488.64 Public Health CENTERS FOR MEDICARE & MEDICAID SERVICES, DEPARTMENT OF... PROCEDURES Special Requirements § 488.64 Remote facility variances for utilization review requirements. (a...

  17. 42 CFR 488.64 - Remote facility variances for utilization review requirements.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 42 Public Health 5 2011-10-01 2011-10-01 false Remote facility variances for utilization review requirements. 488.64 Section 488.64 Public Health CENTERS FOR MEDICARE & MEDICAID SERVICES, DEPARTMENT OF... PROCEDURES Special Requirements § 488.64 Remote facility variances for utilization review requirements. (a...

  18. 42 CFR 488.64 - Remote facility variances for utilization review requirements.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... 42 Public Health 5 2013-10-01 2013-10-01 false Remote facility variances for utilization review requirements. 488.64 Section 488.64 Public Health CENTERS FOR MEDICARE & MEDICAID SERVICES, DEPARTMENT OF... PROCEDURES Special Requirements § 488.64 Remote facility variances for utilization review requirements. (a...

  19. Bootstrap Estimation and Testing for Variance Equality.

    ERIC Educational Resources Information Center

    Olejnik, Stephen; Algina, James

    The purpose of this study was to develop a single procedure for comparing population variances which could be used for distribution forms. Bootstrap methodology was used to estimate the variability of the sample variance statistic when the population distribution was normal, platykurtic and leptokurtic. The data for the study were generated and…

  20. Gender Variance and Educational Psychology: Implications for Practice

    ERIC Educational Resources Information Center

    Yavuz, Carrie

    2016-01-01

    The area of gender variance appears to be more visible in both the media and everyday life. Within educational psychology literature gender variance remains underrepresented. The positioning of educational psychologists working across the three levels of child and family, school or establishment and education authority/council, means that they are…

  1. 40 CFR 142.65 - Variances and exemptions from the maximum contaminant levels for radionuclides.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... maximum contaminant levels for radionuclides. 142.65 Section 142.65 Protection of Environment... Available § 142.65 Variances and exemptions from the maximum contaminant levels for radionuclides. (a)(1) Variances and exemptions from the maximum contaminant levels for combined radium-226 and radium-228, uranium...

  2. 40 CFR 142.65 - Variances and exemptions from the maximum contaminant levels for radionuclides.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... maximum contaminant levels for radionuclides. 142.65 Section 142.65 Protection of Environment... Available § 142.65 Variances and exemptions from the maximum contaminant levels for radionuclides. (a)(1) Variances and exemptions from the maximum contaminant levels for combined radium-226 and radium-228, uranium...

  3. 40 CFR 142.65 - Variances and exemptions from the maximum contaminant levels for radionuclides.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... maximum contaminant levels for radionuclides. 142.65 Section 142.65 Protection of Environment... Available § 142.65 Variances and exemptions from the maximum contaminant levels for radionuclides. (a)(1) Variances and exemptions from the maximum contaminant levels for combined radium-226 and radium-228, uranium...

  4. 40 CFR 142.65 - Variances and exemptions from the maximum contaminant levels for radionuclides.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... maximum contaminant levels for radionuclides. 142.65 Section 142.65 Protection of Environment... Available § 142.65 Variances and exemptions from the maximum contaminant levels for radionuclides. (a)(1) Variances and exemptions from the maximum contaminant levels for combined radium-226 and radium-228, uranium...

  5. Nonlinear Epigenetic Variance: Review and Simulations

    ERIC Educational Resources Information Center

    Kan, Kees-Jan; Ploeger, Annemie; Raijmakers, Maartje E. J.; Dolan, Conor V.; van Der Maas, Han L. J.

    2010-01-01

    We present a review of empirical evidence that suggests that a substantial portion of phenotypic variance is due to nonlinear (epigenetic) processes during ontogenesis. The role of such processes as a source of phenotypic variance in human behaviour genetic studies is not fully appreciated. In addition to our review, we present simulation studies…

  6. Determining Sample Sizes for Precise Contrast Analysis with Heterogeneous Variances

    ERIC Educational Resources Information Center

    Jan, Show-Li; Shieh, Gwowen

    2014-01-01

    The analysis of variance (ANOVA) is one of the most frequently used statistical analyses in practical applications. Accordingly, the single and multiple comparison procedures are frequently applied to assess the differences among mean effects. However, the underlying assumption of homogeneous variances may not always be tenable. This study…

  7. 10 CFR 851.32 - Action on variance requests.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... cited by the Chief Health, Safety and Security Officer; or (ii) Forward to the Under Secretary the... DEPARTMENT OF ENERGY WORKER SAFETY AND HEALTH PROGRAM Variances § 851.32 Action on variance requests. (a) Procedures for an approval recommendation. (1) If the Chief Health, Safety and Security Officer recommends...

  8. A Unifying Probability Example.

    ERIC Educational Resources Information Center

    Maruszewski, Richard F., Jr.

    2002-01-01

    Presents an example from probability and statistics that ties together several topics including the mean and variance of a discrete random variable, the binomial distribution and its particular mean and variance, the sum of independent random variables, the mean and variance of the sum, and the central limit theorem. Uses Excel to illustrate these…

  9. On the Endogeneity of the Mean-Variance Efficient Frontier.

    ERIC Educational Resources Information Center

    Somerville, R. A.; O'Connell, Paul G. J.

    2002-01-01

    Explains that the endogeneity of the efficient frontier in the mean-variance model of portfolio selection is commonly obscured in portfolio selection literature and in widely used textbooks. Demonstrates endogeneity and discusses the impact of parameter changes on the mean-variance efficient frontier and on the beta coefficients of individual…

  10. 44 CFR 60.6 - Variances and exceptions.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program CRITERIA FOR LAND MANAGEMENT AND USE Requirements for Flood Plain Management Regulations § 60.6 Variances and exceptions. (a... the criteria set forth in §§ 60.3, 60.4, and 60.5. The issuance of a variance is for flood plain...

  11. Variance computations for functional of absolute risk estimates.

    PubMed

    Pfeiffer, R M; Petracci, E

    2011-07-01

    We present a simple influence function based approach to compute the variances of estimates of absolute risk and functions of absolute risk. We apply this approach to criteria that assess the impact of changes in the risk factor distribution on absolute risk for an individual and at the population level. As an illustration we use an absolute risk prediction model for breast cancer that includes modifiable risk factors in addition to standard breast cancer risk factors. Influence function based variance estimates for absolute risk and the criteria are compared to bootstrap variance estimates.

  12. Variance computations for functional of absolute risk estimates

    PubMed Central

    Pfeiffer, R.M.; Petracci, E.

    2011-01-01

    We present a simple influence function based approach to compute the variances of estimates of absolute risk and functions of absolute risk. We apply this approach to criteria that assess the impact of changes in the risk factor distribution on absolute risk for an individual and at the population level. As an illustration we use an absolute risk prediction model for breast cancer that includes modifiable risk factors in addition to standard breast cancer risk factors. Influence function based variance estimates for absolute risk and the criteria are compared to bootstrap variance estimates. PMID:21643476

  13. Estimation of within-stratum variance for sample allocation: Foreign commodity production forecasting

    NASA Technical Reports Server (NTRS)

    Chhikara, R. S.; Perry, C. R., Jr. (Principal Investigator)

    1980-01-01

    The problem of determining the stratum variances required for an optimum sample allocation for remotely sensed crop surveys is investigated with emphasis on an approach based on the concept of stratum variance as a function of the sampling unit size. A methodology using the existing and easily available information of historical statistics is developed for obtaining initial estimates of stratum variances. The procedure is applied to variance for wheat in the U.S. Great Plains and is evaluated based on the numerical results obtained. It is shown that the proposed technique is viable and performs satisfactorily with the use of a conservative value (smaller than the expected value) for the field size and with the use of crop statistics from the small political division level.

  14. 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.

  15. Some variance reduction methods for numerical stochastic homogenization.

    PubMed

    Blanc, X; Le Bris, C; Legoll, F

    2016-04-28

    We give an overview of a series of recent studies devoted to variance reduction techniques for numerical stochastic homogenization. Numerical homogenization requires that a set of problems is solved at the microscale, the so-called corrector problems. In a random environment, these problems are stochastic and therefore need to be repeatedly solved, for several configurations of the medium considered. An empirical average over all configurations is then performed using the Monte Carlo approach, so as to approximate the effective coefficients necessary to determine the macroscopic behaviour. Variance severely affects the accuracy and the cost of such computations. Variance reduction approaches, borrowed from other contexts in the engineering sciences, can be useful. Some of these variance reduction techniques are presented, studied and tested here. © 2016 The Author(s).

  16. The variance of dispersion measure of high-redshift transient objects as a probe of ionized bubble size during reionization

    NASA Astrophysics Data System (ADS)

    Yoshiura, Shintaro; Takahashi, Keitaro

    2018-01-01

    The dispersion measure (DM) of high-redshift (z ≳ 6) transient objects such as fast radio bursts can be a powerful tool to probe the intergalactic medium during the Epoch of Reionization. In this paper, we study the variance of the DMs of objects with the same redshift as a potential probe of the size distribution of ionized bubbles. We calculate the DM variance with a simple model with randomly distributed spherical bubbles. It is found that the DM variance reflects the characteristics of the probability distribution of the bubble size. We find that the variance can be measured precisely enough to obtain the information on the typical size with a few hundred sources at a single redshift.

  17. The relation of hand and arm configuration variances while tracking geometric figures in Parkinson's disease: aspects for rehabilitation.

    PubMed

    Keresztényi, Zoltán; Cesari, Paola; Fazekas, Gábor; Laczkó, József

    2009-03-01

    Variances of drawing arm movements between patients with Parkinson's disease and healthy controls were compared. The aim was to determine whether differences in joint synergies or individual joint rotations affect the endpoint (hand position) variance. Joint and endpoint coordinates were measured while participants performed drawing tasks. Variances of arm configurations and endpoints were computed and statistically analyzed for 12 patients and 12 controls. The variance of arm movements for patients (both for arm configuration and endpoint) was overall higher than that for the control group. Variation was smaller for drawing a circle versus a square and for drawing with the dominant versus the nondominant hand within both groups. The ratio of arm configuration variances between groups was similar to the ratio of endpoint variances. There were significant differences in the velocity, but not in the path lengths of movements comparing the two groups. Patients presented less movement stability while drawing different figures in different trials. Moreover, the similarity of the ratios suggests that the ill-coordinated hand movement was caused by the error in the movements of individual body parts rather than by the lack of intersegmental coordination. Thus, rehabilitation may focus on the improvement of the precision of individual joint rotations.

  18. Structural changes and out-of-sample prediction of realized range-based variance in the stock market

    NASA Astrophysics Data System (ADS)

    Gong, Xu; Lin, Boqiang

    2018-03-01

    This paper aims to examine the effects of structural changes on forecasting the realized range-based variance in the stock market. Considering structural changes in variance in the stock market, we develop the HAR-RRV-SC model on the basis of the HAR-RRV model. Subsequently, the HAR-RRV and HAR-RRV-SC models are used to forecast the realized range-based variance of S&P 500 Index. We find that there are many structural changes in variance in the U.S. stock market, and the period after the financial crisis contains more structural change points than the period before the financial crisis. The out-of-sample results show that the HAR-RRV-SC model significantly outperforms the HAR-BV model when they are employed to forecast the 1-day, 1-week, and 1-month realized range-based variances, which means that structural changes can improve out-of-sample prediction of realized range-based variance. The out-of-sample results remain robust across the alternative rolling fixed-window, the alternative threshold value in ICSS algorithm, and the alternative benchmark models. More importantly, we believe that considering structural changes can help improve the out-of-sample performances of most of other existing HAR-RRV-type models in addition to the models used in this paper.

  19. Detection of gene–environment interaction in pedigree data using genome-wide genotypes

    PubMed Central

    Nivard, Michel G; Middeldorp, Christel M; Lubke, Gitta; Hottenga, Jouke-Jan; Abdellaoui, Abdel; Boomsma, Dorret I; Dolan, Conor V

    2016-01-01

    Heritability may be estimated using phenotypic data collected in relatives or in distantly related individuals using genome-wide single nucleotide polymorphism (SNP) data. We combined these approaches by re-parameterizing the model proposed by Zaitlen et al and extended this model to include moderation of (total and SNP-based) genetic and environmental variance components by a measured moderator. By means of data simulation, we demonstrated that the type 1 error rates of the proposed test are correct and parameter estimates are accurate. As an application, we considered the moderation by age or year of birth of variance components associated with body mass index (BMI), height, attention problems (AP), and symptoms of anxiety and depression. The genetic variance of BMI was found to increase with age, but the environmental variance displayed a greater increase with age, resulting in a proportional decrease of the heritability of BMI. Environmental variance of height increased with year of birth. The environmental variance of AP increased with age. These results illustrate the assessment of moderation of environmental and genetic effects, when estimating heritability from combined SNP and family data. The assessment of moderation of genetic and environmental variance will enhance our understanding of the genetic architecture of complex traits. PMID:27436263

  20. Maternal-by-environment but not genotype-by-environment interactions in a fish without parental care.

    PubMed

    Vega-Trejo, Regina; Head, Megan L; Jennions, Michael D; Kruuk, Loeske E B

    2018-01-01

    The impact of environmental conditions on the expression of genetic variance and on maternal effects variance remains an important question in evolutionary quantitative genetics. We investigate here the effects of early environment on variation in seven adult life history, morphological, and secondary sexual traits (including sperm characteristics) in a viviparous poeciliid fish, the mosquitofish Gambusia holbrooki. Specifically, we manipulated food availability during early development and then assessed additive genetic and maternal effects contributions to the overall phenotypic variance in adults. We found higher heritability for female than male traits, but maternal effects variance for traits in both sexes. An interaction between maternal effects variance and rearing environment affected two adult traits (female age at maturity and male size at maturity), but there was no evidence of trade-offs in maternal effects across environments. Our results illustrate (i) the potential for pre-natal maternal effects to interact with offspring environment during development, potentially affecting traits through to adulthood and (ii) that genotype-by-environment interactions might be overestimated if maternal-by-environment interactions are not accounted for, similar to heritability being overestimated if maternal effects are ignored. We also discuss the potential for dominance genetic variance to contribute to the estimate of maternal effects variance.

  1. A fully-stochasticized, age-structured population model for population viability analysis of fish: Lower Missouri River endangered pallid sturgeon example

    USGS Publications Warehouse

    Wildhaber, Mark L.; Albers, Janice; Green, Nicholas; Moran, Edward H.

    2017-01-01

    We develop a fully-stochasticized, age-structured population model suitable for population viability analysis (PVA) of fish and demonstrate its use with the endangered pallid sturgeon (Scaphirhynchus albus) of the Lower Missouri River as an example. The model incorporates three levels of variance: parameter variance (uncertainty about the value of a parameter itself) applied at the iteration level, temporal variance (uncertainty caused by random environmental fluctuations over time) applied at the time-step level, and implicit individual variance (uncertainty caused by differences between individuals) applied within the time-step level. We found that population dynamics were most sensitive to survival rates, particularly age-2+ survival, and to fecundity-at-length. The inclusion of variance (unpartitioned or partitioned), stocking, or both generally decreased the influence of individual parameters on population growth rate. The partitioning of variance into parameter and temporal components had a strong influence on the importance of individual parameters, uncertainty of model predictions, and quasiextinction risk (i.e., pallid sturgeon population size falling below 50 age-1+ individuals). Our findings show that appropriately applying variance in PVA is important when evaluating the relative importance of parameters, and reinforce the need for better and more precise estimates of crucial life-history parameters for pallid sturgeon.

  2. Is There a Common Summary Statistical Process for Representing the Mean and Variance? A Study Using Illustrations of Familiar Items

    PubMed Central

    Yang, Yi; Tokita, Midori; Ishiguchi, Akira

    2018-01-01

    A number of studies revealed that our visual system can extract different types of summary statistics, such as the mean and variance, from sets of items. Although the extraction of such summary statistics has been studied well in isolation, the relationship between these statistics remains unclear. In this study, we explored this issue using an individual differences approach. Observers viewed illustrations of strawberries and lollypops varying in size or orientation and performed four tasks in a within-subject design, namely mean and variance discrimination tasks with size and orientation domains. We found that the performances in the mean and variance discrimination tasks were not correlated with each other and demonstrated that extractions of the mean and variance are mediated by different representation mechanisms. In addition, we tested the relationship between performances in size and orientation domains for each summary statistic (i.e. mean and variance) and examined whether each summary statistic has distinct processes across perceptual domains. The results illustrated that statistical summary representations of size and orientation may share a common mechanism for representing the mean and possibly for representing variance. Introspections for each observer performing the tasks were also examined and discussed. PMID:29399318

  3. Precision of systematic and random sampling in clustered populations: habitat patches and aggregating organisms.

    PubMed

    McGarvey, Richard; Burch, Paul; Matthews, Janet M

    2016-01-01

    Natural populations of plants and animals spatially cluster because (1) suitable habitat is patchy, and (2) within suitable habitat, individuals aggregate further into clusters of higher density. We compare the precision of random and systematic field sampling survey designs under these two processes of species clustering. Second, we evaluate the performance of 13 estimators for the variance of the sample mean from a systematic survey. Replicated simulated surveys, as counts from 100 transects, allocated either randomly or systematically within the study region, were used to estimate population density in six spatial point populations including habitat patches and Matérn circular clustered aggregations of organisms, together and in combination. The standard one-start aligned systematic survey design, a uniform 10 x 10 grid of transects, was much more precise. Variances of the 10 000 replicated systematic survey mean densities were one-third to one-fifth of those from randomly allocated transects, implying transect sample sizes giving equivalent precision by random survey would need to be three to five times larger. Organisms being restricted to patches of habitat was alone sufficient to yield this precision advantage for the systematic design. But this improved precision for systematic sampling in clustered populations is underestimated by standard variance estimators used to compute confidence intervals. True variance for the survey sample mean was computed from the variance of 10 000 simulated survey mean estimates. Testing 10 published and three newly proposed variance estimators, the two variance estimators (v) that corrected for inter-transect correlation (ν₈ and ν(W)) were the most accurate and also the most precise in clustered populations. These greatly outperformed the two "post-stratification" variance estimators (ν₂ and ν₃) that are now more commonly applied in systematic surveys. Similar variance estimator performance rankings were found with a second differently generated set of spatial point populations, ν₈ and ν(W) again being the best performers in the longer-range autocorrelated populations. However, no systematic variance estimators tested were free from bias. On balance, systematic designs bring more narrow confidence intervals in clustered populations, while random designs permit unbiased estimates of (often wider) confidence interval. The search continues for better estimators of sampling variance for the systematic survey mean.

  4. Allan Variance Computed in Space Domain: Definition and Application to InSAR Data to Characterize Noise and Geophysical Signal.

    PubMed

    Cavalié, Olivier; Vernotte, François

    2016-04-01

    The Allan variance was introduced 50 years ago for analyzing the stability of frequency standards. In addition to its metrological interest, it may be also considered as an estimator of the large trends of the power spectral density (PSD) of frequency deviation. For instance, the Allan variance is able to discriminate different types of noise characterized by different power laws in the PSD. The Allan variance was also used in other fields than time and frequency metrology: for more than 20 years, it has been used in accelerometry, geophysics, geodesy, astrophysics, and even finances. However, it seems that up to now, it has been exclusively applied for time series analysis. We propose here to use the Allan variance on spatial data. Interferometric synthetic aperture radar (InSAR) is used in geophysics to image ground displacements in space [over the synthetic aperture radar (SAR) image spatial coverage] and in time thanks to the regular SAR image acquisitions by dedicated satellites. The main limitation of the technique is the atmospheric disturbances that affect the radar signal while traveling from the sensor to the ground and back. In this paper, we propose to use the Allan variance for analyzing spatial data from InSAR measurements. The Allan variance was computed in XY mode as well as in radial mode for detecting different types of behavior for different space-scales, in the same way as the different types of noise versus the integration time in the classical time and frequency application. We found that radial Allan variance is the more appropriate way to have an estimator insensitive to the spatial axis and we applied it on SAR data acquired over eastern Turkey for the period 2003-2011. Spatial Allan variance allowed us to well characterize noise features, classically found in InSAR such as phase decorrelation producing white noise or atmospheric delays, behaving like a random walk signal. We finally applied the spatial Allan variance to an InSAR time series to detect when the geophysical signal, here the ground motion, emerges from the noise.

  5. Genomic estimation of additive and dominance effects and impact of accounting for dominance on accuracy of genomic evaluation in sheep populations.

    PubMed

    Moghaddar, N; van der Werf, J H J

    2017-12-01

    The objectives of this study were to estimate the additive and dominance variance component of several weight and ultrasound scanned body composition traits in purebred and combined cross-bred sheep populations based on single nucleotide polymorphism (SNP) marker genotypes and then to investigate the effect of fitting additive and dominance effects on accuracy of genomic evaluation. Additive and dominance variance components were estimated in a mixed model equation based on "average information restricted maximum likelihood" using additive and dominance (co)variances between animals calculated from 48,599 SNP marker genotypes. Genomic prediction was based on genomic best linear unbiased prediction (GBLUP), and the accuracy of prediction was assessed based on a random 10-fold cross-validation. Across different weight and scanned body composition traits, dominance variance ranged from 0.0% to 7.3% of the phenotypic variance in the purebred population and from 7.1% to 19.2% in the combined cross-bred population. In the combined cross-bred population, the range of dominance variance decreased to 3.1% and 9.9% after accounting for heterosis effects. Accounting for dominance effects significantly improved the likelihood of the fitting model in the combined cross-bred population. This study showed a substantial dominance genetic variance for weight and ultrasound scanned body composition traits particularly in cross-bred population; however, improvement in the accuracy of genomic breeding values was small and statistically not significant. Dominance variance estimates in combined cross-bred population could be overestimated if heterosis is not fitted in the model. © 2017 Blackwell Verlag GmbH.

  6. Defining ulnar variance in the adolescent wrist: measurement technique and interobserver reliability.

    PubMed

    Goldfarb, Charles A; Strauss, Nicole L; Wall, Lindley B; Calfee, Ryan P

    2011-02-01

    The measurement technique for ulnar variance in the adolescent population has not been well established. The purpose of this study was to assess the reliability of a standard ulnar variance assessment in the adolescent population. Four orthopedic surgeons measured 138 adolescent wrist radiographs for ulnar variance using a standard technique. There were 62 male and 76 female radiographs obtained in a standardized fashion for subjects aged 12 to 18 years. Skeletal age was used for analysis. We determined mean variance and assessed for differences related to age and gender. We also determined the interrater reliability. The mean variance was -0.7 mm for boys and -0.4 mm for girls; there was no significant difference between the 2 groups overall. When subdivided by age and gender, the younger group (≤ 15 y of age) was significantly less negative for girls (boys, -0.8 mm and girls, -0.3 mm, p < .05). There was no significant difference between boys and girls in the older group. The greatest difference between any 2 raters was 1 mm; exact agreement was obtained in 72 subjects. Correlations between raters were high (r(p) 0.87-0.97 in boys and 0.82-0.96 for girls). Interrater reliability was excellent (Cronbach's alpha, 0.97-0.98). Standard assessment techniques for ulnar variance are reliable in the adolescent population. Open growth plates did not interfere with this assessment. Young adolescent boys demonstrated a greater degree of negative ulnar variance compared with young adolescent girls. Copyright © 2011 American Society for Surgery of the Hand. Published by Elsevier Inc. All rights reserved.

  7. Vowel category dependence of the relationship between palate height, tongue height, and oral area.

    PubMed

    Hasegawa-Johnson, Mark; Pizza, Shamala; Alwan, Abeer; Cha, Jul Setsu; Haker, Katherine

    2003-06-01

    This article evaluates intertalker variance of oral area, logarithm of the oral area, tongue height, and formant frequencies as a function of vowel category. The data consist of coronal magnetic resonance imaging (MRI) sequences and acoustic recordings of 5 talkers, each producing 11 different vowels. Tongue height (left, right, and midsagittal), palate height, and oral area were measured in 3 coronal sections anterior to the oropharyngeal bend and were subjected to multivariate analysis of variance, variance ratio analysis, and regression analysis. The primary finding of this article is that oral area (between palate and tongue) showed less intertalker variance during production of vowels with an oral place of articulation (palatal and velar vowels) than during production of vowels with a uvular or pharyngeal place of articulation. Although oral area variance is place dependent, percentage variance (log area variance) is not place dependent. Midsagittal tongue height in the molar region was positively correlated with palate height during production of palatal vowels, but not during production of nonpalatal vowels. Taken together, these results suggest that small oral areas are characterized by relatively talker-independent vowel targets and that meeting these talker-independent targets is important enough that each talker adjusts his or her own tongue height to compensate for talker-dependent differences in constriction anatomy. Computer simulation results are presented to demonstrate that these results may be explained by an acoustic control strategy: When talkers with very different anatomical characteristics try to match talker-independent formant targets, the resulting area variances are minimized near the primary vocal tract constriction.

  8. Using variance structure to quantify responses to perturbation in fish catches

    USGS Publications Warehouse

    Vidal, Tiffany E.; Irwin, Brian J.; Wagner, Tyler; Rudstam, Lars G.; Jackson, James R.; Bence, James R.

    2017-01-01

    We present a case study evaluation of gill-net catches of Walleye Sander vitreus to assess potential effects of large-scale changes in Oneida Lake, New York, including the disruption of trophic interactions by double-crested cormorants Phalacrocorax auritus and invasive dreissenid mussels. We used the empirical long-term gill-net time series and a negative binomial linear mixed model to partition the variability in catches into spatial and coherent temporal variance components, hypothesizing that variance partitioning can help quantify spatiotemporal variability and determine whether variance structure differs before and after large-scale perturbations. We found that the mean catch and the total variability of catches decreased following perturbation but that not all sampling locations responded in a consistent manner. There was also evidence of some spatial homogenization concurrent with a restructuring of the relative productivity of individual sites. Specifically, offshore sites generally became more productive following the estimated break point in the gill-net time series. These results provide support for the idea that variance structure is responsive to large-scale perturbations; therefore, variance components have potential utility as statistical indicators of response to a changing environment more broadly. The modeling approach described herein is flexible and would be transferable to other systems and metrics. For example, variance partitioning could be used to examine responses to alternative management regimes, to compare variability across physiographic regions, and to describe differences among climate zones. Understanding how individual variance components respond to perturbation may yield finer-scale insights into ecological shifts than focusing on patterns in the mean responses or total variability alone.

  9. The variance of angle-of-arrival fluctuation of partially coherent Gaussian-Schell Model beam propagations in slant atmospheric turbulence

    NASA Astrophysics Data System (ADS)

    Tan, Zhenkun; Ke, Xizheng

    2017-10-01

    The variance of angle-of-arrival fluctuation of the partially coherent Gaussian-Schell Model (GSM) beam propagations in the slant path, based on the extended Huygens-Fresnel principle and the model of atmospheric refraction index structural constant proposed by the international telecommunication union-radio (ITU-R), has been investigated under the modified Hill turbulence model. The expression of that has been obtained. Firstly, the effects of optical wavelength, the inner-and-outer scale of the turbulence and turbulence intensity on the variance of angle-of-arrival fluctuation have been analyzed by comparing with the partially coherent GSM beam and the completely coherent Gaussian beam. Secondly, the variance of angle-of-arrival fluctuation has been compared with the von Karman spectrum and the modified Hill spectrum under the partially coherent GSM beam. Finally, the effects of beam waist radius and partial coherence length on the variance of angle-of-arrival of the collimated (focused) beam have been analyzed under the modified Hill turbulence model. The results show that the influence of the variance of angle-of-arrival fluctuation for the inner scale effect is larger than that of the outer scale effect. The variance of angle-of-arrival fluctuation under the modified Hill spectrum is larger than that of the von Karman spectrum. The influence of the waist radius on the variance of angle-of-arrival for the collimated beam is less than focused the beam. This study will provide a necessary theoretical basis for the experiments of partially coherent GSM beam propagation through atmosphere turbulence.

  10. Statistical aspects of quantitative real-time PCR experiment design.

    PubMed

    Kitchen, Robert R; Kubista, Mikael; Tichopad, Ales

    2010-04-01

    Experiments using quantitative real-time PCR to test hypotheses are limited by technical and biological variability; we seek to minimise sources of confounding variability through optimum use of biological and technical replicates. The quality of an experiment design is commonly assessed by calculating its prospective power. Such calculations rely on knowledge of the expected variances of the measurements of each group of samples and the magnitude of the treatment effect; the estimation of which is often uninformed and unreliable. Here we introduce a method that exploits a small pilot study to estimate the biological and technical variances in order to improve the design of a subsequent large experiment. We measure the variance contributions at several 'levels' of the experiment design and provide a means of using this information to predict both the total variance and the prospective power of the assay. A validation of the method is provided through a variance analysis of representative genes in several bovine tissue-types. We also discuss the effect of normalisation to a reference gene in terms of the measured variance components of the gene of interest. Finally, we describe a software implementation of these methods, powerNest, that gives the user the opportunity to input data from a pilot study and interactively modify the design of the assay. The software automatically calculates expected variances, statistical power, and optimal design of the larger experiment. powerNest enables the researcher to minimise the total confounding variance and maximise prospective power for a specified maximum cost for the large study. Copyright 2010 Elsevier Inc. All rights reserved.

  11. CMB-S4 and the hemispherical variance anomaly

    NASA Astrophysics Data System (ADS)

    O'Dwyer, Márcio; Copi, Craig J.; Knox, Lloyd; Starkman, Glenn D.

    2017-09-01

    Cosmic microwave background (CMB) full-sky temperature data show a hemispherical asymmetry in power nearly aligned with the Ecliptic. In real space, this anomaly can be quantified by the temperature variance in the Northern and Southern Ecliptic hemispheres, with the Northern hemisphere displaying an anomalously low variance while the Southern hemisphere appears unremarkable [consistent with expectations from the best-fitting theory, Lambda Cold Dark Matter (ΛCDM)]. While this is a well-established result in temperature, the low signal-to-noise ratio in current polarization data prevents a similar comparison. This will change with a proposed ground-based CMB experiment, CMB-S4. With that in mind, we generate realizations of polarization maps constrained by the temperature data and predict the distribution of the hemispherical variance in polarization considering two different sky coverage scenarios possible in CMB-S4: full Ecliptic north coverage and just the portion of the North that can be observed from a ground-based telescope at the high Chilean Atacama plateau. We find that even in the set of realizations constrained by the temperature data, the low Northern hemisphere variance observed in temperature is not expected in polarization. Therefore, observing an anomalously low variance in polarization would make the hypothesis that the temperature anomaly is simply a statistical fluke more unlikely and thus increase the motivation for physical explanations. We show, within ΛCDM, how variance measurements in both sky coverage scenarios are related. We find that the variance makes for a good statistic in cases where the sky coverage is limited, however, full northern coverage is still preferable.

  12. Consistent Small-Sample Variances for Six Gamma-Family Measures of Ordinal Association

    ERIC Educational Resources Information Center

    Woods, Carol M.

    2009-01-01

    Gamma-family measures are bivariate ordinal correlation measures that form a family because they all reduce to Goodman and Kruskal's gamma in the absence of ties (1954). For several gamma-family indices, more than one variance estimator has been introduced. In previous research, the "consistent" variance estimator described by Cliff and…

  13. Estimating the Reliability of Single-Item Life Satisfaction Measures: Results from Four National Panel Studies

    ERIC Educational Resources Information Center

    Lucas, Richard E.; Donnellan, M. Brent

    2012-01-01

    Life satisfaction is often assessed using single-item measures. However, estimating the reliability of these measures can be difficult because internal consistency coefficients cannot be calculated. Existing approaches use longitudinal data to isolate occasion-specific variance from variance that is either completely stable or variance that…

  14. 40 CFR 142.20 - State-issued variances and exemptions under Section 1415(a) and Section 1416 of the Act.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... the Act; and (C) Ownership changes, physical consolidation with another public water system, or other... ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER... responsibility may issue variances to public water systems (other than small system variances) from the...

  15. Comparing Mapped Plot Estimators

    Treesearch

    Paul C. Van Deusen

    2006-01-01

    Two alternative derivations of estimators for mean and variance from mapped plots are compared by considering the models that support the estimators and by simulation. It turns out that both models lead to the same estimator for the mean but lead to very different variance estimators. The variance estimators based on the least valid model assumptions are shown to...

  16. 42 CFR 488.64 - Remote facility variances for utilization review requirements.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 42 Public Health 5 2010-10-01 2010-10-01 false Remote facility variances for utilization review... PROCEDURES Special Requirements § 488.64 Remote facility variances for utilization review requirements. (a... such facility or direct responsibility for the care of the patients being reviewed or, in the case of a...

  17. Estimation of Variance in the Case of Complex Samples.

    ERIC Educational Resources Information Center

    Groenewald, A. C.; Stoker, D. J.

    In a complex sampling scheme it is desirable to select the primary sampling units (PSUs) without replacement to prevent duplications in the sample. Since the estimation of the sampling variances is more complicated when the PSUs are selected without replacement, L. Kish (1965) recommends that the variance be calculated using the formulas…

  18. 40 CFR 59.509 - Can I get a variance?

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 40 Protection of Environment 5 2010-07-01 2010-07-01 false Can I get a variance? 59.509 Section 59... Volatile Organic Compound Emission Standards for Aerosol Coatings § 59.509 Can I get a variance? (a) Any... compliance plan proposed by the applicant can reasonably be implemented and will achieve compliance as...

  19. An Analysis of Variance Framework for Matrix Sampling.

    ERIC Educational Resources Information Center

    Sirotnik, Kenneth

    Significant cost savings can be achieved with the use of matrix sampling in estimating population parameters from psychometric data. The statistical design is intuitively simple, using the framework of the two-way classification analysis of variance technique. For example, the mean and variance are derived from the performance of a certain grade…

  20. 40 CFR 142.20 - State-issued variances and exemptions under Section 1415(a) and Section 1416 of the Act.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... State must consider the availability of an alternative source of water, including the feasibility of... ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER... responsibility may issue variances to public water systems (other than small system variances) from the...

  1. 40 CFR 142.20 - State-issued variances and exemptions under Section 1415(a) and Section 1416 of the Act.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... the Act; and (C) Ownership changes, physical consolidation with another public water system, or other... ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER... responsibility may issue variances to public water systems (other than small system variances) from the...

  2. Estimation of genetic parameters and their sampling variances of quantitative traits in the type 2 modified augmented design

    USDA-ARS?s Scientific Manuscript database

    We proposed a method to estimate the error variance among non-replicated genotypes, thus to estimate the genetic parameters by using replicated controls. We derived formulas to estimate sampling variances of the genetic parameters. Computer simulation indicated that the proposed methods of estimatin...

  3. Conceptual Complexity and the Bias/Variance Tradeoff

    ERIC Educational Resources Information Center

    Briscoe, Erica; Feldman, Jacob

    2011-01-01

    In this paper we propose that the conventional dichotomy between exemplar-based and prototype-based models of concept learning is helpfully viewed as an instance of what is known in the statistical learning literature as the "bias/variance tradeoff". The bias/variance tradeoff can be thought of as a sliding scale that modulates how closely any…

  4. It Depends on the Partner: Person-Related Sources of Efficacy Beliefs and Performance for Athlete Pairs.

    PubMed

    Habeeb, Christine M; Eklund, Robert C; Coffee, Pete

    2017-06-01

    This study explored person-related sources of variance in athletes' efficacy beliefs and performances when performing in pairs with distinguishable roles differing in partner dependence. College cheerleaders (n = 102) performed their role in repeated performance trials of two low- and two high-difficulty paired-stunt tasks with three different partners. Data were obtained on self-, other-, and collective efficacy beliefs and subjective performances, and objective performance assessments were obtained from digital recordings. Using the social relations model framework, total variance in each belief/assessment was partitioned, for each role, into numerical components of person-related variance relative to the self, the other, and the collective. Variance component by performance role by task-difficulty repeated-measures analysis of variances revealed that the largest person-related variance component differed by athlete role and increased in size in high-difficulty tasks. Results suggest that the extent the athlete's performance depends on a partner relates to the extent the partner is a source of self-, other-, and collective efficacy beliefs.

  5. Uncertainty importance analysis using parametric moment ratio functions.

    PubMed

    Wei, Pengfei; Lu, Zhenzhou; Song, Jingwen

    2014-02-01

    This article presents a new importance analysis framework, called parametric moment ratio function, for measuring the reduction of model output uncertainty when the distribution parameters of inputs are changed, and the emphasis is put on the mean and variance ratio functions with respect to the variances of model inputs. The proposed concepts efficiently guide the analyst to achieve a targeted reduction on the model output mean and variance by operating on the variances of model inputs. The unbiased and progressive unbiased Monte Carlo estimators are also derived for the parametric mean and variance ratio functions, respectively. Only a set of samples is needed for implementing the proposed importance analysis by the proposed estimators, thus the computational cost is free of input dimensionality. An analytical test example with highly nonlinear behavior is introduced for illustrating the engineering significance of the proposed importance analysis technique and verifying the efficiency and convergence of the derived Monte Carlo estimators. Finally, the moment ratio function is applied to a planar 10-bar structure for achieving a targeted 50% reduction of the model output variance. © 2013 Society for Risk Analysis.

  6. Allowing variance may enlarge the safe operating space for exploited ecosystems.

    PubMed

    Carpenter, Stephen R; Brock, William A; Folke, Carl; van Nes, Egbert H; Scheffer, Marten

    2015-11-17

    Variable flows of food, water, or other ecosystem services complicate planning. Management strategies that decrease variability and increase predictability may therefore be preferred. However, actions to decrease variance over short timescales (2-4 y), when applied continuously, may lead to long-term ecosystem changes with adverse consequences. We investigated the effects of managing short-term variance in three well-understood models of ecosystem services: lake eutrophication, harvest of a wild population, and yield of domestic herbivores on a rangeland. In all cases, actions to decrease variance can increase the risk of crossing critical ecosystem thresholds, resulting in less desirable ecosystem states. Managing to decrease short-term variance creates ecosystem fragility by changing the boundaries of safe operating spaces, suppressing information needed for adaptive management, cancelling signals of declining resilience, and removing pressures that may build tolerance of stress. Thus, the management of variance interacts strongly and inseparably with the management of resilience. By allowing for variation, learning, and flexibility while observing change, managers can detect opportunities and problems as they develop while sustaining the capacity to deal with them.

  7. Online Estimation of Allan Variance Coefficients Based on a Neural-Extended Kalman Filter

    PubMed Central

    Miao, Zhiyong; Shen, Feng; Xu, Dingjie; He, Kunpeng; Tian, Chunmiao

    2015-01-01

    As a noise analysis method for inertial sensors, the traditional Allan variance method requires the storage of a large amount of data and manual analysis for an Allan variance graph. Although the existing online estimation methods avoid the storage of data and the painful procedure of drawing slope lines for estimation, they require complex transformations and even cause errors during the modeling of dynamic Allan variance. To solve these problems, first, a new state-space model that directly models the stochastic errors to obtain a nonlinear state-space model was established for inertial sensors. Then, a neural-extended Kalman filter algorithm was used to estimate the Allan variance coefficients. The real noises of an ADIS16405 IMU and fiber optic gyro-sensors were analyzed by the proposed method and traditional methods. The experimental results show that the proposed method is more suitable to estimate the Allan variance coefficients than the traditional methods. Moreover, the proposed method effectively avoids the storage of data and can be easily implemented using an online processor. PMID:25625903

  8. Allowing variance may enlarge the safe operating space for exploited ecosystems

    PubMed Central

    Carpenter, Stephen R.; Brock, William A.; Folke, Carl; van Nes, Egbert H.; Scheffer, Marten

    2015-01-01

    Variable flows of food, water, or other ecosystem services complicate planning. Management strategies that decrease variability and increase predictability may therefore be preferred. However, actions to decrease variance over short timescales (2–4 y), when applied continuously, may lead to long-term ecosystem changes with adverse consequences. We investigated the effects of managing short-term variance in three well-understood models of ecosystem services: lake eutrophication, harvest of a wild population, and yield of domestic herbivores on a rangeland. In all cases, actions to decrease variance can increase the risk of crossing critical ecosystem thresholds, resulting in less desirable ecosystem states. Managing to decrease short-term variance creates ecosystem fragility by changing the boundaries of safe operating spaces, suppressing information needed for adaptive management, cancelling signals of declining resilience, and removing pressures that may build tolerance of stress. Thus, the management of variance interacts strongly and inseparably with the management of resilience. By allowing for variation, learning, and flexibility while observing change, managers can detect opportunities and problems as they develop while sustaining the capacity to deal with them. PMID:26438857

  9. Time and resource limits on working memory: cross-age consistency in counting span performance.

    PubMed

    Ransdell, Sarah; Hecht, Steven

    2003-12-01

    This longitudinal study separated resource demand effects from those of retention interval in a counting span task among 100 children tested in grade 2 and again in grades 3 and 4. A last card large counting span condition had an equivalent memory load to a last card small, but the last card large required holding the count over a longer retention interval. In all three waves of assessment, the last card large condition was found to be less accurate than the last card small. A model predicting reading comprehension showed that age was a significant predictor when entered first accounting for 26% of the variance, but counting span accounted for a further 22% of the variance. Span at Wave 1 accounted for significant unique variance at Wave 2 and at Wave 3. Results were similar for math calculation with age accounting for 31% of the variance and counting span accounting for a further 34% of the variance. Span at Wave 1 explained unique variance in math at Wave 2 and at Wave 3.

  10. A Multilevel AR(1) Model: Allowing for Inter-Individual Differences in Trait-Scores, Inertia, and Innovation Variance.

    PubMed

    Jongerling, Joran; Laurenceau, Jean-Philippe; Hamaker, Ellen L

    2015-01-01

    In this article we consider a multilevel first-order autoregressive [AR(1)] model with random intercepts, random autoregression, and random innovation variance (i.e., the level 1 residual variance). Including random innovation variance is an important extension of the multilevel AR(1) model for two reasons. First, between-person differences in innovation variance are important from a substantive point of view, in that they capture differences in sensitivity and/or exposure to unmeasured internal and external factors that influence the process. Second, using simulation methods we show that modeling the innovation variance as fixed across individuals, when it should be modeled as a random effect, leads to biased parameter estimates. Additionally, we use simulation methods to compare maximum likelihood estimation to Bayesian estimation of the multilevel AR(1) model and investigate the trade-off between the number of individuals and the number of time points. We provide an empirical illustration by applying the extended multilevel AR(1) model to daily positive affect ratings from 89 married women over the course of 42 consecutive days.

  11. Selecting band combinations with thematic mapper data

    NASA Technical Reports Server (NTRS)

    Sheffield, C. A.

    1983-01-01

    A problem arises in making color composite images because there are 210 different possible color presentations of TM three-band images. A method is given for reducing that 210 to a single choice, decided by the statistics of a scene or subscene, and taking into full account any correlations that exist between different bands. Instead of using total variance as the measure for information content of the band triplets, the ellipsoid of maximum volume is selected which discourages selection of bands with high correlation. The band triplet is obtained by computing and ranking in order the determinants of each 3 x 3 principal submatrix of the original matrix M. After selection of the best triplet, the assignment of colors is made by using the actual variances (the diagonal elements of M): green (maximum variance), red (second largest variance), blue (smallest variance).

  12. The dispersion of age differences between partners and the asymptotic dynamics of the HIV epidemic.

    PubMed

    d'Albis, Hippolyte; Augeraud-Véron, Emmanuelle; Djemai, Elodie; Ducrot, Arnaud

    2012-01-01

    In this paper, the effect of a change in the distribution of age differences between sexual partners on the dynamics of the HIV epidemic is studied. In a gender- and age-structured compartmental model, it is shown that if the variance of the distribution is small enough, an increase in this variance strongly increases the basic reproduction number. Moreover, if the variance is large enough, the mean age difference barely affects the basic reproduction number. We, therefore, conclude that the local stability of the disease-free equilibrium relies more on the variance than on the mean.

  13. Sources of variation in an enzyme-linked immunoassay of bluetongue virus in Culicoides variipennis (Diptera: Ceratopogonidae).

    PubMed

    Tabachnick, W J; Mecham, J O

    1991-03-01

    An enzyme-linked immunoassay for detecting bluetongue virus in infected Culicoides variipennis was evaluated using a nested analysis of variance to determine sources of experimental error in the procedure. The major source of variation was differences among individual insects (84% of the total variance). Storing insects at -70 degrees C for two months contributed to experimental variation in the ELISA reading (14% of the total variance) and should be avoided. Replicate assays of individual insects were shown to be unnecessary, since variation among replicate wells and plates was minor (2% of the total variance).

  14. A Versatile Omnibus Test for Detecting Mean and Variance Heterogeneity

    PubMed Central

    Bailey, Matthew; Kauwe, John S. K.; Maxwell, Taylor J.

    2014-01-01

    Recent research has revealed loci that display variance heterogeneity through various means such as biological disruption, linkage disequilibrium (LD), gene-by-gene (GxG), or gene-by-environment (GxE) interaction. We propose a versatile likelihood ratio test that allows joint testing for mean and variance heterogeneity (LRTMV) or either effect alone (LRTM or LRTV) in the presence of covariates. Using extensive simulations for our method and others we found that all parametric tests were sensitive to non-normality regardless of any trait transformations. Coupling our test with the parametric bootstrap solves this issue. Using simulations and empirical data from a known mean-only functional variant we demonstrate how linkage disequilibrium (LD) can produce variance-heterogeneity loci (vQTL) in a predictable fashion based on differential allele frequencies, high D’ and relatively low r2 values. We propose that a joint test for mean and variance heterogeneity is more powerful than a variance only test for detecting vQTL. This takes advantage of loci that also have mean effects without sacrificing much power to detect variance only effects. We discuss using vQTL as an approach to detect gene-by-gene interactions and also how vQTL are related to relationship loci (rQTL) and how both can create prior hypothesis for each other and reveal the relationships between traits and possibly between components of a composite trait. PMID:24482837

  15. Multi-objective Optimization of Solar Irradiance and Variance at Pertinent Inclination Angles

    NASA Astrophysics Data System (ADS)

    Jain, Dhanesh; Lalwani, Mahendra

    2018-05-01

    The performance of photovoltaic panel gets highly affected bychange in atmospheric conditions and angle of inclination. This article evaluates the optimum tilt angle and orientation angle (surface azimuth angle) for solar photovoltaic array in order to get maximum solar irradiance and to reduce variance of radiation at different sets or subsets of time periods. Non-linear regression and adaptive neural fuzzy interference system (ANFIS) methods are used for predicting the solar radiation. The results of ANFIS are more accurate in comparison to non-linear regression. These results are further used for evaluating the correlation and applied for estimating the optimum combination of tilt angle and orientation angle with the help of general algebraic modelling system and multi-objective genetic algorithm. The hourly average solar irradiation is calculated at different combinations of tilt angle and orientation angle with the help of horizontal surface radiation data of Jodhpur (Rajasthan, India). The hourly average solar irradiance is calculated for three cases: zero variance, with actual variance and with double variance at different time scenarios. It is concluded that monthly collected solar radiation produces better result as compared to bimonthly, seasonally, half-yearly and yearly collected solar radiation. The profit obtained for monthly varying angle has 4.6% more with zero variance and 3.8% more with actual variance, than the annually fixed angle.

  16. The influence of local spring temperature variance on temperature sensitivity of spring phenology.

    PubMed

    Wang, Tao; Ottlé, Catherine; Peng, Shushi; Janssens, Ivan A; Lin, Xin; Poulter, Benjamin; Yue, Chao; Ciais, Philippe

    2014-05-01

    The impact of climate warming on the advancement of plant spring phenology has been heavily investigated over the last decade and there exists great variability among plants in their phenological sensitivity to temperature. However, few studies have explicitly linked phenological sensitivity to local climate variance. Here, we set out to test the hypothesis that the strength of phenological sensitivity declines with increased local spring temperature variance, by synthesizing results across ground observations. We assemble ground-based long-term (20-50 years) spring phenology database (PEP725 database) and the corresponding climate dataset. We find a prevalent decline in the strength of phenological sensitivity with increasing local spring temperature variance at the species level from ground observations. It suggests that plants might be less likely to track climatic warming at locations with larger local spring temperature variance. This might be related to the possibility that the frost risk could be higher in a larger local spring temperature variance and plants adapt to avoid this risk by relying more on other cues (e.g., high chill requirements, photoperiod) for spring phenology, thus suppressing phenological responses to spring warming. This study illuminates that local spring temperature variance is an understudied source in the study of phenological sensitivity and highlight the necessity of incorporating this factor to improve the predictability of plant responses to anthropogenic climate change in future studies. © 2013 John Wiley & Sons Ltd.

  17. Analysis of a genetically structured variance heterogeneity model using the Box-Cox transformation.

    PubMed

    Yang, Ye; Christensen, Ole F; Sorensen, Daniel

    2011-02-01

    Over recent years, statistical support for the presence of genetic factors operating at the level of the environmental variance has come from fitting a genetically structured heterogeneous variance model to field or experimental data in various species. Misleading results may arise due to skewness of the marginal distribution of the data. To investigate how the scale of measurement affects inferences, the genetically structured heterogeneous variance model is extended to accommodate the family of Box-Cox transformations. Litter size data in rabbits and pigs that had previously been analysed in the untransformed scale were reanalysed in a scale equal to the mode of the marginal posterior distribution of the Box-Cox parameter. In the rabbit data, the statistical evidence for a genetic component at the level of the environmental variance is considerably weaker than that resulting from an analysis in the original metric. In the pig data, the statistical evidence is stronger, but the coefficient of correlation between additive genetic effects affecting mean and variance changes sign, compared to the results in the untransformed scale. The study confirms that inferences on variances can be strongly affected by the presence of asymmetry in the distribution of data. We recommend that to avoid one important source of spurious inferences, future work seeking support for a genetic component acting on environmental variation using a parametric approach based on normality assumptions confirms that these are met.

  18. Origin and Consequences of the Relationship between Protein Mean and Variance

    PubMed Central

    Vallania, Francesco Luigi Massimo; Sherman, Marc; Goodwin, Zane; Mogno, Ilaria; Cohen, Barak Alon; Mitra, Robi David

    2014-01-01

    Cell-to-cell variance in protein levels (noise) is a ubiquitous phenomenon that can increase fitness by generating phenotypic differences within clonal populations of cells. An important challenge is to identify the specific molecular events that control noise. This task is complicated by the strong dependence of a protein's cell-to-cell variance on its mean expression level through a power-law like relationship (σ2∝μ1.69). Here, we dissect the nature of this relationship using a stochastic model parameterized with experimentally measured values. This framework naturally recapitulates the power-law like relationship (σ2∝μ1.6) and accurately predicts protein variance across the yeast proteome (r2 = 0.935). Using this model we identified two distinct mechanisms by which protein variance can be increased. Variables that affect promoter activation, such as nucleosome positioning, increase protein variance by changing the exponent of the power-law relationship. In contrast, variables that affect processes downstream of promoter activation, such as mRNA and protein synthesis, increase protein variance in a mean-dependent manner following the power-law. We verified our findings experimentally using an inducible gene expression system in yeast. We conclude that the power-law-like relationship between noise and protein mean is due to the kinetics of promoter activation. Our results provide a framework for understanding how molecular processes shape stochastic variation across the genome. PMID:25062021

  19. Model-based variance-stabilizing transformation for Illumina microarray data.

    PubMed

    Lin, Simon M; Du, Pan; Huber, Wolfgang; Kibbe, Warren A

    2008-02-01

    Variance stabilization is a step in the preprocessing of microarray data that can greatly benefit the performance of subsequent statistical modeling and inference. Due to the often limited number of technical replicates for Affymetrix and cDNA arrays, achieving variance stabilization can be difficult. Although the Illumina microarray platform provides a larger number of technical replicates on each array (usually over 30 randomly distributed beads per probe), these replicates have not been leveraged in the current log2 data transformation process. We devised a variance-stabilizing transformation (VST) method that takes advantage of the technical replicates available on an Illumina microarray. We have compared VST with log2 and Variance-stabilizing normalization (VSN) by using the Kruglyak bead-level data (2006) and Barnes titration data (2005). The results of the Kruglyak data suggest that VST stabilizes variances of bead-replicates within an array. The results of the Barnes data show that VST can improve the detection of differentially expressed genes and reduce false-positive identifications. We conclude that although both VST and VSN are built upon the same model of measurement noise, VST stabilizes the variance better and more efficiently for the Illumina platform by leveraging the availability of a larger number of within-array replicates. The algorithms and Supplementary Data are included in the lumi package of Bioconductor, available at: www.bioconductor.org.

  20. Methods to estimate the between‐study variance and its uncertainty in meta‐analysis†

    PubMed Central

    Jackson, Dan; Viechtbauer, Wolfgang; Bender, Ralf; Bowden, Jack; Knapp, Guido; Kuss, Oliver; Higgins, Julian PT; Langan, Dean; Salanti, Georgia

    2015-01-01

    Meta‐analyses are typically used to estimate the overall/mean of an outcome of interest. However, inference about between‐study variability, which is typically modelled using a between‐study variance parameter, is usually an additional aim. The DerSimonian and Laird method, currently widely used by default to estimate the between‐study variance, has been long challenged. Our aim is to identify known methods for estimation of the between‐study variance and its corresponding uncertainty, and to summarise the simulation and empirical evidence that compares them. We identified 16 estimators for the between‐study variance, seven methods to calculate confidence intervals, and several comparative studies. Simulation studies suggest that for both dichotomous and continuous data the estimator proposed by Paule and Mandel and for continuous data the restricted maximum likelihood estimator are better alternatives to estimate the between‐study variance. Based on the scenarios and results presented in the published studies, we recommend the Q‐profile method and the alternative approach based on a ‘generalised Cochran between‐study variance statistic’ to compute corresponding confidence intervals around the resulting estimates. Our recommendations are based on a qualitative evaluation of the existing literature and expert consensus. Evidence‐based recommendations require an extensive simulation study where all methods would be compared under the same scenarios. © 2015 The Authors. Research Synthesis Methods published by John Wiley & Sons Ltd. PMID:26332144

  1. Spectral decomposition of internal gravity wave sea surface height in global models

    NASA Astrophysics Data System (ADS)

    Savage, Anna C.; Arbic, Brian K.; Alford, Matthew H.; Ansong, Joseph K.; Farrar, J. Thomas; Menemenlis, Dimitris; O'Rourke, Amanda K.; Richman, James G.; Shriver, Jay F.; Voet, Gunnar; Wallcraft, Alan J.; Zamudio, Luis

    2017-10-01

    Two global ocean models ranging in horizontal resolution from 1/12° to 1/48° are used to study the space and time scales of sea surface height (SSH) signals associated with internal gravity waves (IGWs). Frequency-horizontal wavenumber SSH spectral densities are computed over seven regions of the world ocean from two simulations of the HYbrid Coordinate Ocean Model (HYCOM) and three simulations of the Massachusetts Institute of Technology general circulation model (MITgcm). High wavenumber, high-frequency SSH variance follows the predicted IGW linear dispersion curves. The realism of high-frequency motions (>0.87 cpd) in the models is tested through comparison of the frequency spectral density of dynamic height variance computed from the highest-resolution runs of each model (1/25° HYCOM and 1/48° MITgcm) with dynamic height variance frequency spectral density computed from nine in situ profiling instruments. These high-frequency motions are of particular interest because of their contributions to the small-scale SSH variability that will be observed on a global scale in the upcoming Surface Water and Ocean Topography (SWOT) satellite altimetry mission. The variance at supertidal frequencies can be comparable to the tidal and low-frequency variance for high wavenumbers (length scales smaller than ˜50 km), especially in the higher-resolution simulations. In the highest-resolution simulations, the high-frequency variance can be greater than the low-frequency variance at these scales.

  2. Variance and covariance estimates for weaning weight of Senepol cattle.

    PubMed

    Wright, D W; Johnson, Z B; Brown, C J; Wildeus, S

    1991-10-01

    Variance and covariance components were estimated for weaning weight from Senepol field data for use in the reduced animal model for a maternally influenced trait. The 4,634 weaning records were used to evaluate 113 sires and 1,406 dams on the island of St. Croix. Estimates of direct additive genetic variance (sigma 2A), maternal additive genetic variance (sigma 2M), covariance between direct and maternal additive genetic effects (sigma AM), permanent maternal environmental variance (sigma 2PE), and residual variance (sigma 2 epsilon) were calculated by equating variances estimated from a sire-dam model and a sire-maternal grandsire model, with and without the inverse of the numerator relationship matrix (A-1), to their expectations. Estimates were sigma 2A, 139.05 and 138.14 kg2; sigma 2M, 307.04 and 288.90 kg2; sigma AM, -117.57 and -103.76 kg2; sigma 2PE, -258.35 and -243.40 kg2; and sigma 2 epsilon, 588.18 and 577.72 kg2 with and without A-1, respectively. Heritability estimates for direct additive (h2A) were .211 and .210 with and without A-1, respectively. Heritability estimates for maternal additive (h2M) were .47 and .44 with and without A-1, respectively. Correlations between direct and maternal (IAM) effects were -.57 and -.52 with and without A-1, respectively.

  3. The Variance of Solar Wind Magnetic Fluctuations: Solutions and Further Puzzles

    NASA Technical Reports Server (NTRS)

    Roberts, D. A.; Goldstein, M. L.

    2006-01-01

    We study the dependence of the variance directions of the magnetic field in the solar wind as a function of scale, radial distance, and Alfvenicity. The study resolves the question of why different studies have arrived at widely differing values for the maximum to minimum power (approximately equal to 3:1 up to approximately equal to 20:1). This is due to the decreasing anisotropy with increasing time interval chosen for the variance, and is a direct result of the "spherical polarization" of the waves which follows from the near constancy of |B|. The reason for the magnitude preserving evolution is still unresolved. Moreover, while the long-known tendency for the minimum variance to lie along the mean field also follows from this view (as shown by Barnes many years ago), there is no theory for why the minimum variance follows the field direction as the Parker angle changes. We show that this turning is quite generally true in Alfvenic regions over a wide range of heliocentric distances. The fact that nonAlfvenic regions, while still showing strong power anisotropies, tend to have a much broader range of angles between the minimum variance and the mean field makes it unlikely that the cause of the variance turning is to be found in a turbulence mechanism. There are no obvious alternative mechanisms, leaving us with another intriguing puzzle.

  4. Observed spatiotemporal variability of boundary-layer turbulence over flat, heterogeneous terrain

    NASA Astrophysics Data System (ADS)

    Maurer, V.; Kalthoff, N.; Wieser, A.; Kohler, M.; Mauder, M.; Gantner, L.

    2016-02-01

    In the spring of 2013, extensive measurements with multiple Doppler lidar systems were performed. The instruments were arranged in a triangle with edge lengths of about 3 km in a moderately flat, agriculturally used terrain in northwestern Germany. For 6 mostly cloud-free convective days, vertical velocity variance profiles were calculated. Weighted-averaged surface fluxes proved to be more appropriate than data from individual sites for scaling the variance profiles; but even then, the scatter of profiles was mostly larger than the statistical error. The scatter could not be explained by mean wind speed or stability, whereas time periods with significantly increased variance contained broader thermals. Periods with an elevated maximum of the variance profiles could also be related to broad thermals. Moreover, statistically significant spatial differences of variance were found. They were not influenced by the existing surface heterogeneity. Instead, thermals were preserved between two sites when the travel time was shorter than the large-eddy turnover time. At the same time, no thermals passed for more than 2 h at a third site that was located perpendicular to the mean wind direction in relation to the first two sites. Organized structures of turbulence with subsidence prevailing in the surroundings of thermals can thus partly explain significant spatial variance differences existing for several hours. Therefore, the representativeness of individual variance profiles derived from measurements at a single site cannot be assumed.

  5. 40 CFR 142.303 - Which size public water systems can receive a small system variance?

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 40 Protection of Environment 22 2010-07-01 2010-07-01 false Which size public water systems can receive a small system variance? 142.303 Section 142.303 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS IMPLEMENTATION Variances for Small System General...

  6. Save money by understanding variance and tolerancing.

    PubMed

    Stuart, K

    2007-01-01

    Manufacturing processes are inherently variable, which results in component and assembly variance. Unless process capability, variance and tolerancing are fully understood, incorrect design tolerances may be applied, which will lead to more expensive tooling, inflated production costs, high reject rates, product recalls and excessive warranty costs. A methodology is described for correctly allocating tolerances and performing appropriate analyses.

  7. Environmental Influences on Well-Being: A Dyadic Latent Panel Analysis of Spousal Similarity

    ERIC Educational Resources Information Center

    Schimmack, Ulrich; Lucas, Richard E.

    2010-01-01

    This article uses dyadic latent panel analysis (DLPA) to examine environmental influences on well-being. DLPA requires longitudinal dyadic data. It decomposes the observed variance of both members of a dyad into a trait, state, and an error component. Furthermore, state variance is decomposed into initial and new state variance. Total observed…

  8. Genetic Variance in the F2 Generation of Divergently Selected Parents

    Treesearch

    M.P. Koshy; G. Namkoong; J.H. Roberds

    1998-01-01

    Either by selective breeding for population divergence or by using natural population differences, F2 and advanced generation hybrids can be developed with high variances. We relate the size of the genetic variance to the population divergence based on a forward and backward mutation model at a locus with two alleles with additive gene action....

  9. Robust Means Modeling: An Alternative for Hypothesis Testing of Independent Means under Variance Heterogeneity and Nonnormality

    ERIC Educational Resources Information Center

    Fan, Weihua; Hancock, Gregory R.

    2012-01-01

    This study proposes robust means modeling (RMM) approaches for hypothesis testing of mean differences for between-subjects designs in order to control the biasing effects of nonnormality and variance inequality. Drawing from structural equation modeling (SEM), the RMM approaches make no assumption of variance homogeneity and employ robust…

  10. 76 FR 19003 - Land Disposal Restrictions: Nevada and California; Site Specific Treatment Variances for...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-04-06

    ... both a site-specific treatment variance to U.S. Ecology Nevada (USEN) located in Beatty, Nevada and... site-specific treatment variance to U.S. Ecology Nevada (USEN) located in Beatty, Nevada and withdraw... section of this document. II. Does this action apply to me? This proposal applies only to U. S. Ecology...

  11. Disentangling Stability, Variability and Adaptability in Human Performance: Focus on the Interplay between Local Variance and Serial Correlation

    ERIC Educational Resources Information Center

    Torre, Kjerstin; Balasubramaniam, Ramesh

    2011-01-01

    We address the complex relationship between the stability, variability, and adaptability of psychological systems by decomposing the global variance of serial performance into two independent parts: the local variance (LV) and the serial correlation structure. For two time series with equal LV, the presence of persistent long-range correlations…

  12. The Relation of Hand and Arm Configuration Variances while Tracking Geometric Figures in Parkinson's Disease: Aspects for Rehabilitation

    ERIC Educational Resources Information Center

    Keresztenyi, Zoltan; Cesari, Paola; Fazekas, Gabor; Laczko, Jozsef

    2009-01-01

    Variances of drawing arm movements between patients with Parkinson's disease and healthy controls were compared. The aim was to determine whether differences in joint synergies or individual joint rotations affect the endpoint (hand position) variance. Joint and endpoint coordinates were measured while participants performed drawing tasks.…

  13. A Generalized DIF Effect Variance Estimator for Measuring Unsigned Differential Test Functioning in Mixed Format Tests

    ERIC Educational Resources Information Center

    Penfield, Randall D.; Algina, James

    2006-01-01

    One approach to measuring unsigned differential test functioning is to estimate the variance of the differential item functioning (DIF) effect across the items of the test. This article proposes two estimators of the DIF effect variance for tests containing dichotomous and polytomous items. The proposed estimators are direct extensions of the…

  14. Methods to Estimate the Between-Study Variance and Its Uncertainty in Meta-Analysis

    ERIC Educational Resources Information Center

    Veroniki, Areti Angeliki; Jackson, Dan; Viechtbauer, Wolfgang; Bender, Ralf; Bowden, Jack; Knapp, Guido; Kuss, Oliver; Higgins, Julian P. T.; Langan, Dean; Salanti, Georgia

    2016-01-01

    Meta-analyses are typically used to estimate the overall/mean of an outcome of interest. However, inference about between-study variability, which is typically modelled using a between-study variance parameter, is usually an additional aim. The DerSimonian and Laird method, currently widely used by default to estimate the between-study variance,…

  15. 40 CFR 142.304 - For which of the regulatory requirements is a small system variance available?

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 40 Protection of Environment 23 2011-07-01 2011-07-01 false For which of the regulatory requirements is a small system variance available? 142.304 Section 142.304 Protection of Environment... REGULATIONS IMPLEMENTATION Variances for Small System General Provisions § 142.304 For which of the regulatory...

  16. 40 CFR 142.303 - Which size public water systems can receive a small system variance?

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 40 Protection of Environment 23 2014-07-01 2014-07-01 false Which size public water systems can receive a small system variance? 142.303 Section 142.303 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS IMPLEMENTATION Variances for Small System General...

  17. Three Tests and Three Corrections: Comment on Koen and Yonelinas (2010)

    ERIC Educational Resources Information Center

    Jang, Yoonhee; Mickes, Laura; Wixted, John T.

    2012-01-01

    The slope of the z-transformed receiver-operating characteristic (zROC) in recognition memory experiments is usually less than 1, which has long been interpreted to mean that the variance of the target distribution is greater than the variance of the lure distribution. The greater variance of the target distribution could arise because the…

  18. An Analysis of Variance Approach for the Estimation of Response Time Distributions in Tests

    ERIC Educational Resources Information Center

    Attali, Yigal

    2010-01-01

    Generalizability theory and analysis of variance methods are employed, together with the concept of objective time pressure, to estimate response time distributions and the degree of time pressure in timed tests. By estimating response time variance components due to person, item, and their interaction, and fixed effects due to item types and…

  19. 77 FR 9637 - Process for Requesting a Variance From Vegetation Standards for Levees and Floodwalls; Additional...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-02-17

    ...-2502, Retaining and Flood Walls, 29 September 1989. h. Engineer Technical Letter (ETL) 1110-2-575... vegetation variance request. h. All final documentation for the vegetation variance request shall be uploaded..., especially for I-walls of concern as identified per Paragraph 3.h. For floodwalls, the landside and waterside...

  20. 78 FR 2986 - Northern Indiana Public Service Company; Notice of Application for Temporary Variance of License...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-01-15

    ... Public Service Company; Notice of Application for Temporary Variance of License Article 403 and...: Extension of temporary variance of license article 403. b. Project No: 12514-056. c. Date Filed: November 28... submit brief comments up to 6,000 characters, without prior registration, using the eComment system at...

  1. Relationships of Measurement Error and Prediction Error in Observed-Score Regression

    ERIC Educational Resources Information Center

    Moses, Tim

    2012-01-01

    The focus of this paper is assessing the impact of measurement errors on the prediction error of an observed-score regression. Measures are presented and described for decomposing the linear regression's prediction error variance into parts attributable to the true score variance and the error variances of the dependent variable and the predictor…

  2. Genetic influences on the difference in variability of height, weight and body mass index between Caucasian and East Asian adolescent twins.

    PubMed

    Hur, Y-M; Kaprio, J; Iacono, W G; Boomsma, D I; McGue, M; Silventoinen, K; Martin, N G; Luciano, M; Visscher, P M; Rose, R J; He, M; Ando, J; Ooki, S; Nonaka, K; Lin, C C H; Lajunen, H R; Cornes, B K; Bartels, M; van Beijsterveldt, C E M; Cherny, S S; Mitchell, K

    2008-10-01

    Twin studies are useful for investigating the causes of trait variation between as well as within a population. The goals of the present study were two-fold: First, we aimed to compare the total phenotypic, genetic and environmental variances of height, weight and BMI between Caucasians and East Asians using twins. Secondly, we intended to estimate the extent to which genetic and environmental factors contribute to differences in variability of height, weight and BMI between Caucasians and East Asians. Height and weight data from 3735 Caucasian and 1584 East Asian twin pairs (age: 13-15 years) from Australia, China, Finland, Japan, the Netherlands, South Korea, Taiwan and the United States were used for analyses. Maximum likelihood twin correlations and variance components model-fitting analyses were conducted to fulfill the goals of the present study. The absolute genetic variances for height, weight and BMI were consistently greater in Caucasians than in East Asians with corresponding differences in total variances for all three body measures. In all 80 to 100% of the differences in total variances of height, weight and BMI between the two population groups were associated with genetic differences. Height, weight and BMI were more variable in Caucasian than in East Asian adolescents. Genetic variances for these three body measures were also larger in Caucasians than in East Asians. Variance components model-fitting analyses indicated that genetic factors contributed to the difference in variability of height, weight and BMI between the two population groups. Association studies for these body measures should take account of our findings of differences in genetic variances between the two population groups.

  3. Genetic influences on the difference in variability of height, weight and body mass index between Caucasian and East Asian adolescent twins

    PubMed Central

    Hur, Y-M; Kaprio, J; Iacono, WG; Boomsma, DI; McGue, M; Silventoinen, K; Martin, NG; Luciano, M; Visscher, PM; Rose, RJ; He, M; Ando, J; Ooki, S; Nonaka, K; Lin, CCH; Lajunen, HR; Cornes, BK; Bartels, M; van Beijsterveldt, CEM; Cherny, SS; Mitchell, K

    2008-01-01

    Objective Twin studies are useful for investigating the causes of trait variation between as well as within a population. The goals of the present study were two-fold: First, we aimed to compare the total phenotypic, genetic and environmental variances of height, weight and BMI between Caucasians and East Asians using twins. Secondly, we intended to estimate the extent to which genetic and environmental factors contribute to differences in variability of height, weight and BMI between Caucasians and East Asians. Design Height and weight data from 3735 Caucasian and 1584 East Asian twin pairs (age: 13–15 years) from Australia, China, Finland, Japan, the Netherlands, South Korea, Taiwan and the United States were used for analyses. Maximum likelihood twin correlations and variance components model-fitting analyses were conducted to fulfill the goals of the present study. Results The absolute genetic variances for height, weight and BMI were consistently greater in Caucasians than in East Asians with corresponding differences in total variances for all three body measures. In all 80 to 100% of the differences in total variances of height, weight and BMI between the two population groups were associated with genetic differences. Conclusion Height, weight and BMI were more variable in Caucasian than in East Asian adolescents. Genetic variances for these three body measures were also larger in Caucasians than in East Asians. Variance components model-fitting analyses indicated that genetic factors contributed to the difference in variability of height, weight and BMI between the two population groups. Association studies for these body measures should take account of our findings of differences in genetic variances between the two population groups. PMID:18779828

  4. Methods for calculating confidence and credible intervals for the residual between-study variance in random effects meta-regression models

    PubMed Central

    2014-01-01

    Background Meta-regression is becoming increasingly used to model study level covariate effects. However this type of statistical analysis presents many difficulties and challenges. Here two methods for calculating confidence intervals for the magnitude of the residual between-study variance in random effects meta-regression models are developed. A further suggestion for calculating credible intervals using informative prior distributions for the residual between-study variance is presented. Methods Two recently proposed and, under the assumptions of the random effects model, exact methods for constructing confidence intervals for the between-study variance in random effects meta-analyses are extended to the meta-regression setting. The use of Generalised Cochran heterogeneity statistics is extended to the meta-regression setting and a Newton-Raphson procedure is developed to implement the Q profile method for meta-analysis and meta-regression. WinBUGS is used to implement informative priors for the residual between-study variance in the context of Bayesian meta-regressions. Results Results are obtained for two contrasting examples, where the first example involves a binary covariate and the second involves a continuous covariate. Intervals for the residual between-study variance are wide for both examples. Conclusions Statistical methods, and R computer software, are available to compute exact confidence intervals for the residual between-study variance under the random effects model for meta-regression. These frequentist methods are almost as easily implemented as their established counterparts for meta-analysis. Bayesian meta-regressions are also easily performed by analysts who are comfortable using WinBUGS. Estimates of the residual between-study variance in random effects meta-regressions should be routinely reported and accompanied by some measure of their uncertainty. Confidence and/or credible intervals are well-suited to this purpose. PMID:25196829

  5. Optimal design criteria - prediction vs. parameter estimation

    NASA Astrophysics Data System (ADS)

    Waldl, Helmut

    2014-05-01

    G-optimality is a popular design criterion for optimal prediction, it tries to minimize the kriging variance over the whole design region. A G-optimal design minimizes the maximum variance of all predicted values. If we use kriging methods for prediction it is self-evident to use the kriging variance as a measure of uncertainty for the estimates. Though the computation of the kriging variance and even more the computation of the empirical kriging variance is computationally very costly and finding the maximum kriging variance in high-dimensional regions can be time demanding such that we cannot really find the G-optimal design with nowadays available computer equipment in practice. We cannot always avoid this problem by using space-filling designs because small designs that minimize the empirical kriging variance are often non-space-filling. D-optimality is the design criterion related to parameter estimation. A D-optimal design maximizes the determinant of the information matrix of the estimates. D-optimality in terms of trend parameter estimation and D-optimality in terms of covariance parameter estimation yield basically different designs. The Pareto frontier of these two competing determinant criteria corresponds with designs that perform well under both criteria. Under certain conditions searching the G-optimal design on the above Pareto frontier yields almost as good results as searching the G-optimal design in the whole design region. In doing so the maximum of the empirical kriging variance has to be computed only a few times though. The method is demonstrated by means of a computer simulation experiment based on data provided by the Belgian institute Management Unit of the North Sea Mathematical Models (MUMM) that describe the evolution of inorganic and organic carbon and nutrients, phytoplankton, bacteria and zooplankton in the Southern Bight of the North Sea.

  6. Intelligent ensemble T-S fuzzy neural networks with RCDPSO_DM optimization for effective handling of complex clinical pathway variances.

    PubMed

    Du, Gang; Jiang, Zhibin; Diao, Xiaodi; Yao, Yang

    2013-07-01

    Takagi-Sugeno (T-S) fuzzy neural networks (FNNs) can be used to handle complex, fuzzy, uncertain clinical pathway (CP) variances. However, there are many drawbacks, such as slow training rate, propensity to become trapped in a local minimum and poor ability to perform a global search. In order to improve overall performance of variance handling by T-S FNNs, a new CP variance handling method is proposed in this study. It is based on random cooperative decomposing particle swarm optimization with double mutation mechanism (RCDPSO_DM) for T-S FNNs. Moreover, the proposed integrated learning algorithm, combining the RCDPSO_DM algorithm with a Kalman filtering algorithm, is applied to optimize antecedent and consequent parameters of constructed T-S FNNs. Then, a multi-swarm cooperative immigrating particle swarm algorithm ensemble method is used for intelligent ensemble T-S FNNs with RCDPSO_DM optimization to further improve stability and accuracy of CP variance handling. Finally, two case studies on liver and kidney poisoning variances in osteosarcoma preoperative chemotherapy are used to validate the proposed method. The result demonstrates that intelligent ensemble T-S FNNs based on the RCDPSO_DM achieves superior performances, in terms of stability, efficiency, precision and generalizability, over PSO ensemble of all T-S FNNs with RCDPSO_DM optimization, single T-S FNNs with RCDPSO_DM optimization, standard T-S FNNs, standard Mamdani FNNs and T-S FNNs based on other algorithms (cooperative particle swarm optimization and particle swarm optimization) for CP variance handling. Therefore, it makes CP variance handling more effective. Copyright © 2013 Elsevier Ltd. All rights reserved.

  7. Modeling additive and non-additive effects in a hybrid population using genome-wide genotyping: prediction accuracy implications

    PubMed Central

    Bouvet, J-M; Makouanzi, G; Cros, D; Vigneron, Ph

    2016-01-01

    Hybrids are broadly used in plant breeding and accurate estimation of variance components is crucial for optimizing genetic gain. Genome-wide information may be used to explore models designed to assess the extent of additive and non-additive variance and test their prediction accuracy for the genomic selection. Ten linear mixed models, involving pedigree- and marker-based relationship matrices among parents, were developed to estimate additive (A), dominance (D) and epistatic (AA, AD and DD) effects. Five complementary models, involving the gametic phase to estimate marker-based relationships among hybrid progenies, were developed to assess the same effects. The models were compared using tree height and 3303 single-nucleotide polymorphism markers from 1130 cloned individuals obtained via controlled crosses of 13 Eucalyptus urophylla females with 9 Eucalyptus grandis males. Akaike information criterion (AIC), variance ratios, asymptotic correlation matrices of estimates, goodness-of-fit, prediction accuracy and mean square error (MSE) were used for the comparisons. The variance components and variance ratios differed according to the model. Models with a parent marker-based relationship matrix performed better than those that were pedigree-based, that is, an absence of singularities, lower AIC, higher goodness-of-fit and accuracy and smaller MSE. However, AD and DD variances were estimated with high s.es. Using the same criteria, progeny gametic phase-based models performed better in fitting the observations and predicting genetic values. However, DD variance could not be separated from the dominance variance and null estimates were obtained for AA and AD effects. This study highlighted the advantages of progeny models using genome-wide information. PMID:26328760

  8. Does an uneven sample size distribution across settings matter in cross-classified multilevel modeling? Results of a simulation study.

    PubMed

    Milliren, Carly E; Evans, Clare R; Richmond, Tracy K; Dunn, Erin C

    2018-06-06

    Recent advances in multilevel modeling allow for modeling non-hierarchical levels (e.g., youth in non-nested schools and neighborhoods) using cross-classified multilevel models (CCMM). Current practice is to cluster samples from one context (e.g., schools) and utilize the observations however they are distributed from the second context (e.g., neighborhoods). However, it is unknown whether an uneven distribution of sample size across these contexts leads to incorrect estimates of random effects in CCMMs. Using the school and neighborhood data structure in Add Health, we examined the effect of neighborhood sample size imbalance on the estimation of variance parameters in models predicting BMI. We differentially assigned students from a given school to neighborhoods within that school's catchment area using three scenarios of (im)balance. 1000 random datasets were simulated for each of five combinations of school- and neighborhood-level variance and imbalance scenarios, for a total of 15,000 simulated data sets. For each simulation, we calculated 95% CIs for the variance parameters to determine whether the true simulated variance fell within the interval. Across all simulations, the "true" school and neighborhood variance parameters were estimated 93-96% of the time. Only 5% of models failed to capture neighborhood variance; 6% failed to capture school variance. These results suggest that there is no systematic bias in the ability of CCMM to capture the true variance parameters regardless of the distribution of students across neighborhoods. Ongoing efforts to use CCMM are warranted and can proceed without concern for the sample imbalance across contexts. Copyright © 2018 Elsevier Ltd. All rights reserved.

  9. Decomposing genomic variance using information from GWA, GWE and eQTL analysis.

    PubMed

    Ehsani, A; Janss, L; Pomp, D; Sørensen, P

    2016-04-01

    A commonly used procedure in genome-wide association (GWA), genome-wide expression (GWE) and expression quantitative trait locus (eQTL) analyses is based on a bottom-up experimental approach that attempts to individually associate molecular variants with complex traits. Top-down modeling of the entire set of genomic data and partitioning of the overall variance into subcomponents may provide further insight into the genetic basis of complex traits. To test this approach, we performed a whole-genome variance components analysis and partitioned the genomic variance using information from GWA, GWE and eQTL analyses of growth-related traits in a mouse F2 population. We characterized the mouse trait genetic architecture by ordering single nucleotide polymorphisms (SNPs) based on their P-values and studying the areas under the curve (AUCs). The observed traits were found to have a genomic variance profile that differed significantly from that expected of a trait under an infinitesimal model. This situation was particularly true for both body weight and body fat, for which the AUCs were much higher compared with that of glucose. In addition, SNPs with a high degree of trait-specific regulatory potential (SNPs associated with subset of transcripts that significantly associated with a specific trait) explained a larger proportion of the genomic variance than did SNPs with high overall regulatory potential (SNPs associated with transcripts using traditional eQTL analysis). We introduced AUC measures of genomic variance profiles that can be used to quantify relative importance of SNPs as well as degree of deviation of a trait's inheritance from an infinitesimal model. The shape of the curve aids global understanding of traits: The steeper the left-hand side of the curve, the fewer the number of SNPs controlling most of the phenotypic variance. © 2015 Stichting International Foundation for Animal Genetics.

  10. Global Distributions of Temperature Variances At Different Stratospheric Altitudes From Gps/met Data

    NASA Astrophysics Data System (ADS)

    Gavrilov, N. M.; Karpova, N. V.; Jacobi, Ch.

    The GPS/MET measurements at altitudes 5 - 35 km are used to obtain global distribu- tions of small-scale temperature variances at different stratospheric altitudes. Individ- ual temperature profiles are smoothed using second order polynomial approximations in 5 - 7 km thick layers centered at 10, 20 and 30 km. Temperature inclinations from the averaged values and their variances obtained for each profile are averaged for each month of year during the GPS/MET experiment. Global distributions of temperature variances have inhomogeneous structure. Locations and latitude distributions of the maxima and minima of the variances depend on altitudes and season. One of the rea- sons for the small-scale temperature perturbations in the stratosphere could be internal gravity waves (IGWs). Some assumptions are made about peculiarities of IGW gener- ation and propagation in the tropo-stratosphere based on the results of GPS/MET data analysis.

  11. Taylor's law and body size in exploited marine ecosystems.

    PubMed

    Cohen, Joel E; Plank, Michael J; Law, Richard

    2012-12-01

    Taylor's law (TL), which states that variance in population density is related to mean density via a power law, and density-mass allometry, which states that mean density is related to body mass via a power law, are two of the most widely observed patterns in ecology. Combining these two laws predicts that the variance in density is related to body mass via a power law (variance-mass allometry). Marine size spectra are known to exhibit density-mass allometry, but variance-mass allometry has not been investigated. We show that variance and body mass in unexploited size spectrum models are related by a power law, and that this leads to TL with an exponent slightly <2. These simulated relationships are disrupted less by balanced harvesting, in which fishing effort is spread across a wide range of body sizes, than by size-at-entry fishing, in which only fish above a certain size may legally be caught.

  12. Variances and uncertainties of the sample laboratory-to-laboratory variance (S(L)2) and standard deviation (S(L)) associated with an interlaboratory study.

    PubMed

    McClure, Foster D; Lee, Jung K

    2012-01-01

    The validation process for an analytical method usually employs an interlaboratory study conducted as a balanced completely randomized model involving a specified number of randomly chosen laboratories, each analyzing a specified number of randomly allocated replicates. For such studies, formulas to obtain approximate unbiased estimates of the variance and uncertainty of the sample laboratory-to-laboratory (lab-to-lab) STD (S(L)) have been developed primarily to account for the uncertainty of S(L) when there is a need to develop an uncertainty budget that includes the uncertainty of S(L). For the sake of completeness on this topic, formulas to estimate the variance and uncertainty of the sample lab-to-lab variance (S(L)2) were also developed. In some cases, it was necessary to derive the formulas based on an approximate distribution for S(L)2.

  13. Diallel analysis for sex-linked and maternal effects.

    PubMed

    Zhu, J; Weir, B S

    1996-01-01

    Genetic models including sex-linked and maternal effects as well as autosomal gene effects are described. Monte Carlo simulations were conducted to compare efficiencies of estimation by minimum norm quadratic unbiased estimation (MINQUE) and restricted maximum likelihood (REML) methods. MINQUE(1), which has 1 for all prior values, has a similar efficiency to MINQUE(θ), which requires prior estimates of parameter values. MINQUE(1) has the advantage over REML of unbiased estimation and convenient computation. An adjusted unbiased prediction (AUP) method is developed for predicting random genetic effects. AUP is desirable for its easy computation and unbiasedness of both mean and variance of predictors. The jackknife procedure is appropriate for estimating the sampling variances of estimated variances (or covariances) and of predicted genetic effects. A t-test based on jackknife variances is applicable for detecting significance of variation. Worked examples from mice and silkworm data are given in order to demonstrate variance and covariance estimation and genetic effect prediction.

  14. Taylor's law and body size in exploited marine ecosystems

    PubMed Central

    Cohen, Joel E; Plank, Michael J; Law, Richard

    2012-01-01

    Taylor's law (TL), which states that variance in population density is related to mean density via a power law, and density-mass allometry, which states that mean density is related to body mass via a power law, are two of the most widely observed patterns in ecology. Combining these two laws predicts that the variance in density is related to body mass via a power law (variance-mass allometry). Marine size spectra are known to exhibit density-mass allometry, but variance-mass allometry has not been investigated. We show that variance and body mass in unexploited size spectrum models are related by a power law, and that this leads to TL with an exponent slightly <2. These simulated relationships are disrupted less by balanced harvesting, in which fishing effort is spread across a wide range of body sizes, than by size-at-entry fishing, in which only fish above a certain size may legally be caught. PMID:23301181

  15. Host nutrition alters the variance in parasite transmission potential

    PubMed Central

    Vale, Pedro F.; Choisy, Marc; Little, Tom J.

    2013-01-01

    The environmental conditions experienced by hosts are known to affect their mean parasite transmission potential. How different conditions may affect the variance of transmission potential has received less attention, but is an important question for disease management, especially if specific ecological contexts are more likely to foster a few extremely infectious hosts. Using the obligate-killing bacterium Pasteuria ramosa and its crustacean host Daphnia magna, we analysed how host nutrition affected the variance of individual parasite loads, and, therefore, transmission potential. Under low food, individual parasite loads showed similar mean and variance, following a Poisson distribution. By contrast, among well-nourished hosts, parasite loads were right-skewed and overdispersed, following a negative binomial distribution. Abundant food may, therefore, yield individuals causing potentially more transmission than the population average. Measuring both the mean and variance of individual parasite loads in controlled experimental infections may offer a useful way of revealing risk factors for potential highly infectious hosts. PMID:23407498

  16. Host nutrition alters the variance in parasite transmission potential.

    PubMed

    Vale, Pedro F; Choisy, Marc; Little, Tom J

    2013-04-23

    The environmental conditions experienced by hosts are known to affect their mean parasite transmission potential. How different conditions may affect the variance of transmission potential has received less attention, but is an important question for disease management, especially if specific ecological contexts are more likely to foster a few extremely infectious hosts. Using the obligate-killing bacterium Pasteuria ramosa and its crustacean host Daphnia magna, we analysed how host nutrition affected the variance of individual parasite loads, and, therefore, transmission potential. Under low food, individual parasite loads showed similar mean and variance, following a Poisson distribution. By contrast, among well-nourished hosts, parasite loads were right-skewed and overdispersed, following a negative binomial distribution. Abundant food may, therefore, yield individuals causing potentially more transmission than the population average. Measuring both the mean and variance of individual parasite loads in controlled experimental infections may offer a useful way of revealing risk factors for potential highly infectious hosts.

  17. Determination of the optimal level for combining area and yield estimates

    NASA Technical Reports Server (NTRS)

    Bauer, M. E. (Principal Investigator); Hixson, M. M.; Jobusch, C. D.

    1981-01-01

    Several levels of obtaining both area and yield estimates of corn and soybeans in Iowa were considered: county, refined strata, refined/split strata, crop reporting district, and state. Using the CCEA model form and smoothed weather data, regression coefficients at each level were derived to compute yield and its variance. Variances were also computed with stratum level. The variance of the yield estimates was largest at the state and smallest at the county level for both crops. The refined strata had somewhat larger variances than those associated with the refined/split strata and CRD. For production estimates, the difference in standard deviations among levels was not large for corn, but for soybeans the standard deviation at the state level was more than 50% greater than for the other levels. The refined strata had the smallest standard deviations. The county level was not considered in evaluation of production estimates due to lack of county area variances.

  18. Methods to Estimate the Variance of Some Indices of the Signal Detection Theory: A Simulation Study

    ERIC Educational Resources Information Center

    Suero, Manuel; Privado, Jesús; Botella, Juan

    2017-01-01

    A simulation study is presented to evaluate and compare three methods to estimate the variance of the estimates of the parameters d and "C" of the signal detection theory (SDT). Several methods have been proposed to calculate the variance of their estimators, "d'" and "c." Those methods have been mostly assessed by…

  19. 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…

  20. Correcting for Systematic Bias in Sample Estimates of Population Variances: Why Do We Divide by n-1?

    ERIC Educational Resources Information Center

    Mittag, Kathleen Cage

    An important topic presented in introductory statistics courses is the estimation of population parameters using samples. Students learn that when estimating population variances using sample data, we always get an underestimate of the population variance if we divide by n rather than n-1. One implication of this correction is that the degree of…

  1. Modeling Multiplicative Error Variance: An Example Predicting Tree Diameter from Stump Dimensions in Baldcypress

    Treesearch

    Bernard R. Parresol

    1993-01-01

    In the context of forest modeling, it is often reasonable to assume a multiplicative heteroscedastic error structure to the data. Under such circumstances ordinary least squares no longer provides minimum variance estimates of the model parameters. Through study of the error structure, a suitable error variance model can be specified and its parameters estimated. This...

  2. Effect of natural inbreeding on variance structure in tests of wind pollination Douglas-fir progenies.

    Treesearch

    Frank C. Sorensen; T.L. White

    1988-01-01

    Studies of the mating habits of Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) have shown that wind-pollination families contain a small proportion of very slow-growing natural inbreds.The effect of these very small trees on means, variances, and variance ratios was evaluated for height and diameter in a 16-year-old plantation by...

  3. 75 FR 38130 - Keystone Steel and Wire Company; Notice of Application for a Permanent Variance, Grant of an...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-07-01

    ...] Keystone Steel and Wire Company; Notice of Application for a Permanent Variance, Grant of an Interim Order...: Keystone Steel and Wire Company (KSW) is applying for a permanent variance from the provisions of the OSHA... OSHA's Web page at http://www.osha.gov . I. Notice of Application Keystone Steel and Wire Company...

  4. 76 FR 18921 - Land Disposal Restrictions: Nevada and California; Site Specific Treatment Variances for...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-04-06

    ... final actions to both issue a site- specific treatment variance to U.S. Ecology Nevada (USEN) in Beatty... me? This action applies only to U.S. Ecology Nevada located in Beatty, Nevada and to Chemical Waste... This Variance A. U.S. Ecology Nevada Petition B. What Type and How Much Waste Will be Subject to This...

  5. Understanding the Degrees of Freedom of Sample Variance by Using Microsoft Excel

    ERIC Educational Resources Information Center

    Ding, Jian-Hua; Jin, Xian-Wen; Shuai, Ling-Ying

    2017-01-01

    In this article, the degrees of freedom of the sample variance are simulated by using the Visual Basic for Applications of Microsoft Excel 2010. The simulation file dynamically displays why the sample variance should be calculated by dividing the sum of squared deviations by n-1 rather than n, which is helpful for students to grasp the meaning of…

  6. A Study of Child Variance, Volume 4: The Future; Conceptual Project in Emotional Disturbance.

    ERIC Educational Resources Information Center

    Rhodes, William C.

    Presented in the fourth volume in a series are a discussion of critical issues related to child variance and predictions for how society will perceive and respond to child variance in the future. Reviewed in an introductory chapter are the contents of the first three volumes which deal with conceptual models, interventions, and service delivery…

  7. Using Generalizability Theory to Examine Sources of Variance in Observed Behaviors within High School Classrooms

    ERIC Educational Resources Information Center

    Abry, Tashia; Cash, Anne H.; Bradshaw, Catherine P.

    2014-01-01

    Generalizability theory (GT) offers a useful framework for estimating the reliability of a measure while accounting for multiple sources of error variance. The purpose of this study was to use GT to examine multiple sources of variance in and the reliability of school-level teacher and high school student behaviors as observed using the tool,…

  8. Consequences of Assumption Violations Revisited: A Quantitative Review of Alternatives to the One-Way Analysis of Variance "F" Test.

    ERIC Educational Resources Information Center

    Lix, Lisa M.; And Others

    1996-01-01

    Meta-analytic techniques were used to summarize the statistical robustness literature on Type I error properties of alternatives to the one-way analysis of variance "F" test. The James (1951) and Welch (1951) tests performed best under violations of the variance homogeneity assumption, although their use is not always appropriate. (SLD)

  9. Mesoscale Gravity Wave Variances from AMSU-A Radiances

    NASA Technical Reports Server (NTRS)

    Wu, Dong L.

    2004-01-01

    A variance analysis technique is developed here to extract gravity wave (GW) induced temperature fluctuations from NOAA AMSU-A (Advanced Microwave Sounding Unit-A) radiance measurements. By carefully removing the instrument/measurement noise, the algorithm can produce reliable GW variances with the minimum detectable value as small as 0.1 K2. Preliminary analyses with AMSU-A data show GW variance maps in the stratosphere have very similar distributions to those found with the UARS MLS (Upper Atmosphere Research Satellite Microwave Limb Sounder). However, the AMSU-A offers better horizontal and temporal resolution for observing regional GW variability, such as activity over sub-Antarctic islands.

  10. Variance approach for multi-objective linear programming with fuzzy random of objective function coefficients

    NASA Astrophysics Data System (ADS)

    Indarsih, Indrati, Ch. Rini

    2016-02-01

    In this paper, we define variance of the fuzzy random variables through alpha level. We have a theorem that can be used to know that the variance of fuzzy random variables is a fuzzy number. We have a multi-objective linear programming (MOLP) with fuzzy random of objective function coefficients. We will solve the problem by variance approach. The approach transform the MOLP with fuzzy random of objective function coefficients into MOLP with fuzzy of objective function coefficients. By weighted methods, we have linear programming with fuzzy coefficients and we solve by simplex method for fuzzy linear programming.

  11. Fuel cell stack monitoring and system control

    DOEpatents

    Keskula, Donald H.; Doan, Tien M.; Clingerman, Bruce J.

    2004-02-17

    A control method for monitoring a fuel cell stack in a fuel cell system in which the actual voltage and actual current from the fuel cell stack are monitored. A preestablished relationship between voltage and current over the operating range of the fuel cell is established. A variance value between the actual measured voltage and the expected voltage magnitude for a given actual measured current is calculated and compared with a predetermined allowable variance. An output is generated if the calculated variance value exceeds the predetermined variance. The predetermined voltage-current for the fuel cell is symbolized as a polarization curve at given operating conditions of the fuel cell.

  12. Analysis of conditional genetic effects and variance components in developmental genetics.

    PubMed

    Zhu, J

    1995-12-01

    A genetic model with additive-dominance effects and genotype x environment interactions is presented for quantitative traits with time-dependent measures. The genetic model for phenotypic means at time t conditional on phenotypic means measured at previous time (t-1) is defined. Statistical methods are proposed for analyzing conditional genetic effects and conditional genetic variance components. Conditional variances can be estimated by minimum norm quadratic unbiased estimation (MINQUE) method. An adjusted unbiased prediction (AUP) procedure is suggested for predicting conditional genetic effects. A worked example from cotton fruiting data is given for comparison of unconditional and conditional genetic variances and additive effects.

  13. Analysis of Conditional Genetic Effects and Variance Components in Developmental Genetics

    PubMed Central

    Zhu, J.

    1995-01-01

    A genetic model with additive-dominance effects and genotype X environment interactions is presented for quantitative traits with time-dependent measures. The genetic model for phenotypic means at time t conditional on phenotypic means measured at previous time (t - 1) is defined. Statistical methods are proposed for analyzing conditional genetic effects and conditional genetic variance components. Conditional variances can be estimated by minimum norm quadratic unbiased estimation (MINQUE) method. An adjusted unbiased prediction (AUP) procedure is suggested for predicting conditional genetic effects. A worked example from cotton fruiting data is given for comparison of unconditional and conditional genetic variances and additive effects. PMID:8601500

  14. tscvh R Package: Computational of the two samples test on microarray-sequencing data

    NASA Astrophysics Data System (ADS)

    Fajriyah, Rohmatul; Rosadi, Dedi

    2017-12-01

    We present a new R package, a tscvh (two samples cross-variance homogeneity), as we called it. This package is a software of the cross-variance statistical test which has been proposed and introduced by Fajriyah ([3] and [4]), based on the cross-variance concept. The test can be used as an alternative test for the significance difference between two means when sample size is small, the situation which is usually appeared in the bioinformatics research. Based on its statistical distribution, the p-value can be also provided. The package is built under a homogeneity of variance between samples.

  15. How does variance in fertility change over the demographic transition?

    PubMed Central

    Hruschka, Daniel J.; Burger, Oskar

    2016-01-01

    Most work on the human fertility transition has focused on declines in mean fertility. However, understanding changes in the variance of reproductive outcomes can be equally important for evolutionary questions about the heritability of fertility, individual determinants of fertility and changing patterns of reproductive skew. Here, we document how variance in completed fertility among women (45–49 years) differs across 200 surveys in 72 low- to middle-income countries where fertility transitions are currently in progress at various stages. Nearly all (91%) of samples exhibit variance consistent with a Poisson process of fertility, which places systematic, and often severe, theoretical upper bounds on the proportion of variance that can be attributed to individual differences. In contrast to the pattern of total variance, these upper bounds increase from high- to mid-fertility samples, then decline again as samples move from mid to low fertility. Notably, the lowest fertility samples often deviate from a Poisson process. This suggests that as populations move to low fertility their reproduction shifts from a rate-based process to a focus on an ideal number of children. We discuss the implications of these findings for predicting completed fertility from individual-level variables. PMID:27022082

  16. [Application of single-band brightness variance ratio to the interference dissociation of cloud for satellite data].

    PubMed

    Qu, Wei-ping; Liu, Wen-qing; Liu, Jian-guo; Lu, Yi-huai; Zhu, Jun; Qin, Min; Liu, Cheng

    2006-11-01

    In satellite remote-sensing detection, cloud as an interference plays a negative role in data retrieval. How to discern the cloud fields with high fidelity thus comes as a need to the following research. A new method rooting in atmospheric radiation characteristics of cloud layer, in the present paper, presents a sort of solution where single-band brightness variance ratio is used to detect the relative intensity of cloud clutter so as to delineate cloud field rapidly and exactly, and the formulae of brightness variance ratio of satellite image, image reflectance variance ratio, and brightness temperature variance ratio of thermal infrared image are also given to enable cloud elimination to produce data free from cloud interference. According to the variance of the penetrating capability for different spectra bands, an objective evaluation is done on cloud penetration of them with the factors that influence penetration effect. Finally, a multi-band data fusion task is completed using the image data of infrared penetration from cirrus nothus. Image data reconstruction is of good quality and exactitude to show the real data of visible band covered by cloud fields. Statistics indicates the consistency of waveband relativity with image data after the data fusion.

  17. Comparing transformation methods for DNA microarray data

    PubMed Central

    Thygesen, Helene H; Zwinderman, Aeilko H

    2004-01-01

    Background When DNA microarray data are used for gene clustering, genotype/phenotype correlation studies, or tissue classification the signal intensities are usually transformed and normalized in several steps in order to improve comparability and signal/noise ratio. These steps may include subtraction of an estimated background signal, subtracting the reference signal, smoothing (to account for nonlinear measurement effects), and more. Different authors use different approaches, and it is generally not clear to users which method they should prefer. Results We used the ratio between biological variance and measurement variance (which is an F-like statistic) as a quality measure for transformation methods, and we demonstrate a method for maximizing that variance ratio on real data. We explore a number of transformations issues, including Box-Cox transformation, baseline shift, partial subtraction of the log-reference signal and smoothing. It appears that the optimal choice of parameters for the transformation methods depends on the data. Further, the behavior of the variance ratio, under the null hypothesis of zero biological variance, appears to depend on the choice of parameters. Conclusions The use of replicates in microarray experiments is important. Adjustment for the null-hypothesis behavior of the variance ratio is critical to the selection of transformation method. PMID:15202953

  18. Comparing transformation methods for DNA microarray data.

    PubMed

    Thygesen, Helene H; Zwinderman, Aeilko H

    2004-06-17

    When DNA microarray data are used for gene clustering, genotype/phenotype correlation studies, or tissue classification the signal intensities are usually transformed and normalized in several steps in order to improve comparability and signal/noise ratio. These steps may include subtraction of an estimated background signal, subtracting the reference signal, smoothing (to account for nonlinear measurement effects), and more. Different authors use different approaches, and it is generally not clear to users which method they should prefer. We used the ratio between biological variance and measurement variance (which is an F-like statistic) as a quality measure for transformation methods, and we demonstrate a method for maximizing that variance ratio on real data. We explore a number of transformations issues, including Box-Cox transformation, baseline shift, partial subtraction of the log-reference signal and smoothing. It appears that the optimal choice of parameters for the transformation methods depends on the data. Further, the behavior of the variance ratio, under the null hypothesis of zero biological variance, appears to depend on the choice of parameters. The use of replicates in microarray experiments is important. Adjustment for the null-hypothesis behavior of the variance ratio is critical to the selection of transformation method.

  19. Removing an intersubject variance component in a general linear model improves multiway factoring of event-related spectral perturbations in group EEG studies.

    PubMed

    Spence, Jeffrey S; Brier, Matthew R; Hart, John; Ferree, Thomas C

    2013-03-01

    Linear statistical models are used very effectively to assess task-related differences in EEG power spectral analyses. Mixed models, in particular, accommodate more than one variance component in a multisubject study, where many trials of each condition of interest are measured on each subject. Generally, intra- and intersubject variances are both important to determine correct standard errors for inference on functions of model parameters, but it is often assumed that intersubject variance is the most important consideration in a group study. In this article, we show that, under common assumptions, estimates of some functions of model parameters, including estimates of task-related differences, are properly tested relative to the intrasubject variance component only. A substantial gain in statistical power can arise from the proper separation of variance components when there is more than one source of variability. We first develop this result analytically, then show how it benefits a multiway factoring of spectral, spatial, and temporal components from EEG data acquired in a group of healthy subjects performing a well-studied response inhibition task. Copyright © 2011 Wiley Periodicals, Inc.

  20. Practice reduces task relevant variance modulation and forms nominal trajectory

    NASA Astrophysics Data System (ADS)

    Osu, Rieko; Morishige, Ken-Ichi; Nakanishi, Jun; Miyamoto, Hiroyuki; Kawato, Mitsuo

    2015-12-01

    Humans are capable of achieving complex tasks with redundant degrees of freedom. Much attention has been paid to task relevant variance modulation as an indication of online feedback control strategies to cope with motor variability. Meanwhile, it has been discussed that the brain learns internal models of environments to realize feedforward control with nominal trajectories. Here we examined trajectory variance in both spatial and temporal domains to elucidate the relative contribution of these control schemas. We asked subjects to learn reaching movements with multiple via-points, and found that hand trajectories converged to stereotyped trajectories with the reduction of task relevant variance modulation as learning proceeded. Furthermore, variance reduction was not always associated with task constraints but was highly correlated with the velocity profile. A model assuming noise both on the nominal trajectory and motor command was able to reproduce the observed variance modulation, supporting an expression of nominal trajectories in the brain. The learning-related decrease in task-relevant modulation revealed a reduction in the influence of optimal feedback around the task constraints. After practice, the major part of computation seems to be taken over by the feedforward controller around the nominal trajectory with feedback added only when it becomes necessary.

  1. Prospects for discovering pulsars in future continuum surveys using variance imaging

    NASA Astrophysics Data System (ADS)

    Dai, S.; Johnston, S.; Hobbs, G.

    2017-12-01

    In our previous paper, we developed a formalism for computing variance images from standard, interferometric radio images containing time and frequency information. Variance imaging with future radio continuum surveys allows us to identify radio pulsars and serves as a complement to conventional pulsar searches that are most sensitive to strictly periodic signals. Here, we carry out simulations to predict the number of pulsars that we can uncover with variance imaging in future continuum surveys. We show that the Australian SKA Pathfinder (ASKAP) Evolutionary Map of the Universe (EMU) survey can find ∼30 normal pulsars and ∼40 millisecond pulsars (MSPs) over and above the number known today, and similarly an all-sky continuum survey with SKA-MID can discover ∼140 normal pulsars and ∼110 MSPs with this technique. Variance imaging with EMU and SKA-MID will detect pulsars with large duty cycles and is therefore a potential tool for finding MSPs and pulsars in relativistic binary systems. Compared with current pulsar surveys at high Galactic latitudes in the Southern hemisphere, variance imaging with EMU and SKA-MID will be more sensitive, and will enable detection of pulsars with dispersion measures between ∼10 and 100 cm-3 pc.

  2. Jackknife variance of the partial area under the empirical receiver operating characteristic curve.

    PubMed

    Bandos, Andriy I; Guo, Ben; Gur, David

    2017-04-01

    Receiver operating characteristic analysis provides an important methodology for assessing traditional (e.g., imaging technologies and clinical practices) and new (e.g., genomic studies, biomarker development) diagnostic problems. The area under the clinically/practically relevant part of the receiver operating characteristic curve (partial area or partial area under the receiver operating characteristic curve) is an important performance index summarizing diagnostic accuracy at multiple operating points (decision thresholds) that are relevant to actual clinical practice. A robust estimate of the partial area under the receiver operating characteristic curve is provided by the area under the corresponding part of the empirical receiver operating characteristic curve. We derive a closed-form expression for the jackknife variance of the partial area under the empirical receiver operating characteristic curve. Using the derived analytical expression, we investigate the differences between the jackknife variance and a conventional variance estimator. The relative properties in finite samples are demonstrated in a simulation study. The developed formula enables an easy way to estimate the variance of the empirical partial area under the receiver operating characteristic curve, thereby substantially reducing the computation burden, and provides important insight into the structure of the variability. We demonstrate that when compared with the conventional approach, the jackknife variance has substantially smaller bias, and leads to a more appropriate type I error rate of the Wald-type test. The use of the jackknife variance is illustrated in the analysis of a data set from a diagnostic imaging study.

  3. Errors in the estimation of the variance: implications for multiple-probability fluctuation analysis.

    PubMed

    Saviane, Chiara; Silver, R Angus

    2006-06-15

    Synapses play a crucial role in information processing in the brain. Amplitude fluctuations of synaptic responses can be used to extract information about the mechanisms underlying synaptic transmission and its modulation. In particular, multiple-probability fluctuation analysis can be used to estimate the number of functional release sites, the mean probability of release and the amplitude of the mean quantal response from fits of the relationship between the variance and mean amplitude of postsynaptic responses, recorded at different probabilities. To determine these quantal parameters, calculate their uncertainties and the goodness-of-fit of the model, it is important to weight the contribution of each data point in the fitting procedure. We therefore investigated the errors associated with measuring the variance by determining the best estimators of the variance of the variance and have used simulations of synaptic transmission to test their accuracy and reliability under different experimental conditions. For central synapses, which generally have a low number of release sites, the amplitude distribution of synaptic responses is not normal, thus the use of a theoretical variance of the variance based on the normal assumption is not a good approximation. However, appropriate estimators can be derived for the population and for limited sample sizes using a more general expression that involves higher moments and introducing unbiased estimators based on the h-statistics. Our results are likely to be relevant for various applications of fluctuation analysis when few channels or release sites are present.

  4. The evolution and consequences of sex-specific reproductive variance.

    PubMed

    Mullon, Charles; Reuter, Max; Lehmann, Laurent

    2014-01-01

    Natural selection favors alleles that increase the number of offspring produced by their carriers. But in a world that is inherently uncertain within generations, selection also favors alleles that reduce the variance in the number of offspring produced. If previous studies have established this principle, they have largely ignored fundamental aspects of sexual reproduction and therefore how selection on sex-specific reproductive variance operates. To study the evolution and consequences of sex-specific reproductive variance, we present a population-genetic model of phenotypic evolution in a dioecious population that incorporates previously neglected components of reproductive variance. First, we derive the probability of fixation for mutations that affect male and/or female reproductive phenotypes under sex-specific selection. We find that even in the simplest scenarios, the direction of selection is altered when reproductive variance is taken into account. In particular, previously unaccounted for covariances between the reproductive outputs of different individuals are expected to play a significant role in determining the direction of selection. Then, the probability of fixation is used to develop a stochastic model of joint male and female phenotypic evolution. We find that sex-specific reproductive variance can be responsible for changes in the course of long-term evolution. Finally, the model is applied to an example of parental-care evolution. Overall, our model allows for the evolutionary analysis of social traits in finite and dioecious populations, where interactions can occur within and between sexes under a realistic scenario of reproduction.

  5. The Evolution and Consequences of Sex-Specific Reproductive Variance

    PubMed Central

    Mullon, Charles; Reuter, Max; Lehmann, Laurent

    2014-01-01

    Natural selection favors alleles that increase the number of offspring produced by their carriers. But in a world that is inherently uncertain within generations, selection also favors alleles that reduce the variance in the number of offspring produced. If previous studies have established this principle, they have largely ignored fundamental aspects of sexual reproduction and therefore how selection on sex-specific reproductive variance operates. To study the evolution and consequences of sex-specific reproductive variance, we present a population-genetic model of phenotypic evolution in a dioecious population that incorporates previously neglected components of reproductive variance. First, we derive the probability of fixation for mutations that affect male and/or female reproductive phenotypes under sex-specific selection. We find that even in the simplest scenarios, the direction of selection is altered when reproductive variance is taken into account. In particular, previously unaccounted for covariances between the reproductive outputs of different individuals are expected to play a significant role in determining the direction of selection. Then, the probability of fixation is used to develop a stochastic model of joint male and female phenotypic evolution. We find that sex-specific reproductive variance can be responsible for changes in the course of long-term evolution. Finally, the model is applied to an example of parental-care evolution. Overall, our model allows for the evolutionary analysis of social traits in finite and dioecious populations, where interactions can occur within and between sexes under a realistic scenario of reproduction. PMID:24172130

  6. Mixed emotions: Sensitivity to facial variance in a crowd of faces.

    PubMed

    Haberman, Jason; Lee, Pegan; Whitney, David

    2015-01-01

    The visual system automatically represents summary information from crowds of faces, such as the average expression. This is a useful heuristic insofar as it provides critical information about the state of the world, not simply information about the state of one individual. However, the average alone is not sufficient for making decisions about how to respond to a crowd. The variance or heterogeneity of the crowd--the mixture of emotions--conveys information about the reliability of the average, essential for determining whether the average can be trusted. Despite its importance, the representation of variance within a crowd of faces has yet to be examined. This is addressed here in three experiments. In the first experiment, observers viewed a sample set of faces that varied in emotion, and then adjusted a subsequent set to match the variance of the sample set. To isolate variance as the summary statistic of interest, the average emotion of both sets was random. Results suggested that observers had information regarding crowd variance. The second experiment verified that this was indeed a uniquely high-level phenomenon, as observers were unable to derive the variance of an inverted set of faces as precisely as an upright set of faces. The third experiment replicated and extended the first two experiments using method-of-constant-stimuli. Together, these results show that the visual system is sensitive to emergent information about the emotional heterogeneity, or ambivalence, in crowds of faces.

  7. Variance components estimation for continuous and discrete data, with emphasis on cross-classified sampling designs

    USGS Publications Warehouse

    Gray, Brian R.; Gitzen, Robert A.; Millspaugh, Joshua J.; Cooper, Andrew B.; Licht, Daniel S.

    2012-01-01

    Variance components may play multiple roles (cf. Cox and Solomon 2003). First, magnitudes and relative magnitudes of the variances of random factors may have important scientific and management value in their own right. For example, variation in levels of invasive vegetation among and within lakes may suggest causal agents that operate at both spatial scales – a finding that may be important for scientific and management reasons. Second, variance components may also be of interest when they affect precision of means and covariate coefficients. For example, variation in the effect of water depth on the probability of aquatic plant presence in a study of multiple lakes may vary by lake. This variation will affect the precision of the average depth-presence association. Third, variance component estimates may be used when designing studies, including monitoring programs. For example, to estimate the numbers of years and of samples per year required to meet long-term monitoring goals, investigators need estimates of within and among-year variances. Other chapters in this volume (Chapters 7, 8, and 10) as well as extensive external literature outline a framework for applying estimates of variance components to the design of monitoring efforts. For example, a series of papers with an ecological monitoring theme examined the relative importance of multiple sources of variation, including variation in means among sites, years, and site-years, for the purposes of temporal trend detection and estimation (Larsen et al. 2004, and references therein).

  8. Multi-population Genomic Relationships for Estimating Current Genetic Variances Within and Genetic Correlations Between Populations.

    PubMed

    Wientjes, Yvonne C J; Bijma, Piter; Vandenplas, Jérémie; Calus, Mario P L

    2017-10-01

    Different methods are available to calculate multi-population genomic relationship matrices. Since those matrices differ in base population, it is anticipated that the method used to calculate genomic relationships affects the estimate of genetic variances, covariances, and correlations. The aim of this article is to define the multi-population genomic relationship matrix to estimate current genetic variances within and genetic correlations between populations. The genomic relationship matrix containing two populations consists of four blocks, one block for population 1, one block for population 2, and two blocks for relationships between the populations. It is known, based on literature, that by using current allele frequencies to calculate genomic relationships within a population, current genetic variances are estimated. In this article, we theoretically derived the properties of the genomic relationship matrix to estimate genetic correlations between populations and validated it using simulations. When the scaling factor of across-population genomic relationships is equal to the product of the square roots of the scaling factors for within-population genomic relationships, the genetic correlation is estimated unbiasedly even though estimated genetic variances do not necessarily refer to the current population. When this property is not met, the correlation based on estimated variances should be multiplied by a correction factor based on the scaling factors. In this study, we present a genomic relationship matrix which directly estimates current genetic variances as well as genetic correlations between populations. Copyright © 2017 by the Genetics Society of America.

  9. Repeatability and reproducibility of ribotyping and its computer interpretation.

    PubMed

    Lefresne, Gwénola; Latrille, Eric; Irlinger, Françoise; Grimont, Patrick A D

    2004-04-01

    Many molecular typing methods are difficult to interpret because their repeatability (within-laboratory variance) and reproducibility (between-laboratory variance) have not been thoroughly studied. In the present work, ribotyping of coryneform bacteria was the basis of a study involving within-gel and between-gel repeatability and between-laboratory reproducibility (two laboratories involved). The effect of different technical protocols, different algorithms, and different software for fragment size determination was studied. Analysis of variance (ANOVA) showed, within a laboratory, that there was no significant added variance between gels. However, between-laboratory variance was significantly higher than within-laboratory variance. This may be due to the use of different protocols. An experimental function was calculated to transform the data and make them compatible (i.e., erase the between-laboratory variance). The use of different interpolation algorithms (spline, Schaffer and Sederoff) was a significant source of variation in one laboratory only. The use of either Taxotron (Institut Pasteur) or GelCompar (Applied Maths) was not a significant source of added variation when the same algorithm (spline) was used. However, the use of Bio-Gene (Vilber Lourmat) dramatically increased the error (within laboratory, within gel) in one laboratory, while decreasing the error in the other laboratory; this might be due to automatic normalization attempts. These results were taken into account for building a database and performing automatic pattern identification using Taxotron. Conversion of the data considerably improved the identification of patterns irrespective of the laboratory in which the data were obtained.

  10. On Stabilizing the Variance of Dynamic Functional Brain Connectivity Time Series

    PubMed Central

    Fransson, Peter

    2016-01-01

    Abstract Assessment of dynamic functional brain connectivity based on functional magnetic resonance imaging (fMRI) data is an increasingly popular strategy to investigate temporal dynamics of the brain's large-scale network architecture. Current practice when deriving connectivity estimates over time is to use the Fisher transformation, which aims to stabilize the variance of correlation values that fluctuate around varying true correlation values. It is, however, unclear how well the stabilization of signal variance performed by the Fisher transformation works for each connectivity time series, when the true correlation is assumed to be fluctuating. This is of importance because many subsequent analyses either assume or perform better when the time series have stable variance or adheres to an approximate Gaussian distribution. In this article, using simulations and analysis of resting-state fMRI data, we analyze the effect of applying different variance stabilization strategies on connectivity time series. We focus our investigation on the Fisher transformation, the Box–Cox (BC) transformation and an approach that combines both transformations. Our results show that, if the intention of stabilizing the variance is to use metrics on the time series, where stable variance or a Gaussian distribution is desired (e.g., clustering), the Fisher transformation is not optimal and may even skew connectivity time series away from being Gaussian. Furthermore, we show that the suboptimal performance of the Fisher transformation can be substantially improved by including an additional BC transformation after the dynamic functional connectivity time series has been Fisher transformed. PMID:27784176

  11. On Stabilizing the Variance of Dynamic Functional Brain Connectivity Time Series.

    PubMed

    Thompson, William Hedley; Fransson, Peter

    2016-12-01

    Assessment of dynamic functional brain connectivity based on functional magnetic resonance imaging (fMRI) data is an increasingly popular strategy to investigate temporal dynamics of the brain's large-scale network architecture. Current practice when deriving connectivity estimates over time is to use the Fisher transformation, which aims to stabilize the variance of correlation values that fluctuate around varying true correlation values. It is, however, unclear how well the stabilization of signal variance performed by the Fisher transformation works for each connectivity time series, when the true correlation is assumed to be fluctuating. This is of importance because many subsequent analyses either assume or perform better when the time series have stable variance or adheres to an approximate Gaussian distribution. In this article, using simulations and analysis of resting-state fMRI data, we analyze the effect of applying different variance stabilization strategies on connectivity time series. We focus our investigation on the Fisher transformation, the Box-Cox (BC) transformation and an approach that combines both transformations. Our results show that, if the intention of stabilizing the variance is to use metrics on the time series, where stable variance or a Gaussian distribution is desired (e.g., clustering), the Fisher transformation is not optimal and may even skew connectivity time series away from being Gaussian. Furthermore, we show that the suboptimal performance of the Fisher transformation can be substantially improved by including an additional BC transformation after the dynamic functional connectivity time series has been Fisher transformed.

  12. The Importance of Variance in Statistical Analysis: Don't Throw Out the Baby with the Bathwater.

    ERIC Educational Resources Information Center

    Peet, Martha W.

    This paper analyzes what happens to the effect size of a given dataset when the variance is removed by categorization for the purpose of applying "OVA" methods (analysis of variance, analysis of covariance). The dataset is from a classic study by Holzinger and Swinefors (1939) in which more than 20 ability test were administered to 301…

  13. Comparing the Performance of Approaches for Testing the Homogeneity of Variance Assumption in One-Factor ANOVA Models

    ERIC Educational Resources Information Center

    Wang, Yan; Rodríguez de Gil, Patricia; Chen, Yi-Hsin; Kromrey, Jeffrey D.; Kim, Eun Sook; Pham, Thanh; Nguyen, Diep; Romano, Jeanine L.

    2017-01-01

    Various tests to check the homogeneity of variance assumption have been proposed in the literature, yet there is no consensus as to their robustness when the assumption of normality does not hold. This simulation study evaluated the performance of 14 tests for the homogeneity of variance assumption in one-way ANOVA models in terms of Type I error…

  14. 40 CFR 142.311 - What procedures allow the Administrator to object to a proposed small system variance or overturn...

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 40 Protection of Environment 22 2010-07-01 2010-07-01 false What procedures allow the Administrator to object to a proposed small system variance or overturn a granted small system variance for a public water system serving 3,300 or fewer persons? 142.311 Section 142.311 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER...

  15. Power and Sample Size Calculations for Testing Linear Combinations of Group Means under Variance Heterogeneity with Applications to Meta and Moderation Analyses

    ERIC Educational Resources Information Center

    Shieh, Gwowen; Jan, Show-Li

    2015-01-01

    The general formulation of a linear combination of population means permits a wide range of research questions to be tested within the context of ANOVA. However, it has been stressed in many research areas that the homogeneous variances assumption is frequently violated. To accommodate the heterogeneity of variance structure, the…

  16. Global Gravity Wave Variances from Aura MLS: Characteristics and Interpretation

    DTIC Science & Technology

    2008-12-01

    slight longitudinal variations, with secondary high- latitude peaks occurring over Greenland and Europe . As the QBO changes to the westerly phase, the...equatorial GW temperature variances from suborbital data (e.g., Eck- ermann et al. 1995). The extratropical wave variances are generally larger in the...emanating from tropopause altitudes, presumably radiated from tropospheric jet stream in- stabilities associated with baroclinic storm systems that

  17. 25 CFR 547.17 - How does a tribal gaming regulatory authority apply for a variance from these standards?

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... CLASS II GAMES § 547.17 How does a tribal gaming regulatory authority apply for a variance from these... 25 Indians 2 2010-04-01 2010-04-01 false How does a tribal gaming regulatory authority apply for a variance from these standards? 547.17 Section 547.17 Indians NATIONAL INDIAN GAMING COMMISSION, DEPARTMENT...

  18. The Expected Sample Variance of Uncorrelated Random Variables with a Common Mean and Some Applications in Unbalanced Random Effects Models

    ERIC Educational Resources Information Center

    Vardeman, Stephen B.; Wendelberger, Joanne R.

    2005-01-01

    There is a little-known but very simple generalization of the standard result that for uncorrelated random variables with common mean [mu] and variance [sigma][superscript 2], the expected value of the sample variance is [sigma][superscript 2]. The generalization justifies the use of the usual standard error of the sample mean in possibly…

  19. Genomic Analysis of Complex Microbial Communities in Wounds

    DTIC Science & Technology

    2012-01-01

    thoroughly in the ecology literature. Permutation Multivariate Analysis of Variance ( PerMANOVA ). We used PerMANOVA to test the null-hypothesis of no...difference between the bacterial communities found within a single wound compared to those from different patients (α = 0.05). PerMANOVA is a...permutation-based version of the multivariate analysis of variance (MANOVA). PerMANOVA uses the distances between samples to partition variance and

  20. Variance Difference between Maximum Likelihood Estimation Method and Expected A Posteriori Estimation Method Viewed from Number of Test Items

    ERIC Educational Resources Information Center

    Mahmud, Jumailiyah; Sutikno, Muzayanah; Naga, Dali S.

    2016-01-01

    The aim of this study is to determine variance difference between maximum likelihood and expected A posteriori estimation methods viewed from number of test items of aptitude test. The variance presents an accuracy generated by both maximum likelihood and Bayes estimation methods. The test consists of three subtests, each with 40 multiple-choice…

  1. 40 CFR 142.311 - What procedures allow the Administrator to object to a proposed small system variance or overturn...

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 40 Protection of Environment 23 2014-07-01 2014-07-01 false What procedures allow the Administrator to object to a proposed small system variance or overturn a granted small system variance for a public water system serving 3,300 or fewer persons? 142.311 Section 142.311 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER...

  2. Adult Second Language Reading in the USA: The Effects of Readers' Gender and Test Method

    ERIC Educational Resources Information Center

    Brantmeier, Cindy

    2006-01-01

    Bernhardt (2003) claims that half of the variance in second language (L2) reading is accounted for by first language literacy (20%) and second language knowledge (30%), and that one of the central goals of current L2 reading research should be to investigate the 50% of variance that remains unexplained. Part of this variance takes consists of…

  3. Systems, Subjects, Sessions: To What Extent Do These Factors Influence EEG Data?

    PubMed

    Melnik, Andrew; Legkov, Petr; Izdebski, Krzysztof; Kärcher, Silke M; Hairston, W David; Ferris, Daniel P; König, Peter

    2017-01-01

    Lab-based electroencephalography (EEG) techniques have matured over decades of research and can produce high-quality scientific data. It is often assumed that the specific choice of EEG system has limited impact on the data and does not add variance to the results. However, many low cost and mobile EEG systems are now available, and there is some doubt as to the how EEG data vary across these newer systems. We sought to determine how variance across systems compares to variance across subjects or repeated sessions. We tested four EEG systems: two standard research-grade systems, one system designed for mobile use with dry electrodes, and an affordable mobile system with a lower channel count. We recorded four subjects three times with each of the four EEG systems. This setup allowed us to assess the influence of all three factors on the variance of data. Subjects performed a battery of six short standard EEG paradigms based on event-related potentials (ERPs) and steady-state visually evoked potential (SSVEP). Results demonstrated that subjects account for 32% of the variance, systems for 9% of the variance, and repeated sessions for each subject-system combination for 1% of the variance. In most lab-based EEG research, the number of subjects per study typically ranges from 10 to 20, and error of uncertainty in estimates of the mean (like ERP) will improve by the square root of the number of subjects. As a result, the variance due to EEG system (9%) is of the same order of magnitude as variance due to subjects (32%/sqrt(16) = 8%) with a pool of 16 subjects. The two standard research-grade EEG systems had no significantly different means from each other across all paradigms. However, the two other EEG systems demonstrated different mean values from one or both of the two standard research-grade EEG systems in at least half of the paradigms. In addition to providing specific estimates of the variability across EEG systems, subjects, and repeated sessions, we also propose a benchmark to evaluate new mobile EEG systems by means of ERP responses.

  4. Estimation of genetic variance for macro- and micro-environmental sensitivity using double hierarchical generalized linear models.

    PubMed

    Mulder, Han A; Rönnegård, Lars; Fikse, W Freddy; Veerkamp, Roel F; Strandberg, Erling

    2013-07-04

    Genetic variation for environmental sensitivity indicates that animals are genetically different in their response to environmental factors. Environmental factors are either identifiable (e.g. temperature) and called macro-environmental or unknown and called micro-environmental. The objectives of this study were to develop a statistical method to estimate genetic parameters for macro- and micro-environmental sensitivities simultaneously, to investigate bias and precision of resulting estimates of genetic parameters and to develop and evaluate use of Akaike's information criterion using h-likelihood to select the best fitting model. We assumed that genetic variation in macro- and micro-environmental sensitivities is expressed as genetic variance in the slope of a linear reaction norm and environmental variance, respectively. A reaction norm model to estimate genetic variance for macro-environmental sensitivity was combined with a structural model for residual variance to estimate genetic variance for micro-environmental sensitivity using a double hierarchical generalized linear model in ASReml. Akaike's information criterion was constructed as model selection criterion using approximated h-likelihood. Populations of sires with large half-sib offspring groups were simulated to investigate bias and precision of estimated genetic parameters. Designs with 100 sires, each with at least 100 offspring, are required to have standard deviations of estimated variances lower than 50% of the true value. When the number of offspring increased, standard deviations of estimates across replicates decreased substantially, especially for genetic variances of macro- and micro-environmental sensitivities. Standard deviations of estimated genetic correlations across replicates were quite large (between 0.1 and 0.4), especially when sires had few offspring. Practically, no bias was observed for estimates of any of the parameters. Using Akaike's information criterion the true genetic model was selected as the best statistical model in at least 90% of 100 replicates when the number of offspring per sire was 100. Application of the model to lactation milk yield in dairy cattle showed that genetic variance for micro- and macro-environmental sensitivities existed. The algorithm and model selection criterion presented here can contribute to better understand genetic control of macro- and micro-environmental sensitivities. Designs or datasets should have at least 100 sires each with 100 offspring.

  5. Systems, Subjects, Sessions: To What Extent Do These Factors Influence EEG Data?

    PubMed Central

    Melnik, Andrew; Legkov, Petr; Izdebski, Krzysztof; Kärcher, Silke M.; Hairston, W. David; Ferris, Daniel P.; König, Peter

    2017-01-01

    Lab-based electroencephalography (EEG) techniques have matured over decades of research and can produce high-quality scientific data. It is often assumed that the specific choice of EEG system has limited impact on the data and does not add variance to the results. However, many low cost and mobile EEG systems are now available, and there is some doubt as to the how EEG data vary across these newer systems. We sought to determine how variance across systems compares to variance across subjects or repeated sessions. We tested four EEG systems: two standard research-grade systems, one system designed for mobile use with dry electrodes, and an affordable mobile system with a lower channel count. We recorded four subjects three times with each of the four EEG systems. This setup allowed us to assess the influence of all three factors on the variance of data. Subjects performed a battery of six short standard EEG paradigms based on event-related potentials (ERPs) and steady-state visually evoked potential (SSVEP). Results demonstrated that subjects account for 32% of the variance, systems for 9% of the variance, and repeated sessions for each subject-system combination for 1% of the variance. In most lab-based EEG research, the number of subjects per study typically ranges from 10 to 20, and error of uncertainty in estimates of the mean (like ERP) will improve by the square root of the number of subjects. As a result, the variance due to EEG system (9%) is of the same order of magnitude as variance due to subjects (32%/sqrt(16) = 8%) with a pool of 16 subjects. The two standard research-grade EEG systems had no significantly different means from each other across all paradigms. However, the two other EEG systems demonstrated different mean values from one or both of the two standard research-grade EEG systems in at least half of the paradigms. In addition to providing specific estimates of the variability across EEG systems, subjects, and repeated sessions, we also propose a benchmark to evaluate new mobile EEG systems by means of ERP responses. PMID:28424600

  6. Effects of Reduced Acuity and Stereo Acuity on Saccades and Reaching Movements in Adults With Amblyopia and Strabismus.

    PubMed

    Niechwiej-Szwedo, Ewa; Goltz, Herbert C; Colpa, Linda; Chandrakumar, Manokaraananthan; Wong, Agnes M F

    2017-02-01

    Our previous work has shown that amblyopia disrupts the planning and execution of visually-guided saccadic and reaching movements. We investigated the association between the clinical features of amblyopia and aspects of visuomotor behavior that are disrupted by amblyopia. A total of 55 adults with amblyopia (22 anisometropic, 18 strabismic, 15 mixed mechanism), 14 adults with strabismus without amblyopia, and 22 visually-normal control participants completed a visuomotor task while their eye and hand movements were recorded. Univariate and multivariate analyses were performed to assess the association between three clinical predictors of amblyopia (amblyopic eye [AE] acuity, stereo sensitivity, and eye deviation) and seven kinematic outcomes, including saccadic and reach latency, interocular saccadic and reach latency difference, saccadic and reach precision, and PA/We ratio (an index of reach control strategy efficacy using online feedback correction). Amblyopic eye acuity explained 28% of the variance in saccadic latency, and 48% of the variance in mean saccadic latency difference between the amblyopic and fellow eyes (i.e., interocular latency difference). In contrast, for reach latency, AE acuity explained only 10% of the variance. Amblyopic eye acuity was associated with reduced endpoint saccadic (23% of variance) and reach (22% of variance) precision in the amblyopic group. In the strabismus without amblyopia group, stereo sensitivity and eye deviation did not explain any significant variance in saccadic and reach latency or precision. Stereo sensitivity was the best clinical predictor of deficits in reach control strategy, explaining 23% of total variance of PA/We ratio in the amblyopic group and 12% of variance in the strabismus without amblyopia group when viewing with the amblyopic/nondominant eye. Deficits in eye and limb movement initiation (latency) and target localization (precision) were associated with amblyopic acuity deficit, whereas changes in the sensorimotor reach strategy were associated with deficits in stereopsis. Importantly, more than 50% of variance was not explained by the measured clinical features. Our findings suggest that other factors, including higher order visual processing and attention, may have an important role in explaining the kinematic deficits observed in amblyopia.

  7. Cross-bispectrum computation and variance estimation

    NASA Technical Reports Server (NTRS)

    Lii, K. S.; Helland, K. N.

    1981-01-01

    A method for the estimation of cross-bispectra of discrete real time series is developed. The asymptotic variance properties of the bispectrum are reviewed, and a method for the direct estimation of bispectral variance is given. The symmetry properties are described which minimize the computations necessary to obtain a complete estimate of the cross-bispectrum in the right-half-plane. A procedure is given for computing the cross-bispectrum by subdividing the domain into rectangular averaging regions which help reduce the variance of the estimates and allow easy application of the symmetry relationships to minimize the computational effort. As an example of the procedure, the cross-bispectrum of a numerically generated, exponentially distributed time series is computed and compared with theory.

  8. Examination of Variables That May Affect the Relationship Between Cognition and Functional Status in Individuals with Mild Cognitive Impairment: A Meta-Analysis

    PubMed Central

    Mcalister, Courtney; Schmitter-Edgecombe, Maureen; Lamb, Richard

    2016-01-01

    The objective of this meta-analysis was to improve understanding of the heterogeneity in the relationship between cognition and functional status in individuals with mild cognitive impairment (MCI). Demographic, clinical, and methodological moderators were examined. Cognition explained an average of 23% of the variance in functional outcomes. Executive function measures explained the largest amount of variance (37%), whereas global cognitive status and processing speed measures explained the least (20%). Short- and long-delayed memory measures accounted for more variance (35% and 31%) than immediate memory measures (18%), and the relationship between cognition and functional outcomes was stronger when assessed with informant-report (28%) compared with self-report (21%). Demographics, sample characteristics, and type of everyday functioning measures (i.e., questionnaire, performance-based) explained relatively little variance compared with cognition. Executive functioning, particularly measured by Trails B, was a strong predictor of everyday functioning in individuals with MCI. A large proportion of variance remained unexplained by cognition. PMID:26743326

  9. Comment on Hoffman and Rovine (2007): SPSS MIXED can estimate models with heterogeneous variances.

    PubMed

    Weaver, Bruce; Black, Ryan A

    2015-06-01

    Hoffman and Rovine (Behavior Research Methods, 39:101-117, 2007) have provided a very nice overview of how multilevel models can be useful to experimental psychologists. They included two illustrative examples and provided both SAS and SPSS commands for estimating the models they reported. However, upon examining the SPSS syntax for the models reported in their Table 3, we found no syntax for models 2B and 3B, both of which have heterogeneous error variances. Instead, there is syntax that estimates similar models with homogeneous error variances and a comment stating that SPSS does not allow heterogeneous errors. But that is not correct. We provide SPSS MIXED commands to estimate models 2B and 3B with heterogeneous error variances and obtain results nearly identical to those reported by Hoffman and Rovine in their Table 3. Therefore, contrary to the comment in Hoffman and Rovine's syntax file, SPSS MIXED can estimate models with heterogeneous error variances.

  10. Accounting for therapist variability in couple therapy outcomes: what really matters?

    PubMed

    Owen, Jesse; Duncan, Barry; Reese, Robert Jeff; Anker, Morten; Sparks, Jacqueline

    2014-01-01

    This study examined whether therapist gender, professional discipline, experience conducting couple therapy, and average second-session alliance score would account for the variance in outcomes attributed to the therapist. The authors investigated therapist variability in couple therapy with 158 couples randomly assigned to and treated by 18 therapists in a naturalistic setting. Consistent with previous studies in individual therapy, in this study therapists accounted for 8.0% of the variance in client outcomes and 10% of the variance in client alliance scores. Therapist average alliance score and experience conducting couple therapy were salient predictors of client outcomes attributed to therapist. In contrast, therapist gender and discipline did not significantly account for the variance in client outcomes attributed to therapists. Tests of incremental validity demonstrated that therapist average alliance score and therapist experience uniquely accounted for the variance in outcomes attributed to the therapist. Emphasis on improving therapist alliance quality and specificity of therapist experience in couple therapy are discussed.

  11. An efficient sampling approach for variance-based sensitivity analysis based on the law of total variance in the successive intervals without overlapping

    NASA Astrophysics Data System (ADS)

    Yun, Wanying; Lu, Zhenzhou; Jiang, Xian

    2018-06-01

    To efficiently execute the variance-based global sensitivity analysis, the law of total variance in the successive intervals without overlapping is proved at first, on which an efficient space-partition sampling-based approach is subsequently proposed in this paper. Through partitioning the sample points of output into different subsets according to different inputs, the proposed approach can efficiently evaluate all the main effects concurrently by one group of sample points. In addition, there is no need for optimizing the partition scheme in the proposed approach. The maximum length of subintervals is decreased by increasing the number of sample points of model input variables in the proposed approach, which guarantees the convergence condition of the space-partition approach well. Furthermore, a new interpretation on the thought of partition is illuminated from the perspective of the variance ratio function. Finally, three test examples and one engineering application are employed to demonstrate the accuracy, efficiency and robustness of the proposed approach.

  12. Neighborhood disadvantage as a moderator of the association between harsh parenting and toddler-aged children’s internalizing and externalizing problems

    PubMed Central

    Callahan, Kristin L.; Scaramella, Laura V.; Laird, Robert D.; Sohr-Preston, Sara L.

    2011-01-01

    Neighborhood dangerousness and belongingness were expected to moderate associations between harsh parenting and toddler-aged children’s problem behaviors. Fifty-five predominantly African American mothers participated with their 2-year old children. Neighborhood danger, neighborhood belongingness, and children’s problem behaviors were measured with mothers’ reports. Harsh parenting was measured with observer ratings. Analyses considered variance common to externalizing and internalizing problems, using a total problems score, and unique variance, by controlling for internalizing behavior when predicting externalizing behavior, and vice-versa. Regarding the common variance, only the main effects of neighborhood danger and harsh parenting were significantly associated with total problem behavior. In contrast, after controlling for externalizing problems, the positive association between harsh parenting and unique variance in internalizing problems became stronger as neighborhood danger increased. No statistically significant associations emerged for the models predicting the unique variance in externalizing problems or models considering neighborhood belongingness. PMID:21355648

  13. Neighborhood disadvantage as a moderator of the association between harsh parenting and toddler-aged children's internalizing and externalizing problems.

    PubMed

    Callahan, Kristin L; Scaramella, Laura V; Laird, Robert D; Sohr-Preston, Sara L

    2011-02-01

    Neighborhood dangerousness and belongingness were expected to moderate associations between harsh parenting and toddler-age children's problem behaviors. Fifty-five predominantly African American mothers participated with their 2-year old children. Neighborhood danger, neighborhood belongingness, and children's problem behaviors were measured with mothers' reports. Harsh parenting was measured with observer ratings. Analyses considered variance common to externalizing and internalizing problems, using a total problems score, and unique variance, by controlling for internalizing behavior when predicting externalizing behavior, and vice versa. Regarding the common variance, only the main effects of neighborhood danger and harsh parenting were significantly associated with total problem behavior. In contrast, after controlling for externalizing problems, the positive association between harsh parenting and unique variance in internalizing problems became stronger as neighborhood danger increased. No statistically significant associations emerged for the models predicting the unique variance in externalizing problems or models considering neighborhood belongingness. PsycINFO Database Record (c) 2011 APA, all rights reserved.

  14. A Bias and Variance Analysis for Multistep-Ahead Time Series Forecasting.

    PubMed

    Ben Taieb, Souhaib; Atiya, Amir F

    2016-01-01

    Multistep-ahead forecasts can either be produced recursively by iterating a one-step-ahead time series model or directly by estimating a separate model for each forecast horizon. In addition, there are other strategies; some of them combine aspects of both aforementioned concepts. In this paper, we present a comprehensive investigation into the bias and variance behavior of multistep-ahead forecasting strategies. We provide a detailed review of the different multistep-ahead strategies. Subsequently, we perform a theoretical study that derives the bias and variance for a number of forecasting strategies. Finally, we conduct a Monte Carlo experimental study that compares and evaluates the bias and variance performance of the different strategies. From the theoretical and the simulation studies, we analyze the effect of different factors, such as the forecast horizon and the time series length, on the bias and variance components, and on the different multistep-ahead strategies. Several lessons are learned, and recommendations are given concerning the advantages, disadvantages, and best conditions of use of each strategy.

  15. Modeling the subfilter scalar variance for large eddy simulation in forced isotropic turbulence

    NASA Astrophysics Data System (ADS)

    Cheminet, Adam; Blanquart, Guillaume

    2011-11-01

    Static and dynamic model for the subfilter scalar variance in homogeneous isotropic turbulence are investigated using direct numerical simulations (DNS) of a lineary forced passive scalar field. First, we introduce a new scalar forcing technique conditioned only on the scalar field which allows the fluctuating scalar field to reach a statistically stationary state. Statistical properties, including 2nd and 3rd statistical moments, spectra, and probability density functions of the scalar field have been analyzed. Using this technique, we performed constant density and variable density DNS of scalar mixing in isotropic turbulence. The results are used in an a-priori study of scalar variance models. Emphasis is placed on further studying the dynamic model introduced by G. Balarac, H. Pitsch and V. Raman [Phys. Fluids 20, (2008)]. Scalar variance models based on Bedford and Yeo's expansion are accurate for small filter width but errors arise in the inertial subrange. Results suggest that a constant coefficient computed from an assumed Kolmogorov spectrum is often sufficient to predict the subfilter scalar variance.

  16. Anthropometry as a predictor of high speed performance.

    PubMed

    Caruso, J F; Ramey, E; Hastings, L P; Monda, J K; Coday, M A; McLagan, J; Drummond, J

    2009-07-01

    To assess anthropometry as a predictor of high-speed performance, subjects performed four seated knee- and hip-extension workouts with their left leg on an inertial exercise trainer (Impulse Technologies, Newnan GA). Workouts, done exclusively in either the tonic or phasic contractile mode, entailed two one-minute sets separated by a 90-second rest period and yielded three performance variables: peak force, average force and work. Subjects provided the following anthropometric data: height, weight, body mass index, as well as total, upper and lower left leg lengths. Via multiple regression, anthropometry attempted to predict the variance per performance variable. Anthropometry explained a modest (R2=0.27-0.43) yet significant degree of variance from inertial exercise trainer workouts. Anthropometry was a better predictor of peak force variance from phasic workouts, while it accounted for a significant degree of average force and work variance solely from tonic workouts. Future research should identify variables that account for the unexplained variance from high-speed exercise performance.

  17. Jackknife for Variance Analysis of Multifactor Experiments.

    DTIC Science & Technology

    1982-05-01

    variance-covariance matrix is generated y a subroutine named CORAN (UNIVAC, 1969). The jackknife variances are then punched on computer cards in the same...LEVEL OF: InMte CALL cORAN (oaILa.NSUR.NOAY.D,*OXflRRORR.PCOF.2K.1’)I WRITE IP97111 )1RRN.4 .1:NDAY) 0 a 3fill1UR I .’t UN 001f’..1uŔ:1 .w100710n

  18. 40 CFR 142.312 - What EPA action is necessary when a State proposes to grant a small system variance to a public...

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... State proposes to grant a small system variance to a public water system serving a population of more... water system serving a population of more than 3,300 and fewer than 10,000 persons? (a) At the time a State proposes to grant a small system variance to a public water system serving a population of more...

  19. 40 CFR 142.312 - What EPA action is necessary when a State proposes to grant a small system variance to a public...

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... State proposes to grant a small system variance to a public water system serving a population of more... water system serving a population of more than 3,300 and fewer than 10,000 persons? (a) At the time a State proposes to grant a small system variance to a public water system serving a population of more...

  20. 40 CFR 142.312 - What EPA action is necessary when a State proposes to grant a small system variance to a public...

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... State proposes to grant a small system variance to a public water system serving a population of more... water system serving a population of more than 3,300 and fewer than 10,000 persons? (a) At the time a State proposes to grant a small system variance to a public water system serving a population of more...

  1. A de-noising method using the improved wavelet threshold function based on noise variance estimation

    NASA Astrophysics Data System (ADS)

    Liu, Hui; Wang, Weida; Xiang, Changle; Han, Lijin; Nie, Haizhao

    2018-01-01

    The precise and efficient noise variance estimation is very important for the processing of all kinds of signals while using the wavelet transform to analyze signals and extract signal features. In view of the problem that the accuracy of traditional noise variance estimation is greatly affected by the fluctuation of noise values, this study puts forward the strategy of using the two-state Gaussian mixture model to classify the high-frequency wavelet coefficients in the minimum scale, which takes both the efficiency and accuracy into account. According to the noise variance estimation, a novel improved wavelet threshold function is proposed by combining the advantages of hard and soft threshold functions, and on the basis of the noise variance estimation algorithm and the improved wavelet threshold function, the research puts forth a novel wavelet threshold de-noising method. The method is tested and validated using random signals and bench test data of an electro-mechanical transmission system. The test results indicate that the wavelet threshold de-noising method based on the noise variance estimation shows preferable performance in processing the testing signals of the electro-mechanical transmission system: it can effectively eliminate the interference of transient signals including voltage, current, and oil pressure and maintain the dynamic characteristics of the signals favorably.

  2. The variance modulation associated with the vestibular evoked myogenic potential.

    PubMed

    Lütkenhöner, Bernd; Rudack, Claudia; Basel, Türker

    2011-07-01

    Model considerations suggest that the sound-induced inhibition underlying the vestibular evoked myogenic potential (VEMP) briefly reduces the variance of the electromyogram (EMG) from which the VEMP is derived. Although more difficult to investigate, this inhibitory modulation of the variance promises to be a specific measure of the inhibition, in that respect being superior to the VEMP itself. This study aimed to verify the theoretical predictions. Archived data from 672 clinical VEMP investigations, comprising about 300,000 EMG records altogether, were pooled. Both the complete data pool and subsets of data representing VEMPs of varying degrees of distinctness were analyzed. The data were generally normalized so that the EMG had variance one. Regarding VEMP deflection p13, the data confirm the theoretical predictions. At the latency of deflection n23, however, an additional excitatory component, showing a maximal effect around 30 ms, appears to contribute. Studying the variance modulation may help to identify and characterize different components of the VEMP. In particular, it appears to be possible to distinguish between inhibition and excitation. The variance modulation provides information not being available in the VEMP itself. Thus, studying this measure may significantly contribute to our understanding of the VEMP phenomenon. Copyright © 2010 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

  3. An Evolutionary Perspective on Epistasis and the Missing Heritability

    PubMed Central

    Hemani, Gibran; Knott, Sara; Haley, Chris

    2013-01-01

    The relative importance between additive and non-additive genetic variance has been widely argued in quantitative genetics. By approaching this question from an evolutionary perspective we show that, while additive variance can be maintained under selection at a low level for some patterns of epistasis, the majority of the genetic variance that will persist is actually non-additive. We propose that one reason that the problem of the “missing heritability” arises is because the additive genetic variation that is estimated to be contributing to the variance of a trait will most likely be an artefact of the non-additive variance that can be maintained over evolutionary time. In addition, it can be shown that even a small reduction in linkage disequilibrium between causal variants and observed SNPs rapidly erodes estimates of epistatic variance, leading to an inflation in the perceived importance of additive effects. We demonstrate that the perception of independent additive effects comprising the majority of the genetic architecture of complex traits is biased upwards and that the search for causal variants in complex traits under selection is potentially underpowered by parameterising for additive effects alone. Given dense SNP panels the detection of causal variants through genome-wide association studies may be improved by searching for epistatic effects explicitly. PMID:23509438

  4. Performance of chromatographic systems to model soil-water sorption.

    PubMed

    Hidalgo-Rodríguez, Marta; Fuguet, Elisabet; Ràfols, Clara; Rosés, Martí

    2012-08-24

    A systematic approach for evaluating the goodness of chromatographic systems to model the sorption of neutral organic compounds by soil from water is presented in this work. It is based on the examination of the three sources of error that determine the overall variance obtained when soil-water partition coefficients are correlated against chromatographic retention factors: the variance of the soil-water sorption data, the variance of the chromatographic data, and the variance attributed to the dissimilarity between the two systems. These contributions of variance are easily predicted through the characterization of the systems by the solvation parameter model. According to this method, several chromatographic systems besides the reference octanol-water partition system have been selected to test their performance in the emulation of soil-water sorption. The results from the experimental correlations agree with the predicted variances. The high-performance liquid chromatography system based on an immobilized artificial membrane and the micellar electrokinetic chromatography systems of sodium dodecylsulfate and sodium taurocholate provide the most precise correlation models. They have shown to predict well soil-water sorption coefficients of several tested herbicides. Octanol-water partitions and high-performance liquid chromatography measurements using C18 columns are less suited for the estimation of soil-water partition coefficients. Copyright © 2012 Elsevier B.V. All rights reserved.

  5. Thermal noise variance of a receive radiofrequency coil as a respiratory motion sensor.

    PubMed

    Andreychenko, A; Raaijmakers, A J E; Sbrizzi, A; Crijns, S P M; Lagendijk, J J W; Luijten, P R; van den Berg, C A T

    2017-01-01

    Development of a passive respiratory motion sensor based on the noise variance of the receive coil array. Respiratory motion alters the body resistance. The noise variance of an RF coil depends on the body resistance and, thus, is also modulated by respiration. For the noise variance monitoring, the noise samples were acquired without and with MR signal excitation on clinical 1.5/3 T MR scanners. The performance of the noise sensor was compared with the respiratory bellow and with the diaphragm displacement visible on MR images. Several breathing patterns were tested. The noise variance demonstrated a periodic, temporal modulation that was synchronized with the respiratory bellow signal. The modulation depth of the noise variance resulting from the respiration varied between the channels of the array and depended on the channel's location with respect to the body. The noise sensor combined with MR acquisition was able to detect the respiratory motion for every k-space read-out line. Within clinical MR systems, the respiratory motion can be detected by the noise in receive array. The noise sensor does not require careful positioning unlike the bellow, any additional hardware, and/or MR acquisition. Magn Reson Med 77:221-228, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  6. A close examination of double filtering with fold change and t test in microarray analysis

    PubMed Central

    2009-01-01

    Background Many researchers use the double filtering procedure with fold change and t test to identify differentially expressed genes, in the hope that the double filtering will provide extra confidence in the results. Due to its simplicity, the double filtering procedure has been popular with applied researchers despite the development of more sophisticated methods. Results This paper, for the first time to our knowledge, provides theoretical insight on the drawback of the double filtering procedure. We show that fold change assumes all genes to have a common variance while t statistic assumes gene-specific variances. The two statistics are based on contradicting assumptions. Under the assumption that gene variances arise from a mixture of a common variance and gene-specific variances, we develop the theoretically most powerful likelihood ratio test statistic. We further demonstrate that the posterior inference based on a Bayesian mixture model and the widely used significance analysis of microarrays (SAM) statistic are better approximations to the likelihood ratio test than the double filtering procedure. Conclusion We demonstrate through hypothesis testing theory, simulation studies and real data examples, that well constructed shrinkage testing methods, which can be united under the mixture gene variance assumption, can considerably outperform the double filtering procedure. PMID:19995439

  7. Technical and biological variance structure in mRNA-Seq data: life in the real world

    PubMed Central

    2012-01-01

    Background mRNA expression data from next generation sequencing platforms is obtained in the form of counts per gene or exon. Counts have classically been assumed to follow a Poisson distribution in which the variance is equal to the mean. The Negative Binomial distribution which allows for over-dispersion, i.e., for the variance to be greater than the mean, is commonly used to model count data as well. Results In mRNA-Seq data from 25 subjects, we found technical variation to generally follow a Poisson distribution as has been reported previously and biological variability was over-dispersed relative to the Poisson model. The mean-variance relationship across all genes was quadratic, in keeping with a Negative Binomial (NB) distribution. Over-dispersed Poisson and NB distributional assumptions demonstrated marked improvements in goodness-of-fit (GOF) over the standard Poisson model assumptions, but with evidence of over-fitting in some genes. Modeling of experimental effects improved GOF for high variance genes but increased the over-fitting problem. Conclusions These conclusions will guide development of analytical strategies for accurate modeling of variance structure in these data and sample size determination which in turn will aid in the identification of true biological signals that inform our understanding of biological systems. PMID:22769017

  8. Sampling hazelnuts for aflatoxin: uncertainty associated with sampling, sample preparation, and analysis.

    PubMed

    Ozay, Guner; Seyhan, Ferda; Yilmaz, Aysun; Whitaker, Thomas B; Slate, Andrew B; Giesbrecht, Francis

    2006-01-01

    The variability associated with the aflatoxin test procedure used to estimate aflatoxin levels in bulk shipments of hazelnuts was investigated. Sixteen 10 kg samples of shelled hazelnuts were taken from each of 20 lots that were suspected of aflatoxin contamination. The total variance associated with testing shelled hazelnuts was estimated and partitioned into sampling, sample preparation, and analytical variance components. Each variance component increased as aflatoxin concentration (either B1 or total) increased. With the use of regression analysis, mathematical expressions were developed to model the relationship between aflatoxin concentration and the total, sampling, sample preparation, and analytical variances. The expressions for these relationships were used to estimate the variance for any sample size, subsample size, and number of analyses for a specific aflatoxin concentration. The sampling, sample preparation, and analytical variances associated with estimating aflatoxin in a hazelnut lot at a total aflatoxin level of 10 ng/g and using a 10 kg sample, a 50 g subsample, dry comminution with a Robot Coupe mill, and a high-performance liquid chromatographic analytical method are 174.40, 0.74, and 0.27, respectively. The sampling, sample preparation, and analytical steps of the aflatoxin test procedure accounted for 99.4, 0.4, and 0.2% of the total variability, respectively.

  9. The distribution of genetic variance across phenotypic space and the response to selection.

    PubMed

    Blows, Mark W; McGuigan, Katrina

    2015-05-01

    The role of adaptation in biological invasions will depend on the availability of genetic variation for traits under selection in the new environment. Although genetic variation is present for most traits in most populations, selection is expected to act on combinations of traits, not individual traits in isolation. The distribution of genetic variance across trait combinations can be characterized by the empirical spectral distribution of the genetic variance-covariance (G) matrix. Empirical spectral distributions of G from a range of trait types and taxa all exhibit a characteristic shape; some trait combinations have large levels of genetic variance, while others have very little genetic variance. In this study, we review what is known about the empirical spectral distribution of G and show how it predicts the response to selection across phenotypic space. In particular, trait combinations that form a nearly null genetic subspace with little genetic variance respond only inconsistently to selection. We go on to set out a framework for understanding how the empirical spectral distribution of G may differ from the random expectations that have been developed under random matrix theory (RMT). Using a data set containing a large number of gene expression traits, we illustrate how hypotheses concerning the distribution of multivariate genetic variance can be tested using RMT methods. We suggest that the relative alignment between novel selection pressures during invasion and the nearly null genetic subspace is likely to be an important component of the success or failure of invasion, and for the likelihood of rapid adaptation in small populations in general. © 2014 John Wiley & Sons Ltd.

  10. Spatial and temporal variance in fatty acid and stable isotope signatures across trophic levels in large river systems

    USGS Publications Warehouse

    Fritts, Andrea; Knights, Brent C.; Lafrancois, Toben D.; Bartsch, Lynn; Vallazza, Jon; Bartsch, Michelle; Richardson, William B.; Karns, Byron N.; Bailey, Sean; Kreiling, Rebecca

    2018-01-01

    Fatty acid and stable isotope signatures allow researchers to better understand food webs, food sources, and trophic relationships. Research in marine and lentic systems has indicated that the variance of these biomarkers can exhibit substantial differences across spatial and temporal scales, but this type of analysis has not been completed for large river systems. Our objectives were to evaluate variance structures for fatty acids and stable isotopes (i.e. δ13C and δ15N) of seston, threeridge mussels, hydropsychid caddisflies, gizzard shad, and bluegill across spatial scales (10s-100s km) in large rivers of the Upper Mississippi River Basin, USA that were sampled annually for two years, and to evaluate the implications of this variance on the design and interpretation of trophic studies. The highest variance for both isotopes was present at the largest spatial scale for all taxa (except seston δ15N) indicating that these isotopic signatures are responding to factors at a larger geographic level rather than being influenced by local-scale alterations. Conversely, the highest variance for fatty acids was present at the smallest spatial scale (i.e. among individuals) for all taxa except caddisflies, indicating that the physiological and metabolic processes that influence fatty acid profiles can differ substantially between individuals at a given site. Our results highlight the need to consider the spatial partitioning of variance during sample design and analysis, as some taxa may not be suitable to assess ecological questions at larger spatial scales.

  11. Parametric correlation functions to model the structure of permanent environmental (co)variances in milk yield random regression models.

    PubMed

    Bignardi, A B; El Faro, L; Cardoso, V L; Machado, P F; Albuquerque, L G

    2009-09-01

    The objective of the present study was to estimate milk yield genetic parameters applying random regression models and parametric correlation functions combined with a variance function to model animal permanent environmental effects. A total of 152,145 test-day milk yields from 7,317 first lactations of Holstein cows belonging to herds located in the southeastern region of Brazil were analyzed. Test-day milk yields were divided into 44 weekly classes of days in milk. Contemporary groups were defined by herd-test-day comprising a total of 2,539 classes. The model included direct additive genetic, permanent environmental, and residual random effects. The following fixed effects were considered: contemporary group, age of cow at calving (linear and quadratic regressions), and the population average lactation curve modeled by fourth-order orthogonal Legendre polynomial. Additive genetic effects were modeled by random regression on orthogonal Legendre polynomials of days in milk, whereas permanent environmental effects were estimated using a stationary or nonstationary parametric correlation function combined with a variance function of different orders. The structure of residual variances was modeled using a step function containing 6 variance classes. The genetic parameter estimates obtained with the model using a stationary correlation function associated with a variance function to model permanent environmental effects were similar to those obtained with models employing orthogonal Legendre polynomials for the same effect. A model using a sixth-order polynomial for additive effects and a stationary parametric correlation function associated with a seventh-order variance function to model permanent environmental effects would be sufficient for data fitting.

  12. Heritable Environmental Variance Causes Nonlinear Relationships Between Traits: Application to Birth Weight and Stillbirth of Pigs

    PubMed Central

    Mulder, Herman A.; Hill, William G.; Knol, Egbert F.

    2015-01-01

    There is recent evidence from laboratory experiments and analysis of livestock populations that not only the phenotype itself, but also its environmental variance, is under genetic control. Little is known about the relationships between the environmental variance of one trait and mean levels of other traits, however. A genetic covariance between these is expected to lead to nonlinearity between them, for example between birth weight and survival of piglets, where animals of extreme weights have lower survival. The objectives were to derive this nonlinear relationship analytically using multiple regression and apply it to data on piglet birth weight and survival. This study provides a framework to study such nonlinear relationships caused by genetic covariance of environmental variance of one trait and the mean of the other. It is shown that positions of phenotypic and genetic optima may differ and that genetic relationships are likely to be more curvilinear than phenotypic relationships, dependent mainly on the environmental correlation between these traits. Genetic correlations may change if the population means change relative to the optimal phenotypes. Data of piglet birth weight and survival show that the presence of nonlinearity can be partly explained by the genetic covariance between environmental variance of birth weight and survival. The framework developed can be used to assess effects of artificial and natural selection on means and variances of traits and the statistical method presented can be used to estimate trade-offs between environmental variance of one trait and mean levels of others. PMID:25631318

  13. Joint Adaptive Mean-Variance Regularization and Variance Stabilization of High Dimensional Data.

    PubMed

    Dazard, Jean-Eudes; Rao, J Sunil

    2012-07-01

    The paper addresses a common problem in the analysis of high-dimensional high-throughput "omics" data, which is parameter estimation across multiple variables in a set of data where the number of variables is much larger than the sample size. Among the problems posed by this type of data are that variable-specific estimators of variances are not reliable and variable-wise tests statistics have low power, both due to a lack of degrees of freedom. In addition, it has been observed in this type of data that the variance increases as a function of the mean. We introduce a non-parametric adaptive regularization procedure that is innovative in that : (i) it employs a novel "similarity statistic"-based clustering technique to generate local-pooled or regularized shrinkage estimators of population parameters, (ii) the regularization is done jointly on population moments, benefiting from C. Stein's result on inadmissibility, which implies that usual sample variance estimator is improved by a shrinkage estimator using information contained in the sample mean. From these joint regularized shrinkage estimators, we derived regularized t-like statistics and show in simulation studies that they offer more statistical power in hypothesis testing than their standard sample counterparts, or regular common value-shrinkage estimators, or when the information contained in the sample mean is simply ignored. Finally, we show that these estimators feature interesting properties of variance stabilization and normalization that can be used for preprocessing high-dimensional multivariate data. The method is available as an R package, called 'MVR' ('Mean-Variance Regularization'), downloadable from the CRAN website.

  14. Joint Adaptive Mean-Variance Regularization and Variance Stabilization of High Dimensional Data

    PubMed Central

    Dazard, Jean-Eudes; Rao, J. Sunil

    2012-01-01

    The paper addresses a common problem in the analysis of high-dimensional high-throughput “omics” data, which is parameter estimation across multiple variables in a set of data where the number of variables is much larger than the sample size. Among the problems posed by this type of data are that variable-specific estimators of variances are not reliable and variable-wise tests statistics have low power, both due to a lack of degrees of freedom. In addition, it has been observed in this type of data that the variance increases as a function of the mean. We introduce a non-parametric adaptive regularization procedure that is innovative in that : (i) it employs a novel “similarity statistic”-based clustering technique to generate local-pooled or regularized shrinkage estimators of population parameters, (ii) the regularization is done jointly on population moments, benefiting from C. Stein's result on inadmissibility, which implies that usual sample variance estimator is improved by a shrinkage estimator using information contained in the sample mean. From these joint regularized shrinkage estimators, we derived regularized t-like statistics and show in simulation studies that they offer more statistical power in hypothesis testing than their standard sample counterparts, or regular common value-shrinkage estimators, or when the information contained in the sample mean is simply ignored. Finally, we show that these estimators feature interesting properties of variance stabilization and normalization that can be used for preprocessing high-dimensional multivariate data. The method is available as an R package, called ‘MVR’ (‘Mean-Variance Regularization’), downloadable from the CRAN website. PMID:22711950

  15. One-shot estimate of MRMC variance: AUC.

    PubMed

    Gallas, Brandon D

    2006-03-01

    One popular study design for estimating the area under the receiver operating characteristic curve (AUC) is the one in which a set of readers reads a set of cases: a fully crossed design in which every reader reads every case. The variability of the subsequent reader-averaged AUC has two sources: the multiple readers and the multiple cases (MRMC). In this article, we present a nonparametric estimate for the variance of the reader-averaged AUC that is unbiased and does not use resampling tools. The one-shot estimate is based on the MRMC variance derived by the mechanistic approach of Barrett et al. (2005), as well as the nonparametric variance of a single-reader AUC derived in the literature on U statistics. We investigate the bias and variance properties of the one-shot estimate through a set of Monte Carlo simulations with simulated model observers and images. The different simulation configurations vary numbers of readers and cases, amounts of image noise and internal noise, as well as how the readers are constructed. We compare the one-shot estimate to a method that uses the jackknife resampling technique with an analysis of variance model at its foundation (Dorfman et al. 1992). The name one-shot highlights that resampling is not used. The one-shot and jackknife estimators behave similarly, with the one-shot being marginally more efficient when the number of cases is small. We have derived a one-shot estimate of the MRMC variance of AUC that is based on a probabilistic foundation with limited assumptions, is unbiased, and compares favorably to an established estimate.

  16. Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial DNA restriction data.

    PubMed

    Excoffier, L; Smouse, P E; Quattro, J M

    1992-06-01

    We present here a framework for the study of molecular variation within a single species. Information on DNA haplotype divergence is incorporated into an analysis of variance format, derived from a matrix of squared-distances among all pairs of haplotypes. This analysis of molecular variance (AMOVA) produces estimates of variance components and F-statistic analogs, designated here as phi-statistics, reflecting the correlation of haplotypic diversity at different levels of hierarchical subdivision. The method is flexible enough to accommodate several alternative input matrices, corresponding to different types of molecular data, as well as different types of evolutionary assumptions, without modifying the basic structure of the analysis. The significance of the variance components and phi-statistics is tested using a permutational approach, eliminating the normality assumption that is conventional for analysis of variance but inappropriate for molecular data. Application of AMOVA to human mitochondrial DNA haplotype data shows that population subdivisions are better resolved when some measure of molecular differences among haplotypes is introduced into the analysis. At the intraspecific level, however, the additional information provided by knowing the exact phylogenetic relations among haplotypes or by a nonlinear translation of restriction-site change into nucleotide diversity does not significantly modify the inferred population genetic structure. Monte Carlo studies show that site sampling does not fundamentally affect the significance of the molecular variance components. The AMOVA treatment is easily extended in several different directions and it constitutes a coherent and flexible framework for the statistical analysis of molecular data.

  17. Performance of time-varying predictors in multilevel models under an assumption of fixed or random effects.

    PubMed

    Baird, Rachel; Maxwell, Scott E

    2016-06-01

    Time-varying predictors in multilevel models are a useful tool for longitudinal research, whether they are the research variable of interest or they are controlling for variance to allow greater power for other variables. However, standard recommendations to fix the effect of time-varying predictors may make an assumption that is unlikely to hold in reality and may influence results. A simulation study illustrates that treating the time-varying predictor as fixed may allow analyses to converge, but the analyses have poor coverage of the true fixed effect when the time-varying predictor has a random effect in reality. A second simulation study shows that treating the time-varying predictor as random may have poor convergence, except when allowing negative variance estimates. Although negative variance estimates are uninterpretable, results of the simulation show that estimates of the fixed effect of the time-varying predictor are as accurate for these cases as for cases with positive variance estimates, and that treating the time-varying predictor as random and allowing negative variance estimates performs well whether the time-varying predictor is fixed or random in reality. Because of the difficulty of interpreting negative variance estimates, 2 procedures are suggested for selection between fixed-effect and random-effect models: comparing between fixed-effect and constrained random-effect models with a likelihood ratio test or fitting a fixed-effect model when an unconstrained random-effect model produces negative variance estimates. The performance of these 2 procedures is compared. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  18. Age-specific survival of male golden-cheeked warblers on the Fort Hood Military Reservation, Texas

    USGS Publications Warehouse

    Duarte, Adam; Hines, James E.; Nichols, James D.; Hatfield, Jeffrey S.; Weckerly, Floyd W.

    2014-01-01

    Population models are essential components of large-scale conservation and management plans for the federally endangered Golden-cheeked Warbler (Setophaga chrysoparia; hereafter GCWA). However, existing models are based on vital rate estimates calculated using relatively small data sets that are now more than a decade old. We estimated more current, precise adult and juvenile apparent survival (Φ) probabilities and their associated variances for male GCWAs. In addition to providing estimates for use in population modeling, we tested hypotheses about spatial and temporal variation in Φ. We assessed whether a linear trend in Φ or a change in the overall mean Φ corresponded to an observed increase in GCWA abundance during 1992-2000 and if Φ varied among study plots. To accomplish these objectives, we analyzed long-term GCWA capture-resight data from 1992 through 2011, collected across seven study plots on the Fort Hood Military Reservation using a Cormack-Jolly-Seber model structure within program MARK. We also estimated Φ process and sampling variances using a variance-components approach. Our results did not provide evidence of site-specific variation in adult Φ on the installation. Because of a lack of data, we could not assess whether juvenile Φ varied spatially. We did not detect a strong temporal association between GCWA abundance and Φ. Mean estimates of Φ for adult and juvenile male GCWAs for all years analyzed were 0.47 with a process variance of 0.0120 and a sampling variance of 0.0113 and 0.28 with a process variance of 0.0076 and a sampling variance of 0.0149, respectively. Although juvenile Φ did not differ greatly from previous estimates, our adult Φ estimate suggests previous GCWA population models were overly optimistic with respect to adult survival. These updated Φ probabilities and their associated variances will be incorporated into new population models to assist with GCWA conservation decision making.

  19. Deflation as a method of variance reduction for estimating the trace of a matrix inverse

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

    Gambhir, Arjun Singh; Stathopoulos, Andreas; Orginos, Kostas

    Many fields require computing the trace of the inverse of a large, sparse matrix. The typical method used for such computations is the Hutchinson method which is a Monte Carlo (MC) averaging over matrix quadratures. To improve its convergence, several variance reductions techniques have been proposed. In this paper, we study the effects of deflating the near null singular value space. We make two main contributions. First, we analyze the variance of the Hutchinson method as a function of the deflated singular values and vectors. Although this provides good intuition in general, by assuming additionally that the singular vectors aremore » random unitary matrices, we arrive at concise formulas for the deflated variance that include only the variance and mean of the singular values. We make the remarkable observation that deflation may increase variance for Hermitian matrices but not for non-Hermitian ones. This is a rare, if not unique, property where non-Hermitian matrices outperform Hermitian ones. The theory can be used as a model for predicting the benefits of deflation. Second, we use deflation in the context of a large scale application of "disconnected diagrams" in Lattice QCD. On lattices, Hierarchical Probing (HP) has previously provided an order of magnitude of variance reduction over MC by removing "error" from neighboring nodes of increasing distance in the lattice. Although deflation used directly on MC yields a limited improvement of 30% in our problem, when combined with HP they reduce variance by a factor of over 150 compared to MC. For this, we pre-computated 1000 smallest singular values of an ill-conditioned matrix of size 25 million. Furthermore, using PRIMME and a domain-specific Algebraic Multigrid preconditioner, we perform one of the largest eigenvalue computations in Lattice QCD at a fraction of the cost of our trace computation.« less

  20. Prediction-error variance in Bayesian model updating: a comparative study

    NASA Astrophysics Data System (ADS)

    Asadollahi, Parisa; Li, Jian; Huang, Yong

    2017-04-01

    In Bayesian model updating, the likelihood function is commonly formulated by stochastic embedding in which the maximum information entropy probability model of prediction error variances plays an important role and it is Gaussian distribution subject to the first two moments as constraints. The selection of prediction error variances can be formulated as a model class selection problem, which automatically involves a trade-off between the average data-fit of the model class and the information it extracts from the data. Therefore, it is critical for the robustness in the updating of the structural model especially in the presence of modeling errors. To date, three ways of considering prediction error variances have been seem in the literature: 1) setting constant values empirically, 2) estimating them based on the goodness-of-fit of the measured data, and 3) updating them as uncertain parameters by applying Bayes' Theorem at the model class level. In this paper, the effect of different strategies to deal with the prediction error variances on the model updating performance is investigated explicitly. A six-story shear building model with six uncertain stiffness parameters is employed as an illustrative example. Transitional Markov Chain Monte Carlo is used to draw samples of the posterior probability density function of the structure model parameters as well as the uncertain prediction variances. The different levels of modeling uncertainty and complexity are modeled through three FE models, including a true model, a model with more complexity, and a model with modeling error. Bayesian updating is performed for the three FE models considering the three aforementioned treatments of the prediction error variances. The effect of number of measurements on the model updating performance is also examined in the study. The results are compared based on model class assessment and indicate that updating the prediction error variances as uncertain parameters at the model class level produces more robust results especially when the number of measurement is small.

  1. Deflation as a method of variance reduction for estimating the trace of a matrix inverse

    DOE PAGES

    Gambhir, Arjun Singh; Stathopoulos, Andreas; Orginos, Kostas

    2017-04-06

    Many fields require computing the trace of the inverse of a large, sparse matrix. The typical method used for such computations is the Hutchinson method which is a Monte Carlo (MC) averaging over matrix quadratures. To improve its convergence, several variance reductions techniques have been proposed. In this paper, we study the effects of deflating the near null singular value space. We make two main contributions. First, we analyze the variance of the Hutchinson method as a function of the deflated singular values and vectors. Although this provides good intuition in general, by assuming additionally that the singular vectors aremore » random unitary matrices, we arrive at concise formulas for the deflated variance that include only the variance and mean of the singular values. We make the remarkable observation that deflation may increase variance for Hermitian matrices but not for non-Hermitian ones. This is a rare, if not unique, property where non-Hermitian matrices outperform Hermitian ones. The theory can be used as a model for predicting the benefits of deflation. Second, we use deflation in the context of a large scale application of "disconnected diagrams" in Lattice QCD. On lattices, Hierarchical Probing (HP) has previously provided an order of magnitude of variance reduction over MC by removing "error" from neighboring nodes of increasing distance in the lattice. Although deflation used directly on MC yields a limited improvement of 30% in our problem, when combined with HP they reduce variance by a factor of over 150 compared to MC. For this, we pre-computated 1000 smallest singular values of an ill-conditioned matrix of size 25 million. Furthermore, using PRIMME and a domain-specific Algebraic Multigrid preconditioner, we perform one of the largest eigenvalue computations in Lattice QCD at a fraction of the cost of our trace computation.« less

  2. A Mean variance analysis of arbitrage portfolios

    NASA Astrophysics Data System (ADS)

    Fang, Shuhong

    2007-03-01

    Based on the careful analysis of the definition of arbitrage portfolio and its return, the author presents a mean-variance analysis of the return of arbitrage portfolios, which implies that Korkie and Turtle's results ( B. Korkie, H.J. Turtle, A mean-variance analysis of self-financing portfolios, Manage. Sci. 48 (2002) 427-443) are misleading. A practical example is given to show the difference between the arbitrage portfolio frontier and the usual portfolio frontier.

  3. A comparison of two follow-up analyses after multiple analysis of variance, analysis of variance, and descriptive discriminant analysis: A case study of the program effects on education-abroad programs

    Treesearch

    Alvin H. Yu; Garry Chick

    2010-01-01

    This study compared the utility of two different post-hoc tests after detecting significant differences within factors on multiple dependent variables using multivariate analysis of variance (MANOVA). We compared the univariate F test (the Scheffé method) to descriptive discriminant analysis (DDA) using an educational-tour survey of university study-...

  4. Concerns about a variance approach to X-ray diffractometric estimation of microfibril angle in wood

    Treesearch

    Steve P. Verrill; David E. Kretschmann; Victoria L. Herian; Michael C. Wiemann; Harry A. Alden

    2011-01-01

    In this article, we raise three technical concerns about Evans’ 1999 Appita Journal “variance approach” to estimating microfibril angle (MFA). The first concern is associated with the approximation of the variance of an X-ray intensity half-profile by a function of the MFA and the natural variability of the MFA. The second concern is associated with the approximation...

  5. Concerns about a variance approach to the X-ray diffractometric estimation of microfibril angle in wood

    Treesearch

    Steve P. Verrill; David E. Kretschmann; Victoria L. Herian; Michael Wiemann; Harry A. Alden

    2010-01-01

    In this paper we raise three technical concerns about Evans’s 1999 Appita Journal “variance approach” to estimating microfibril angle. The first concern is associated with the approximation of the variance of an X-ray intensity half-profile by a function of the microfibril angle and the natural variability of the microfibril angle, S2...

  6. Simulation of Autonomic Logistics System (ALS) Sortie Generation

    DTIC Science & Technology

    2003-03-01

    84 Appendix B. ANOVA Assumptions Mission Capable Rate ANOVA Assumptions Constant Variance SSR # X cols SSE n Breusch - Pagan Chi-square 3.57E...85 Flying Scheduling Effectiveness ANOVA Assumptions Constant Variance SSR # X cols SSE n Breusch - Pagan Chi-square 2.12E-10 3 0.000816 270...Constant Variance SSR # X cols SSE n Breusch - Pagan Chi-square 1.86E-09 3 0.003758 270 3.20308814 0.9556957 Independence Durbin-Watson

  7. Predicting Cost and Schedule Growth for Military and Civil Space Systems

    DTIC Science & Technology

    2008-03-01

    the Shapiro-Wilk Test , and testing the residuals for constant variance using the Breusch - Pagan test . For logistic models, diagnostics include...the Breusch - Pagan Test . With this test , a p-value below 0.05 rejects the null hypothesis that the residuals have constant variance. Thus, similar...to the Shapiro- Wilk Test , because the optimal model will have constant variance of its residuals, this requires Breusch - Pagan p-values over 0.05

  8. The Impact of Economic Factors and Acquisition Reforms on the Cost of Defense Weapon Systems

    DTIC Science & Technology

    2006-03-01

    test for homoskedasticity, the Breusch - Pagan test is employed. The null hypothesis of the Breusch - Pagan test is that the variance is equal to zero...made. Using the Breusch - Pagan test shown in Table 19 below, the prob>chi2 is greater than 05.=α , therefore we fail to reject the null hypothesis...overrunpercentfp100 Breusch - Pagan Test (Ho=Constant Variance) Estimated Results Variance Standard Deviation overrunpercent100

  9. Jackknife Estimation of Sampling Variance of Ratio Estimators in Complex Samples: Bias and the Coefficient of Variation. Research Report. ETS RR-06-19

    ERIC Educational Resources Information Center

    Oranje, Andreas

    2006-01-01

    A multitude of methods has been proposed to estimate the sampling variance of ratio estimates in complex samples (Wolter, 1985). Hansen and Tepping (1985) studied some of those variance estimators and found that a high coefficient of variation (CV) of the denominator of a ratio estimate is indicative of a biased estimate of the standard error of a…

  10. Tests of Mediation: Paradoxical Decline in Statistical Power as a Function of Mediator Collinearity

    PubMed Central

    Beasley, T. Mark

    2013-01-01

    Increasing the correlation between the independent variable and the mediator (a coefficient) increases the effect size (ab) for mediation analysis; however, increasing a by definition increases collinearity in mediation models. As a result, the standard error of product tests increase. The variance inflation due to increases in a at some point outweighs the increase of the effect size (ab) and results in a loss of statistical power. This phenomenon also occurs with nonparametric bootstrapping approaches because the variance of the bootstrap distribution of ab approximates the variance expected from normal theory. Both variances increase dramatically when a exceeds the b coefficient, thus explaining the power decline with increases in a. Implications for statistical analysis and applied researchers are discussed. PMID:24954952

  11. 42 CFR 456.520 - Definitions.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... ASSISTANCE PROGRAMS UTILIZATION CONTROL Utilization Review Plans: FFP, Waivers, and Variances for Hospitals and Mental Hospitals Ur Plan: Remote Facility Variances from Time Requirements § 456.520 Definitions...

  12. Maintaining evolvability.

    PubMed

    Crow, James F

    2008-12-01

    Although molecular methods, such as QTL mapping, have revealed a number of loci with large effects, it is still likely that the bulk of quantitative variability is due to multiple factors, each with small effect. Typically, these have a large additive component. Conventional wisdom argues that selection, natural or artificial, uses up additive variance and thus depletes its supply. Over time, the variance should be reduced, and at equilibrium be near zero. This is especially expected for fitness and traits highly correlated with it. Yet, populations typically have a great deal of additive variance, and do not seem to run out of genetic variability even after many generations of directional selection. Long-term selection experiments show that populations continue to retain seemingly undiminished additive variance despite large changes in the mean value. I propose that there are several reasons for this. (i) The environment is continually changing so that what was formerly most fit no longer is. (ii) There is an input of genetic variance from mutation, and sometimes from migration. (iii) As intermediate-frequency alleles increase in frequency towards one, producing less variance (as p --> 1, p(1 - p) --> 0), others that were originally near zero become more common and increase the variance. Thus, a roughly constant variance is maintained. (iv) There is always selection for fitness and for characters closely related to it. To the extent that the trait is heritable, later generations inherit a disproportionate number of genes acting additively on the trait, thus increasing genetic variance. For these reasons a selected population retains its ability to evolve. Of course, genes with large effect are also important. Conspicuous examples are the small number of loci that changed teosinte to maize, and major phylogenetic changes in the animal kingdom. The relative importance of these along with duplications, chromosome rearrangements, horizontal transmission and polyploidy is yet to be determined. It is likely that only a case-by-case analysis will provide the answers. Despite the difficulties that complex interactions cause for evolution in Mendelian populations, such populations nevertheless evolve very well. Longlasting species must have evolved mechanisms for coping with such problems. Since such difficulties do not arise in asexual populations, a comparison of epistatic patterns in closely related sexual and asexual species might provide some important insights.

  13. Estimation of genetic variance for macro- and micro-environmental sensitivity using double hierarchical generalized linear models

    PubMed Central

    2013-01-01

    Background Genetic variation for environmental sensitivity indicates that animals are genetically different in their response to environmental factors. Environmental factors are either identifiable (e.g. temperature) and called macro-environmental or unknown and called micro-environmental. The objectives of this study were to develop a statistical method to estimate genetic parameters for macro- and micro-environmental sensitivities simultaneously, to investigate bias and precision of resulting estimates of genetic parameters and to develop and evaluate use of Akaike’s information criterion using h-likelihood to select the best fitting model. Methods We assumed that genetic variation in macro- and micro-environmental sensitivities is expressed as genetic variance in the slope of a linear reaction norm and environmental variance, respectively. A reaction norm model to estimate genetic variance for macro-environmental sensitivity was combined with a structural model for residual variance to estimate genetic variance for micro-environmental sensitivity using a double hierarchical generalized linear model in ASReml. Akaike’s information criterion was constructed as model selection criterion using approximated h-likelihood. Populations of sires with large half-sib offspring groups were simulated to investigate bias and precision of estimated genetic parameters. Results Designs with 100 sires, each with at least 100 offspring, are required to have standard deviations of estimated variances lower than 50% of the true value. When the number of offspring increased, standard deviations of estimates across replicates decreased substantially, especially for genetic variances of macro- and micro-environmental sensitivities. Standard deviations of estimated genetic correlations across replicates were quite large (between 0.1 and 0.4), especially when sires had few offspring. Practically, no bias was observed for estimates of any of the parameters. Using Akaike’s information criterion the true genetic model was selected as the best statistical model in at least 90% of 100 replicates when the number of offspring per sire was 100. Application of the model to lactation milk yield in dairy cattle showed that genetic variance for micro- and macro-environmental sensitivities existed. Conclusion The algorithm and model selection criterion presented here can contribute to better understand genetic control of macro- and micro-environmental sensitivities. Designs or datasets should have at least 100 sires each with 100 offspring. PMID:23827014

  14. The mean and variance of phylogenetic diversity under rarefaction

    PubMed Central

    Matsen, Frederick A.

    2013-01-01

    Summary Phylogenetic diversity (PD) depends on sampling depth, which complicates the comparison of PD between samples of different depth. One approach to dealing with differing sample depth for a given diversity statistic is to rarefy, which means to take a random subset of a given size of the original sample. Exact analytical formulae for the mean and variance of species richness under rarefaction have existed for some time but no such solution exists for PD.We have derived exact formulae for the mean and variance of PD under rarefaction. We confirm that these formulae are correct by comparing exact solution mean and variance to that calculated by repeated random (Monte Carlo) subsampling of a dataset of stem counts of woody shrubs of Toohey Forest, Queensland, Australia. We also demonstrate the application of the method using two examples: identifying hotspots of mammalian diversity in Australasian ecoregions, and characterising the human vaginal microbiome.There is a very high degree of correspondence between the analytical and random subsampling methods for calculating mean and variance of PD under rarefaction, although the Monte Carlo method requires a large number of random draws to converge on the exact solution for the variance.Rarefaction of mammalian PD of ecoregions in Australasia to a common standard of 25 species reveals very different rank orderings of ecoregions, indicating quite different hotspots of diversity than those obtained for unrarefied PD. The application of these methods to the vaginal microbiome shows that a classical score used to quantify bacterial vaginosis is correlated with the shape of the rarefaction curve.The analytical formulae for the mean and variance of PD under rarefaction are both exact and more efficient than repeated subsampling. Rarefaction of PD allows for many applications where comparisons of samples of different depth is required. PMID:23833701

  15. The mean and variance of phylogenetic diversity under rarefaction.

    PubMed

    Nipperess, David A; Matsen, Frederick A

    2013-06-01

    Phylogenetic diversity (PD) depends on sampling depth, which complicates the comparison of PD between samples of different depth. One approach to dealing with differing sample depth for a given diversity statistic is to rarefy, which means to take a random subset of a given size of the original sample. Exact analytical formulae for the mean and variance of species richness under rarefaction have existed for some time but no such solution exists for PD.We have derived exact formulae for the mean and variance of PD under rarefaction. We confirm that these formulae are correct by comparing exact solution mean and variance to that calculated by repeated random (Monte Carlo) subsampling of a dataset of stem counts of woody shrubs of Toohey Forest, Queensland, Australia. We also demonstrate the application of the method using two examples: identifying hotspots of mammalian diversity in Australasian ecoregions, and characterising the human vaginal microbiome.There is a very high degree of correspondence between the analytical and random subsampling methods for calculating mean and variance of PD under rarefaction, although the Monte Carlo method requires a large number of random draws to converge on the exact solution for the variance.Rarefaction of mammalian PD of ecoregions in Australasia to a common standard of 25 species reveals very different rank orderings of ecoregions, indicating quite different hotspots of diversity than those obtained for unrarefied PD. The application of these methods to the vaginal microbiome shows that a classical score used to quantify bacterial vaginosis is correlated with the shape of the rarefaction curve.The analytical formulae for the mean and variance of PD under rarefaction are both exact and more efficient than repeated subsampling. Rarefaction of PD allows for many applications where comparisons of samples of different depth is required.

  16. Sampling design optimisation for rainfall prediction using a non-stationary geostatistical model

    NASA Astrophysics Data System (ADS)

    Wadoux, Alexandre M. J.-C.; Brus, Dick J.; Rico-Ramirez, Miguel A.; Heuvelink, Gerard B. M.

    2017-09-01

    The accuracy of spatial predictions of rainfall by merging rain-gauge and radar data is partly determined by the sampling design of the rain-gauge network. Optimising the locations of the rain-gauges may increase the accuracy of the predictions. Existing spatial sampling design optimisation methods are based on minimisation of the spatially averaged prediction error variance under the assumption of intrinsic stationarity. Over the past years, substantial progress has been made to deal with non-stationary spatial processes in kriging. Various well-documented geostatistical models relax the assumption of stationarity in the mean, while recent studies show the importance of considering non-stationarity in the variance for environmental processes occurring in complex landscapes. We optimised the sampling locations of rain-gauges using an extension of the Kriging with External Drift (KED) model for prediction of rainfall fields. The model incorporates both non-stationarity in the mean and in the variance, which are modelled as functions of external covariates such as radar imagery, distance to radar station and radar beam blockage. Spatial predictions are made repeatedly over time, each time recalibrating the model. The space-time averaged KED variance was minimised by Spatial Simulated Annealing (SSA). The methodology was tested using a case study predicting daily rainfall in the north of England for a one-year period. Results show that (i) the proposed non-stationary variance model outperforms the stationary variance model, and (ii) a small but significant decrease of the rainfall prediction error variance is obtained with the optimised rain-gauge network. In particular, it pays off to place rain-gauges at locations where the radar imagery is inaccurate, while keeping the distribution over the study area sufficiently uniform.

  17. Blinded sample size re-estimation in three-arm trials with 'gold standard' design.

    PubMed

    Mütze, Tobias; Friede, Tim

    2017-10-15

    In this article, we study blinded sample size re-estimation in the 'gold standard' design with internal pilot study for normally distributed outcomes. The 'gold standard' design is a three-arm clinical trial design that includes an active and a placebo control in addition to an experimental treatment. We focus on the absolute margin approach to hypothesis testing in three-arm trials at which the non-inferiority of the experimental treatment and the assay sensitivity are assessed by pairwise comparisons. We compare several blinded sample size re-estimation procedures in a simulation study assessing operating characteristics including power and type I error. We find that sample size re-estimation based on the popular one-sample variance estimator results in overpowered trials. Moreover, sample size re-estimation based on unbiased variance estimators such as the Xing-Ganju variance estimator results in underpowered trials, as it is expected because an overestimation of the variance and thus the sample size is in general required for the re-estimation procedure to eventually meet the target power. To overcome this problem, we propose an inflation factor for the sample size re-estimation with the Xing-Ganju variance estimator and show that this approach results in adequately powered trials. Because of favorable features of the Xing-Ganju variance estimator such as unbiasedness and a distribution independent of the group means, the inflation factor does not depend on the nuisance parameter and, therefore, can be calculated prior to a trial. Moreover, we prove that the sample size re-estimation based on the Xing-Ganju variance estimator does not bias the effect estimate. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  18. Variance estimation when using inverse probability of treatment weighting (IPTW) with survival analysis.

    PubMed

    Austin, Peter C

    2016-12-30

    Propensity score methods are used to reduce the effects of observed confounding when using observational data to estimate the effects of treatments or exposures. A popular method of using the propensity score is inverse probability of treatment weighting (IPTW). When using this method, a weight is calculated for each subject that is equal to the inverse of the probability of receiving the treatment that was actually received. These weights are then incorporated into the analyses to minimize the effects of observed confounding. Previous research has found that these methods result in unbiased estimation when estimating the effect of treatment on survival outcomes. However, conventional methods of variance estimation were shown to result in biased estimates of standard error. In this study, we conducted an extensive set of Monte Carlo simulations to examine different methods of variance estimation when using a weighted Cox proportional hazards model to estimate the effect of treatment. We considered three variance estimation methods: (i) a naïve model-based variance estimator; (ii) a robust sandwich-type variance estimator; and (iii) a bootstrap variance estimator. We considered estimation of both the average treatment effect and the average treatment effect in the treated. We found that the use of a bootstrap estimator resulted in approximately correct estimates of standard errors and confidence intervals with the correct coverage rates. The other estimators resulted in biased estimates of standard errors and confidence intervals with incorrect coverage rates. Our simulations were informed by a case study examining the effect of statin prescribing on mortality. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

  19. An Empirical Assessment of Defense Contractor Risk 1976-1984.

    DTIC Science & Technology

    1986-06-01

    Model to evaluate the. Department of Defense contract pricing , financing, and profit policies . ’ D*’ ’ *NTV D? 7A’:: TA E *A l ..... -:- A-i SN 0102...defense con- tractor risk-return relationship is performed utilizing four methods: mean-variance analysis of rate of return, the Capital Asset Pricing Model ...relationship is performed utilizing four methods: mean- variance analysis of rate of return, the Capital Asset Pricing Model , mean-variance analysis of total

  20. Enhanced backscatter of a reflected beam in atmospheric turbulence

    NASA Astrophysics Data System (ADS)

    Churnside, James H.; Wilson, James J.

    1993-05-01

    We measure the mean and the variance of the irradiance of a diverging laser beam after reflection from a retroreflector and from a plane mirror in a turbulent atmosphere. Increases in both the mean irradiance and the normalized variance are observed in the direct backscatter direction because of correlation of turbulence on the outgoing path and the return path. The backscattered irradiance is enhanced by a factor of about 2 and the variance by somewhat less.

  1. Possibility of modifying the growth trajectory in Raeini Cashmere goat.

    PubMed

    Ghiasi, Heydar; Mokhtari, M S

    2018-03-27

    The objective of this study was to investigate the possibility of modifying the growth trajectory in Raeini Cashmere goat breed. In total, 13,193 records on live body weight collected from 4788 Raeini Cashmere goats were used. According to Akanke's information criterion (AIC), the sing-trait random regression model included fourth-order Legendre polynomial for direct and maternal genetic effect; maternal and individual permanent environmental effect was the best model for estimating (co)variance components. The matrices of eigenvectors for (co)variances between random regression coefficients of direct additive genetic were used to calculate eigenfunctions, and different eigenvector indices were also constructed. The obtained results showed that the first eigenvalue explained 79.90% of total genetic variance. Therefore, changing the body weights applying the first eigenfunction will be obtained rapidly. Selection based on the first eigenvector will cause favorable positive genetic gains for all body weight considered from birth to 12 months of age. For modifying the growth trajectory in Raeini Cashmere goat, the selection should be based on the second eigenfunction. The second eigenvalue accounted for 14.41% of total genetic variance for body weights that is low in comparison with genetic variance explained by the first eigenvalue. The complex patterns of genetic change in growth trajectory observed under the third and fourth eigenfunction and low amount of genetic variance explained by the third and fourth eigenvalues.

  2. Investigation of noise properties in grating-based x-ray phase tomography with reverse projection method

    NASA Astrophysics Data System (ADS)

    Bao, Yuan; Wang, Yan; Gao, Kun; Wang, Zhi-Li; Zhu, Pei-Ping; Wu, Zi-Yu

    2015-10-01

    The relationship between noise variance and spatial resolution in grating-based x-ray phase computed tomography (PCT) imaging is investigated with reverse projection extraction method, and the noise variances of the reconstructed absorption coefficient and refractive index decrement are compared. For the differential phase contrast method, the noise variance in the differential projection images follows the same inverse-square law with spatial resolution as in conventional absorption-based x-ray imaging projections. However, both theoretical analysis and simulations demonstrate that in PCT the noise variance of the reconstructed refractive index decrement scales with spatial resolution follows an inverse linear relationship at fixed slice thickness, while the noise variance of the reconstructed absorption coefficient conforms with the inverse cubic law. The results indicate that, for the same noise variance level, PCT imaging may enable higher spatial resolution than conventional absorption computed tomography (ACT), while ACT benefits more from degraded spatial resolution. This could be a useful guidance in imaging the inner structure of the sample in higher spatial resolution. Project supported by the National Basic Research Program of China (Grant No. 2012CB825800), the Science Fund for Creative Research Groups, the Knowledge Innovation Program of the Chinese Academy of Sciences (Grant Nos. KJCX2-YW-N42 and Y4545320Y2), the National Natural Science Foundation of China (Grant Nos. 11475170, 11205157, 11305173, 11205189, 11375225, 11321503, 11179004, and U1332109).

  3. Strategies for Selecting Crosses Using Genomic Prediction in Two Wheat Breeding Programs.

    PubMed

    Lado, Bettina; Battenfield, Sarah; Guzmán, Carlos; Quincke, Martín; Singh, Ravi P; Dreisigacker, Susanne; Peña, R Javier; Fritz, Allan; Silva, Paula; Poland, Jesse; Gutiérrez, Lucía

    2017-07-01

    The single most important decision in plant breeding programs is the selection of appropriate crosses. The ideal cross would provide superior predicted progeny performance and enough diversity to maintain genetic gain. The aim of this study was to compare the best crosses predicted using combinations of mid-parent value and variance prediction accounting for linkage disequilibrium (V) or assuming linkage equilibrium (V). After predicting the mean and the variance of each cross, we selected crosses based on mid-parent value, the top 10% of the progeny, and weighted mean and variance within progenies for grain yield, grain protein content, mixing time, and loaf volume in two applied wheat ( L.) breeding programs: Instituto Nacional de Investigación Agropecuaria (INIA) Uruguay and CIMMYT Mexico. Although the variance of the progeny is important to increase the chances of finding superior individuals from transgressive segregation, we observed that the mid-parent values of the crosses drove the genetic gain but the variance of the progeny had a small impact on genetic gain for grain yield. However, the relative importance of the variance of the progeny was larger for quality traits. Overall, the genomic resources and the statistical models are now available to plant breeders to predict both the performance of breeding lines per se as well as the value of progeny from any potential crosses. Copyright © 2017 Crop Science Society of America.

  4. Partial covariance based functional connectivity computation using Ledoit-Wolf covariance regularization.

    PubMed

    Brier, Matthew R; Mitra, Anish; McCarthy, John E; Ances, Beau M; Snyder, Abraham Z

    2015-11-01

    Functional connectivity refers to shared signals among brain regions and is typically assessed in a task free state. Functional connectivity commonly is quantified between signal pairs using Pearson correlation. However, resting-state fMRI is a multivariate process exhibiting a complicated covariance structure. Partial covariance assesses the unique variance shared between two brain regions excluding any widely shared variance, hence is appropriate for the analysis of multivariate fMRI datasets. However, calculation of partial covariance requires inversion of the covariance matrix, which, in most functional connectivity studies, is not invertible owing to rank deficiency. Here we apply Ledoit-Wolf shrinkage (L2 regularization) to invert the high dimensional BOLD covariance matrix. We investigate the network organization and brain-state dependence of partial covariance-based functional connectivity. Although RSNs are conventionally defined in terms of shared variance, removal of widely shared variance, surprisingly, improved the separation of RSNs in a spring embedded graphical model. This result suggests that pair-wise unique shared variance plays a heretofore unrecognized role in RSN covariance organization. In addition, application of partial correlation to fMRI data acquired in the eyes open vs. eyes closed states revealed focal changes in uniquely shared variance between the thalamus and visual cortices. This result suggests that partial correlation of resting state BOLD time series reflect functional processes in addition to structural connectivity. Copyright © 2015 Elsevier Inc. All rights reserved.

  5. Reduced genetic variance among high fitness individuals: inferring stabilizing selection on male sexual displays in Drosophila serrata.

    PubMed

    Sztepanacz, Jacqueline L; Rundle, Howard D

    2012-10-01

    Directional selection is prevalent in nature, yet phenotypes tend to remain relatively constant, suggesting a limit to trait evolution. However, the genetic basis of this limit is unresolved. Given widespread pleiotropy, opposing selection on a trait may arise from the effects of the underlying alleles on other traits under selection, generating net stabilizing selection on trait genetic variance. These pleiotropic costs of trait exaggeration may arise through any number of other traits, making them hard to detect in phenotypic analyses. Stabilizing selection can be inferred, however, if genetic variance is greater among low- compared to high-fitness individuals. We extend a recently suggested approach to provide a direct test of a difference in genetic variance for a suite of cuticular hydrocarbons (CHCs) in Drosophila serrata. Despite strong directional sexual selection on these traits, genetic variance differed between high- and low-fitness individuals and was greater among the low-fitness males for seven of eight CHCs, significantly more than expected by chance. Univariate tests of a difference in genetic variance were nonsignificant but likely have low power. Our results suggest that further CHC exaggeration in D. serrata in response to sexual selection is limited by pleiotropic costs mediated through other traits. © 2012 The Author(s). Evolution© 2012 The Society for the Study of Evolution.

  6. Variance components of short-term biomarkers of manganese exposure in an inception cohort of welding trainees.

    PubMed

    Baker, Marissa G; Simpson, Christopher D; Sheppard, Lianne; Stover, Bert; Morton, Jackie; Cocker, John; Seixas, Noah

    2015-01-01

    Various biomarkers of exposure have been explored as a way to quantitatively estimate an internal dose of manganese (Mn) exposure, but given the tight regulation of Mn in the body, inter-individual variability in baseline Mn levels, and variability in timing between exposure and uptake into various biological tissues, identification of a valuable and useful biomarker for Mn exposure has been elusive. Thus, a mixed model estimating variance components using restricted maximum likelihood was used to assess the within- and between-subject variance components in whole blood, plasma, and urine (MnB, MnP, and MnU, respectively) in a group of nine newly-exposed apprentice welders, on whom baseline and subsequent longitudinal samples were taken over a three month period. In MnB, the majority of variance was found to be between subjects (94%), while in MnP and MnU the majority of variance was found to be within subjects (79% and 99%, respectively), even when controlling for timing of sample. While blood seemed to exhibit a homeostatic control of Mn, plasma and urine, with the majority of the variance within subjects, did not. Results presented here demonstrate the importance of repeat measure or longitudinal study designs when assessing biomarkers of Mn, and the spurious associations that could result from cross-sectional analyses. Copyright © 2014 Elsevier GmbH. All rights reserved.

  7. Parasitism alters three power laws of scaling in a metazoan community: Taylor’s law, density-mass allometry, and variance-mass allometry

    PubMed Central

    Lagrue, Clément; Poulin, Robert; Cohen, Joel E.

    2015-01-01

    How do the lifestyles (free-living unparasitized, free-living parasitized, and parasitic) of animal species affect major ecological power-law relationships? We investigated this question in metazoan communities in lakes of Otago, New Zealand. In 13,752 samples comprising 1,037,058 organisms, we found that species of different lifestyles differed in taxonomic distribution and body mass and were well described by three power laws: a spatial Taylor’s law (the spatial variance in population density was a power-law function of the spatial mean population density); density-mass allometry (the spatial mean population density was a power-law function of mean body mass); and variance-mass allometry (the spatial variance in population density was a power-law function of mean body mass). To our knowledge, this constitutes the first empirical confirmation of variance-mass allometry for any animal community. We found that the parameter values of all three relationships differed for species with different lifestyles in the same communities. Taylor's law and density-mass allometry accurately predicted the form and parameter values of variance-mass allometry. We conclude that species of different lifestyles in these metazoan communities obeyed the same major ecological power-law relationships but did so with parameters specific to each lifestyle, probably reflecting differences among lifestyles in population dynamics and spatial distribution. PMID:25550506

  8. Precision, Reliability, and Effect Size of Slope Variance in Latent Growth Curve Models: Implications for Statistical Power Analysis

    PubMed Central

    Brandmaier, Andreas M.; von Oertzen, Timo; Ghisletta, Paolo; Lindenberger, Ulman; Hertzog, Christopher

    2018-01-01

    Latent Growth Curve Models (LGCM) have become a standard technique to model change over time. Prediction and explanation of inter-individual differences in change are major goals in lifespan research. The major determinants of statistical power to detect individual differences in change are the magnitude of true inter-individual differences in linear change (LGCM slope variance), design precision, alpha level, and sample size. Here, we show that design precision can be expressed as the inverse of effective error. Effective error is determined by instrument reliability and the temporal arrangement of measurement occasions. However, it also depends on another central LGCM component, the variance of the latent intercept and its covariance with the latent slope. We derive a new reliability index for LGCM slope variance—effective curve reliability (ECR)—by scaling slope variance against effective error. ECR is interpretable as a standardized effect size index. We demonstrate how effective error, ECR, and statistical power for a likelihood ratio test of zero slope variance formally relate to each other and how they function as indices of statistical power. We also provide a computational approach to derive ECR for arbitrary intercept-slope covariance. With practical use cases, we argue for the complementary utility of the proposed indices of a study's sensitivity to detect slope variance when making a priori longitudinal design decisions or communicating study designs. PMID:29755377

  9. Team climate at Antarctic research stations 1996-2000: leadership matters.

    PubMed

    Schmidt, Lacey L; Wood, JoAnna; Lugg, Desmond J

    2004-08-01

    The popular assumption is that extreme environments induce a climate of hostility, incompatibility, and tension by intensifying differences and disagreements among team members. Team members' perceptions of team climate are likely to change over time in an extreme environment, and thus team climate should be considered as a dynamic outcome variable resulting from multiple factors. In order to explore team climate as a dynamic outcome, we explored whether variables at multiple levels of analysis contributed to team climate over time for teams living and working in Antarctica. Data for this study were collected from volunteers involved in Australian National Antarctic Research Expeditions conducted from 1996 to 2000. Multilevel analysis was used to partition and estimate the variance in team climate and to explore factors explaining variance at the group/team, individual, and weekly levels. Most of the variance in perceptions of team climate was at the individual level (57%). Team climate had less variance at the group level (16%) and at the weekly level (26%). Results indicated that perceived leadership effectiveness was significantly related to team climate. Perceived leadership effectiveness accounted for an estimated 77% of the group level variance, which equated to 14% of the overall variance in team climate. Our results suggest that exploring the characteristics and behaviors that constitute effective leadership would contribute to a more complete and useful picture of team climate, as well as guide selection research.

  10. Partial covariance based functional connectivity computation using Ledoit-Wolf covariance regularization

    PubMed Central

    Brier, Matthew R.; Mitra, Anish; McCarthy, John E.; Ances, Beau M.; Snyder, Abraham Z.

    2015-01-01

    Functional connectivity refers to shared signals among brain regions and is typically assessed in a task free state. Functional connectivity commonly is quantified between signal pairs using Pearson correlation. However, resting-state fMRI is a multivariate process exhibiting a complicated covariance structure. Partial covariance assesses the unique variance shared between two brain regions excluding any widely shared variance, hence is appropriate for the analysis of multivariate fMRI datasets. However, calculation of partial covariance requires inversion of the covariance matrix, which, in most functional connectivity studies, is not invertible owing to rank deficiency. Here we apply Ledoit-Wolf shrinkage (L2 regularization) to invert the high dimensional BOLD covariance matrix. We investigate the network organization and brain-state dependence of partial covariance-based functional connectivity. Although RSNs are conventionally defined in terms of shared variance, removal of widely shared variance, surprisingly, improved the separation of RSNs in a spring embedded graphical model. This result suggests that pair-wise unique shared variance plays a heretofore unrecognized role in RSN covariance organization. In addition, application of partial correlation to fMRI data acquired in the eyes open vs. eyes closed states revealed focal changes in uniquely shared variance between the thalamus and visual cortices. This result suggests that partial correlation of resting state BOLD time series reflect functional processes in addition to structural connectivity. PMID:26208872

  11. Parasitism alters three power laws of scaling in a metazoan community: Taylor's law, density-mass allometry, and variance-mass allometry.

    PubMed

    Lagrue, Clément; Poulin, Robert; Cohen, Joel E

    2015-02-10

    How do the lifestyles (free-living unparasitized, free-living parasitized, and parasitic) of animal species affect major ecological power-law relationships? We investigated this question in metazoan communities in lakes of Otago, New Zealand. In 13,752 samples comprising 1,037,058 organisms, we found that species of different lifestyles differed in taxonomic distribution and body mass and were well described by three power laws: a spatial Taylor's law (the spatial variance in population density was a power-law function of the spatial mean population density); density-mass allometry (the spatial mean population density was a power-law function of mean body mass); and variance-mass allometry (the spatial variance in population density was a power-law function of mean body mass). To our knowledge, this constitutes the first empirical confirmation of variance-mass allometry for any animal community. We found that the parameter values of all three relationships differed for species with different lifestyles in the same communities. Taylor's law and density-mass allometry accurately predicted the form and parameter values of variance-mass allometry. We conclude that species of different lifestyles in these metazoan communities obeyed the same major ecological power-law relationships but did so with parameters specific to each lifestyle, probably reflecting differences among lifestyles in population dynamics and spatial distribution.

  12. Comparing the utility of the theory of planned behavior between boys and girls for predicting snack food consumption: implications for practice.

    PubMed

    Branscum, Paul; Sharma, Manoj

    2014-01-01

    The purpose of this study was to use the theory of planned behavior to explain two types of snack food consumption among boys and girls (girls n = 98; boys n = 69), which may have implications for future theory-based health promotion interventions. Between genders, there was a significant difference for calorie-dense/nutrient-poor snacks (p = .002), but no difference for fruit and vegetable snacks. Using stepwise multiple regression, attitudes, perceived behavioral control, and subjective norms accounted for a large amount of the variance of intentions (girls = 43.3%; boys = 55.9%); however, for girls, subjective norms accounted for the most variance, whereas for boys, attitudes accounted for the most variance. Calories from calorie-dense/nutrient-poor snacks and fruit and vegetable snacks were also predicted by intentions. For boys, intentions predicted 6.4% of the variance for fruit and vegetable snacks (p = .03) but was not significant for calorie-dense/nutrient-poor snacks, whereas for girls, intentions predicted 6.0% of the variance for fruit and vegetable snacks (p = .007), and 7.2% of the variance for calorie-dense/nutrient-poor snacks (p = .004). Results suggest that the theory of planned behavior is a useful framework for predicting snack foods among children; however, there are important differences between genders that should be considered in future health promotion interventions.

  13. Analysis of signal-dependent sensor noise on JPEG 2000-compressed Sentinel-2 multi-spectral images

    NASA Astrophysics Data System (ADS)

    Uss, M.; Vozel, B.; Lukin, V.; Chehdi, K.

    2017-10-01

    The processing chain of Sentinel-2 MultiSpectral Instrument (MSI) data involves filtering and compression stages that modify MSI sensor noise. As a result, noise in Sentinel-2 Level-1C data distributed to users becomes processed. We demonstrate that processed noise variance model is bivariate: noise variance depends on image intensity (caused by signal-dependency of photon counting detectors) and signal-to-noise ratio (SNR; caused by filtering/compression). To provide information on processed noise parameters, which is missing in Sentinel-2 metadata, we propose to use blind noise parameter estimation approach. Existing methods are restricted to univariate noise model. Therefore, we propose extension of existing vcNI+fBm blind noise parameter estimation method to multivariate noise model, mvcNI+fBm, and apply it to each band of Sentinel-2A data. Obtained results clearly demonstrate that noise variance is affected by filtering/compression for SNR less than about 15. Processed noise variance is reduced by a factor of 2 - 5 in homogeneous areas as compared to noise variance for high SNR values. Estimate of noise variance model parameters are provided for each Sentinel-2A band. Sentinel-2A MSI Level-1C noise models obtained in this paper could be useful for end users and researchers working in a variety of remote sensing applications.

  14. Examination of Variables That May Affect the Relationship Between Cognition and Functional Status in Individuals with Mild Cognitive Impairment: A Meta-Analysis.

    PubMed

    Mcalister, Courtney; Schmitter-Edgecombe, Maureen; Lamb, Richard

    2016-03-01

    The objective of this meta-analysis was to improve understanding of the heterogeneity in the relationship between cognition and functional status in individuals with mild cognitive impairment (MCI). Demographic, clinical, and methodological moderators were examined. Cognition explained an average of 23% of the variance in functional outcomes. Executive function measures explained the largest amount of variance (37%), whereas global cognitive status and processing speed measures explained the least (20%). Short- and long-delayed memory measures accounted for more variance (35% and 31%) than immediate memory measures (18%), and the relationship between cognition and functional outcomes was stronger when assessed with informant-report (28%) compared with self-report (21%). Demographics, sample characteristics, and type of everyday functioning measures (i.e., questionnaire, performance-based) explained relatively little variance compared with cognition. Executive functioning, particularly measured by Trails B, was a strong predictor of everyday functioning in individuals with MCI. A large proportion of variance remained unexplained by cognition. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  15. Variance-Based Sensitivity Analysis to Support Simulation-Based Design Under Uncertainty

    DOE PAGES

    Opgenoord, Max M. J.; Allaire, Douglas L.; Willcox, Karen E.

    2016-09-12

    Sensitivity analysis plays a critical role in quantifying uncertainty in the design of engineering systems. A variance-based global sensitivity analysis is often used to rank the importance of input factors, based on their contribution to the variance of the output quantity of interest. However, this analysis assumes that all input variability can be reduced to zero, which is typically not the case in a design setting. Distributional sensitivity analysis (DSA) instead treats the uncertainty reduction in the inputs as a random variable, and defines a variance-based sensitivity index function that characterizes the relative contribution to the output variance as amore » function of the amount of uncertainty reduction. This paper develops a computationally efficient implementation for the DSA formulation and extends it to include distributions commonly used in engineering design under uncertainty. Application of the DSA method to the conceptual design of a commercial jetliner demonstrates how the sensitivity analysis provides valuable information to designers and decision-makers on where and how to target uncertainty reduction efforts.« less

  16. Good genes, genetic compatibility and the evolution of polyandry: use of the diallel cross to address competing hypotheses.

    PubMed

    Ivy, T M

    2007-03-01

    Genetic benefits can enhance the fitness of polyandrous females through the high intrinsic genetic quality of females' mates or through the interaction between female and male genes. I used a full diallel cross, a quantitative genetics design that involves all possible crosses among a set of genetically homogeneous lines, to determine the mechanism through which polyandrous female decorated crickets (Gryllodes sigillatus) obtain genetic benefits. I measured several traits related to fitness and partitioned the phenotypic variance into components representing the contribution of additive genetic variance ('good genes'), nonadditive genetic variance (genetic compatibility), as well as maternal and paternal effects. The results reveal a significant variance attributable to both nonadditive and additive sources in the measured traits, and their influence depended on which trait was considered. The lack of congruence in sources of phenotypic variance among these fitness-related traits suggests that the evolution and maintenance of polyandry are unlikely to have resulted from one selective influence, but rather are the result of the collective effects of a number of factors.

  17. Variance-Based Sensitivity Analysis to Support Simulation-Based Design Under Uncertainty

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

    Opgenoord, Max M. J.; Allaire, Douglas L.; Willcox, Karen E.

    Sensitivity analysis plays a critical role in quantifying uncertainty in the design of engineering systems. A variance-based global sensitivity analysis is often used to rank the importance of input factors, based on their contribution to the variance of the output quantity of interest. However, this analysis assumes that all input variability can be reduced to zero, which is typically not the case in a design setting. Distributional sensitivity analysis (DSA) instead treats the uncertainty reduction in the inputs as a random variable, and defines a variance-based sensitivity index function that characterizes the relative contribution to the output variance as amore » function of the amount of uncertainty reduction. This paper develops a computationally efficient implementation for the DSA formulation and extends it to include distributions commonly used in engineering design under uncertainty. Application of the DSA method to the conceptual design of a commercial jetliner demonstrates how the sensitivity analysis provides valuable information to designers and decision-makers on where and how to target uncertainty reduction efforts.« less

  18. Analysis of overdispersed count data: application to the Human Papillomavirus Infection in Men (HIM) Study.

    PubMed

    Lee, J-H; Han, G; Fulp, W J; Giuliano, A R

    2012-06-01

    The Poisson model can be applied to the count of events occurring within a specific time period. The main feature of the Poisson model is the assumption that the mean and variance of the count data are equal. However, this equal mean-variance relationship rarely occurs in observational data. In most cases, the observed variance is larger than the assumed variance, which is called overdispersion. Further, when the observed data involve excessive zero counts, the problem of overdispersion results in underestimating the variance of the estimated parameter, and thus produces a misleading conclusion. We illustrated the use of four models for overdispersed count data that may be attributed to excessive zeros. These are Poisson, negative binomial, zero-inflated Poisson and zero-inflated negative binomial models. The example data in this article deal with the number of incidents involving human papillomavirus infection. The four models resulted in differing statistical inferences. The Poisson model, which is widely used in epidemiology research, underestimated the standard errors and overstated the significance of some covariates.

  19. Are stock prices too volatile to be justified by the dividend discount model?

    NASA Astrophysics Data System (ADS)

    Akdeniz, Levent; Salih, Aslıhan Altay; Ok, Süleyman Tuluğ

    2007-03-01

    This study investigates excess stock price volatility using the variance bound framework of LeRoy and Porter [The present-value relation: tests based on implied variance bounds, Econometrica 49 (1981) 555-574] and of Shiller [Do stock prices move too much to be justified by subsequent changes in dividends? Am. Econ. Rev. 71 (1981) 421-436.]. The conditional variance bound relationship is examined using cross-sectional data simulated from the general equilibrium asset pricing model of Brock [Asset prices in a production economy, in: J.J. McCall (Ed.), The Economics of Information and Uncertainty, University of Chicago Press, Chicago (for N.B.E.R.), 1982]. Results show that the conditional variance bounds hold, hence, our hypothesis of the validity of the dividend discount model cannot be rejected. Moreover, in our setting, markets are efficient and stock prices are neither affected by herd psychology nor by the outcome of noise trading by naive investors; thus, we are able to control for market efficiency. Consequently, we show that one cannot infer any conclusions about market efficiency from the unconditional variance bounds tests.

  20. Non-stationary internal tides observed with satellite altimetry

    NASA Astrophysics Data System (ADS)

    Ray, R. D.; Zaron, E. D.

    2011-09-01

    Temporal variability of the internal tide is inferred from a 17-year combined record of Topex/Poseidon and Jason satellite altimeters. A global sampling of along-track sea-surface height wavenumber spectra finds that non-stationary variance is generally 25% or less of the average variance at wavenumbers characteristic of mode-1 tidal internal waves. With some exceptions the non-stationary variance does not exceed 0.25 cm2. The mode-2 signal, where detectable, contains a larger fraction of non-stationary variance, typically 50% or more. Temporal subsetting of the data reveals interannual variability barely significant compared with tidal estimation error from 3-year records. Comparison of summer vs. winter conditions shows only one region of noteworthy seasonal changes, the northern South China Sea. Implications for the anticipated SWOT altimeter mission are briefly discussed.

  1. Estimation of bias and variance of measurements made from tomography scans

    NASA Astrophysics Data System (ADS)

    Bradley, Robert S.

    2016-09-01

    Tomographic imaging modalities are being increasingly used to quantify internal characteristics of objects for a wide range of applications, from medical imaging to materials science research. However, such measurements are typically presented without an assessment being made of their associated variance or confidence interval. In particular, noise in raw scan data places a fundamental lower limit on the variance and bias of measurements made on the reconstructed 3D volumes. In this paper, the simulation-extrapolation technique, which was originally developed for statistical regression, is adapted to estimate the bias and variance for measurements made from a single scan. The application to x-ray tomography is considered in detail and it is demonstrated that the technique can also allow the robustness of automatic segmentation strategies to be compared.

  2. Fuel cell stack monitoring and system control

    DOEpatents

    Keskula, Donald H.; Doan, Tien M.; Clingerman, Bruce J.

    2005-01-25

    A control method for monitoring a fuel cell stack in a fuel cell system in which the actual voltage and actual current from the fuel cell stack are monitored. A preestablished relationship between voltage and current over the operating range of the fuel cell is established. A variance value between the actual measured voltage and the expected voltage magnitude for a given actual measured current is calculated and compared with a predetermined allowable variance. An output is generated if the calculated variance value exceeds the predetermined variance. The predetermined voltage-current for the fuel cell is symbolized as a polarization curve at given operating conditions of the fuel cell. Other polarization curves may be generated and used for fuel cell stack monitoring based on different operating pressures, temperatures, hydrogen quantities.

  3. On the design of classifiers for crop inventories

    NASA Technical Reports Server (NTRS)

    Heydorn, R. P.; Takacs, H. C.

    1986-01-01

    Crop proportion estimators that use classifications of satellite data to correct, in an additive way, a given estimate acquired from ground observations are discussed. A linear version of these estimators is optimal, in terms of minimum variance, when the regression of the ground observations onto the satellite observations in linear. When this regression is not linear, but the reverse regression (satellite observations onto ground observations) is linear, the estimator is suboptimal but still has certain appealing variance properties. In this paper expressions are derived for those regressions which relate the intercepts and slopes to conditional classification probabilities. These expressions are then used to discuss the question of classifier designs that can lead to low-variance crop proportion estimates. Variance expressions for these estimates in terms of classifier omission and commission errors are also derived.

  4. Non-Stationary Internal Tides Observed with Satellite Altimetry

    NASA Technical Reports Server (NTRS)

    Ray, Richard D.; Zaron, E. D.

    2011-01-01

    Temporal variability of the internal tide is inferred from a 17-year combined record of Topex/Poseidon and Jason satellite altimeters. A global sampling of along-track sea-surface height wavenumber spectra finds that non-stationary variance is generally 25% or less of the average variance at wavenumbers characteristic of mode-l tidal internal waves. With some exceptions the non-stationary variance does not exceed 0.25 sq cm. The mode-2 signal, where detectable, contains a larger fraction of non-stationary variance, typically 50% or more. Temporal subsetting of the data reveals interannual variability barely significant compared with tidal estimation error from 3-year records. Comparison of summer vs. winter conditions shows only one region of noteworthy seasonal changes, the northern South China Sea. Implications for the anticipated SWOT altimeter mission are briefly discussed.

  5. Sampling in freshwater environments: suspended particle traps and variability in the final data.

    PubMed

    Barbizzi, Sabrina; Pati, Alessandra

    2008-11-01

    This paper reports one practical method to estimate the measurement uncertainty including sampling, derived by the approach implemented by Ramsey for soil investigations. The methodology has been applied to estimate the measurements uncertainty (sampling and analyses) of (137)Cs activity concentration (Bq kg(-1)) and total carbon content (%) in suspended particle sampling in a freshwater ecosystem. Uncertainty estimates for between locations, sampling and analysis components have been evaluated. For the considered measurands, the relative expanded measurement uncertainties are 12.3% for (137)Cs and 4.5% for total carbon. For (137)Cs, the measurement (sampling+analysis) variance gives the major contribution to the total variance, while for total carbon the spatial variance is the dominant contributor to the total variance. The limitations and advantages of this basic method are discussed.

  6. IDENTIFYING GENETIC ASSOCIATIONS WITH VARIABILITY IN METABOLIC HEALTH AND BLOOD COUNT LABORATORY VALUES: DIVING INTO THE QUANTITATIVE TRAITS BY LEVERAGING LONGITUDINAL DATA FROM AN EHR.

    PubMed

    Verma, Shefali S; Lucas, Anastasia M; Lavage, Daniel R; Leader, Joseph B; Metpally, Raghu; Krishnamurthy, Sarathbabu; Dewey, Frederick; Borecki, Ingrid; Lopez, Alexander; Overton, John; Penn, John; Reid, Jeffrey; Pendergrass, Sarah A; Breitwieser, Gerda; Ritchie, Marylyn D

    2017-01-01

    A wide range of patient health data is recorded in Electronic Health Records (EHR). This data includes diagnosis, surgical procedures, clinical laboratory measurements, and medication information. Together this information reflects the patient's medical history. Many studies have efficiently used this data from the EHR to find associations that are clinically relevant, either by utilizing International Classification of Diseases, version 9 (ICD-9) codes or laboratory measurements, or by designing phenotype algorithms to extract case and control status with accuracy from the EHR. Here we developed a strategy to utilize longitudinal quantitative trait data from the EHR at Geisinger Health System focusing on outpatient metabolic and complete blood panel data as a starting point. Comprehensive Metabolic Panel (CMP) as well as Complete Blood Counts (CBC) are parts of routine care and provide a comprehensive picture from high level screening of patients' overall health and disease. We randomly split our data into two datasets to allow for discovery and replication. We first conducted a genome-wide association study (GWAS) with median values of 25 different clinical laboratory measurements to identify variants from Human Omni Express Exome beadchip data that are associated with these measurements. We identified 687 variants that associated and replicated with the tested clinical measurements at p<5×10-08. Since longitudinal data from the EHR provides a record of a patient's medical history, we utilized this information to further investigate the ICD-9 codes that might be associated with differences in variability of the measurements in the longitudinal dataset. We identified low and high variance patients by looking at changes within their individual longitudinal EHR laboratory results for each of the 25 clinical lab values (thus creating 50 groups - a high variance and a low variance for each lab variable). We then performed a PheWAS analysis with ICD-9 diagnosis codes, separately in the high variance group and the low variance group for each lab variable. We found 717 PheWAS associations that replicated at a p-value less than 0.001. Next, we evaluated the results of this study by comparing the association results between the high and low variance groups. For example, we found 39 SNPs (in multiple genes) associated with ICD-9 250.01 (Type-I diabetes) in patients with high variance of plasma glucose levels, but not in patients with low variance in plasma glucose levels. Another example is the association of 4 SNPs in UMOD with chronic kidney disease in patients with high variance for aspartate aminotransferase (discovery p-value: 8.71×10-09 and replication p-value: 2.03×10-06). In general, we see a pattern of many more statistically significant associations from patients with high variance in the quantitative lab variables, in comparison with the low variance group across all of the 25 laboratory measurements. This study is one of the first of its kind to utilize quantitative trait variance from longitudinal laboratory data to find associations among genetic variants and clinical phenotypes obtained from an EHR, integrating laboratory values and diagnosis codes to understand the genetic complexities of common diseases.

  7. Job Tasks as Determinants of Thoracic Aerosol Exposure in the Cement Production Industry.

    PubMed

    Notø, Hilde; Nordby, Karl-Christian; Skare, Øivind; Eduard, Wijnand

    2017-12-15

    The aims of this study were to identify important determinants and investigate the variance components of thoracic aerosol exposure for the workers in the production departments of European cement plants. Personal thoracic aerosol measurements and questionnaire information (Notø et al., 2015) were the basis for this study. Determinants categorized in three levels were selected to describe the exposure relationships separately for the job types production, cleaning, maintenance, foreman, administration, laboratory, and other jobs by linear mixed models. The influence of plant and job determinants on variance components were explored separately and also combined in full models (plant&job) against models with no determinants (null). The best mixed models (best) describing the exposure for each job type were selected by the lowest Akaike information criterion (AIC; Akaike, 1974) after running all possible combination of the determinants. Tasks that significantly increased the thoracic aerosol exposure above the mean level for production workers were: packing and shipping, raw meal, cement and filter cleaning, and de-clogging of the cyclones. For maintenance workers, time spent with welding and dismantling before repair work increased the exposure while time with electrical maintenance and oiling decreased the exposure. Administration work decreased the exposure among foremen. A subjective tidiness factor scored by the research team explained up to a 3-fold (cleaners) variation in thoracic aerosol levels. Within-worker (WW) variance contained a major part of the total variance (35-58%) for all job types. Job determinants had little influence on the WW variance (0-4% reduction), some influence on the between-plant (BP) variance (from 5% to 39% reduction for production, maintenance, and other jobs respectively but an 79% increase for foremen) and a substantial influence on the between-worker within-plant variance (30-96% for production, foremen, and other workers). Plant determinants had little influence on the WW variance (0-2% reduction), some influence on the between-worker variance (0-1% reduction and 8% increase), and considerable influence on the BP variance (36-58% reduction) compared to the null models. Some job tasks contribute to low levels of thoracic aerosol exposure and others to higher exposure among cement plant workers. Thus, job task may predict exposure in this industry. Dust control measures in the packing and shipping departments and in the areas of raw meal and cement handling could contribute substantially to reduce the exposure levels. Rotation between low and higher exposed tasks may contribute to equalize the exposure levels between high and low exposed workers as a temporary solution before more permanent dust reduction measures is implemented. A tidy plant may reduce the overall exposure for almost all workers no matter of job type. © The Author 2017. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.

  8. On the impact of relatedness on SNP association analysis.

    PubMed

    Gross, Arnd; Tönjes, Anke; Scholz, Markus

    2017-12-06

    When testing for SNP (single nucleotide polymorphism) associations in related individuals, observations are not independent. Simple linear regression assuming independent normally distributed residuals results in an increased type I error and the power of the test is also affected in a more complicate manner. Inflation of type I error is often successfully corrected by genomic control. However, this reduces the power of the test when relatedness is of concern. In the present paper, we derive explicit formulae to investigate how heritability and strength of relatedness contribute to variance inflation of the effect estimate of the linear model. Further, we study the consequences of variance inflation on hypothesis testing and compare the results with those of genomic control correction. We apply the developed theory to the publicly available HapMap trio data (N=129), the Sorbs (a self-contained population with N=977 characterised by a cryptic relatedness structure) and synthetic family studies with different sample sizes (ranging from N=129 to N=999) and different degrees of relatedness. We derive explicit and easily to apply approximation formulae to estimate the impact of relatedness on the variance of the effect estimate of the linear regression model. Variance inflation increases with increasing heritability. Relatedness structure also impacts the degree of variance inflation as shown for example family structures. Variance inflation is smallest for HapMap trios, followed by a synthetic family study corresponding to the trio data but with larger sample size than HapMap. Next strongest inflation is observed for the Sorbs, and finally, for a synthetic family study with a more extreme relatedness structure but with similar sample size as the Sorbs. Type I error increases rapidly with increasing inflation. However, for smaller significance levels, power increases with increasing inflation while the opposite holds for larger significance levels. When genomic control is applied, type I error is preserved while power decreases rapidly with increasing variance inflation. Stronger relatedness as well as higher heritability result in increased variance of the effect estimate of simple linear regression analysis. While type I error rates are generally inflated, the behaviour of power is more complex since power can be increased or reduced in dependence on relatedness and the heritability of the phenotype. Genomic control cannot be recommended to deal with inflation due to relatedness. Although it preserves type I error, the loss in power can be considerable. We provide a simple formula for estimating variance inflation given the relatedness structure and the heritability of a trait of interest. As a rule of thumb, variance inflation below 1.05 does not require correction and simple linear regression analysis is still appropriate.

  9. Means and Variances without Calculus

    ERIC Educational Resources Information Center

    Kinney, John J.

    2005-01-01

    This article gives a method of finding discrete approximations to continuous probability density functions and shows examples of its use, allowing students without calculus access to the calculation of means and variances.

  10. Advanced Communication Processing Techniques Held in Ruidoso, New Mexico on 14-17 May 1989

    DTIC Science & Technology

    1990-01-01

    Criteria: * Prob. of Detection and False Alarm * Variances of Parameter Estimators * Prob. of Correct Classiflcsation and Rejection 0 2 In the exposure...couple of criteria. The tell? [LAUGHTER] If it was anybody else, I standard Neyman-Pearson approach for de- wouldn’t say .... tection, variances for... VARIANCE AISJ11T UPPER AND0 LOWER PMIOUIESOES FEATUE---OELET!U FETUA1E----WW-4A140 TIME SEOLIENTIAL CORRELATION FEATUE -$-ESTIMATED INA FEATURE-ID--LOW

  11. Distribution of lod scores in oligogenic linkage analysis.

    PubMed

    Williams, J T; North, K E; Martin, L J; Comuzzie, A G; Göring, H H; Blangero, J

    2001-01-01

    In variance component oligogenic linkage analysis it can happen that the residual additive genetic variance bounds to zero when estimating the effect of the ith quantitative trait locus. Using quantitative trait Q1 from the Genetic Analysis Workshop 12 simulated general population data, we compare the observed lod scores from oligogenic linkage analysis with the empirical lod score distribution under a null model of no linkage. We find that zero residual additive genetic variance in the null model alters the usual distribution of the likelihood-ratio statistic.

  12. New Variance-Reducing Methods for the PSD Analysis of Large Optical Surfaces

    NASA Technical Reports Server (NTRS)

    Sidick, Erkin

    2010-01-01

    Edge data of a measured surface map of a circular optic result in large variance or "spectral leakage" behavior in the corresponding Power Spectral Density (PSD) data. In this paper we present two new, alternative methods for reducing such variance in the PSD data by replacing the zeros outside the circular area of a surface map by non-zero values either obtained from a PSD fit (method 1) or taken from the inside of the circular area (method 2).

  13. The Effects of Laser Phase Noise on Laser Radar Performance

    DTIC Science & Technology

    1992-12-01

    Laboratory 5. Figure 3 shows Allan variance plots of the above ultrastable C02 laser which has an open Fabry - Perot cavity 5. The open and solid circles...the same measurement time -r) by more than 10 dB. Therefore, the root Allan variance for the Fabry - Perot cavity ultrastable C02 laser can be...variance so that the SSB phase noise for the Fabry - Perot cavity ultrastable CO 2 laser is about 20 dB (because of the squaring operation) below that of the

  14. Logistic and Multiple Regression: A Two-Pronged Approach to Accurately Estimate Cost Growth in Major DoD Weapon Systems

    DTIC Science & Technology

    2004-03-01

    Breusch - Pagan test for constant variance of the residuals. Using Microsoft Excel® we calculate a p-value of 0.841237. This high p-value, which is above...our alpha of 0.05, indicates that our residuals indeed pass the Breusch - Pagan test for constant variance. In addition to the assumption tests , we...Wilk Test for Normality – Support (Reduced) Model (OLS) Finally, we perform a Breusch - Pagan test for constant variance of the residuals. Using

  15. The effects of r- and K-selection on components of variance for two quantitative traits.

    PubMed

    Long, T; Long, G

    1974-03-01

    The genetic and environmental components of variance for two quantitative characters were measured in the descendants of Drosophila melanogaster populations which had been grown for several generations at densities of 100, 200, 300, and 400 eggs per vial. Populations subject to intermediate densities had a greater proportion of phenotypic variance available for selection than populations from either extreme. Selection on either character would be least effective under pure r-selection, a frequent attribute of selection programs.

  16. Sensitivity analysis of simulated SOA loadings using a variance-based statistical approach: SENSITIVITY ANALYSIS OF SOA

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

    Shrivastava, Manish; Zhao, Chun; Easter, Richard C.

    We investigate the sensitivity of secondary organic aerosol (SOA) loadings simulated by a regional chemical transport model to 7 selected tunable model parameters: 4 involving emissions of anthropogenic and biogenic volatile organic compounds, anthropogenic semi-volatile and intermediate volatility organics (SIVOCs), and NOx, 2 involving dry deposition of SOA precursor gases, and one involving particle-phase transformation of SOA to low volatility. We adopt a quasi-Monte Carlo sampling approach to effectively sample the high-dimensional parameter space, and perform a 250 member ensemble of simulations using a regional model, accounting for some of the latest advances in SOA treatments based on our recentmore » work. We then conduct a variance-based sensitivity analysis using the generalized linear model method to study the responses of simulated SOA loadings to the tunable parameters. Analysis of SOA variance from all 250 simulations shows that the volatility transformation parameter, which controls whether particle-phase transformation of SOA from semi-volatile SOA to non-volatile is on or off, is the dominant contributor to variance of simulated surface-level daytime SOA (65% domain average contribution). We also split the simulations into 2 subsets of 125 each, depending on whether the volatility transformation is turned on/off. For each subset, the SOA variances are dominated by the parameters involving biogenic VOC and anthropogenic SIVOC emissions. Furthermore, biogenic VOC emissions have a larger contribution to SOA variance when the SOA transformation to non-volatile is on, while anthropogenic SIVOC emissions have a larger contribution when the transformation is off. NOx contributes less than 4.3% to SOA variance, and this low contribution is mainly attributed to dominance of intermediate to high NOx conditions throughout the simulated domain. The two parameters related to dry deposition of SOA precursor gases also have very low contributions to SOA variance. This study highlights the large sensitivity of SOA loadings to the particle-phase transformation of SOA volatility, which is neglected in most previous models.« less

  17. 42 CFR 456.524 - Notification of Administrator's action and duration of variance.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ..., DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL ASSISTANCE PROGRAMS UTILIZATION CONTROL Utilization Review Plans: FFP, Waivers, and Variances for Hospitals and Mental Hospitals Ur Plan: Remote...

  18. Importance Sampling Variance Reduction in GRESS ATMOSIM

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

    Wakeford, Daniel Tyler

    This document is intended to introduce the importance sampling method of variance reduction to a Geant4 user for application to neutral particle Monte Carlo transport through the atmosphere, as implemented in GRESS ATMOSIM.

  19. 40 CFR 264.97 - General ground-water monitoring requirements.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... paragraph (i) of this section. (1) A parametric analysis of variance (ANOVA) followed by multiple... mean levels for each constituent. (2) An analysis of variance (ANOVA) based on ranks followed by...

  20. 29 CFR 4204.22 - PBGC action on requests.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... MULTIEMPLOYER PLANS VARIANCES FOR SALE OF ASSETS Procedures for Individual and Class Variances or Exemptions... the risk of financial loss to the plan. (b) Notice of pendency of request. As soon as practicable...

  1. Technical Note: Introduction of variance component analysis to setup error analysis in radiotherapy

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

    Matsuo, Yukinori, E-mail: ymatsuo@kuhp.kyoto-u.ac.

    Purpose: The purpose of this technical note is to introduce variance component analysis to the estimation of systematic and random components in setup error of radiotherapy. Methods: Balanced data according to the one-factor random effect model were assumed. Results: Analysis-of-variance (ANOVA)-based computation was applied to estimate the values and their confidence intervals (CIs) for systematic and random errors and the population mean of setup errors. The conventional method overestimates systematic error, especially in hypofractionated settings. The CI for systematic error becomes much wider than that for random error. The ANOVA-based estimation can be extended to a multifactor model considering multiplemore » causes of setup errors (e.g., interpatient, interfraction, and intrafraction). Conclusions: Variance component analysis may lead to novel applications to setup error analysis in radiotherapy.« less

  2. Discrete velocity computations with stochastic variance reduction of the Boltzmann equation for gas mixtures

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

    Clarke, Peter; Varghese, Philip; Goldstein, David

    We extend a variance reduced discrete velocity method developed at UT Austin [1, 2] to gas mixtures with large mass ratios and flows with trace species. The mixture is stored as a collection of independent velocity distribution functions, each with a unique grid in velocity space. Different collision types (A-A, A-B, B-B, etc.) are treated independently, and the variance reduction scheme is formulated with different equilibrium functions for each separate collision type. The individual treatment of species enables increased focus on species important to the physics of the flow, even if the important species are present in trace amounts. Themore » method is verified through comparisons to Direct Simulation Monte Carlo computations and the computational workload per time step is investigated for the variance reduced method.« less

  3. Evidence of Convergent and Discriminant Validity of Child, Teacher, and Peer Reports of Teacher-Student Support

    PubMed Central

    Li, Yan; Hughes, Jan N.; Kwok, Oi-man; Hsu, Hsien-Yuan

    2012-01-01

    This study investigated the construct validity of measures of teacher-student support in a sample of 709 ethnically diverse second and third grade academically at-risk students. Confirmatory factor analysis investigated the convergent and discriminant validities of teacher, child, and peer reports of teacher-student support and child conduct problems. Results supported the convergent and discriminant validity of scores on the measures. Peer reports accounted for the largest proportion of trait variance and non-significant method variance. Child reports accounted for the smallest proportion of trait variance and the largest method variance. A model with two latent factors provided a better fit to the data than a model with one factor, providing further evidence of the discriminant validity of measures of teacher-student support. Implications for research, policy, and practice are discussed. PMID:21767024

  4. Active commuting patterns at a large, midwestern college campus.

    PubMed

    Bopp, Melissa; Kaczynski, Andrew; Wittman, Pamela

    2011-01-01

    To understand patterns and influences on active commuting (AC) behavior. Students and faculty/staff at a university campus. In April-May 2008, respondents answered an online survey about mode of travel to campus and influences on commuting decisions. Hierarchical regression analyses predicted variance in walking and biking using sets of demographic, psychological, and environmental variables. Of 898 respondents, 55.7% were female, 457 were students (50.4%). Students reported more AC than faculty/staff. For students, the models explained 36.2% and 29.1% of the variance in walking and biking, respectively. Among faculty/staff, the models explained 45% and 25.8% of the variance in walking and biking. For all models, the psychological set explained the greatest amount of variance. With current economic and ecological concerns, AC should be considered a behavior to target for campus health promotion.

  5. Factors controlling degree of correlation between ISEE 1 and ISEE 3 interplanetary magnetic field measurements

    NASA Technical Reports Server (NTRS)

    Crooker, N. U.; Siscoe, G. L.; Russell, C. T.; Smith, E. J.

    1982-01-01

    Correlation variability between ISEE 1 and 3 IMF measurements is investigated, and factors governing the variability are discussed. About 200 two-hour periods when correlation was good, and 200 when correlation was poor, are examined, and both IMF variance and spacecraft separation distance in the plane perpendicular to the earth-sun line exert substantial control. The scale size of magnetic features is larger when variance is high, and abrupt changes in the correlation coefficient from poor to good or good to poor in adjacent two-hour intervals appear to be governed by the sense of change of IMF variance and vice versa. During periods of low variance, good correlations are most likely to occur when the distance between ISEE 1 and 3 perpendicular to the IMF is less than 20 earth radii.

  6. Characterization of turbulence stability through the identification of multifractional Brownian motions

    NASA Astrophysics Data System (ADS)

    Lee, K. C.

    2013-02-01

    Multifractional Brownian motions have become popular as flexible models in describing real-life signals of high-frequency features in geoscience, microeconomics, and turbulence, to name a few. The time-changing Hurst exponent, which describes regularity levels depending on time measurements, and variance, which relates to an energy level, are two parameters that characterize multifractional Brownian motions. This research suggests a combined method of estimating the time-changing Hurst exponent and variance using the local variation of sampled paths of signals. The method consists of two phases: initially estimating global variance and then accurately estimating the time-changing Hurst exponent. A simulation study shows its performance in estimation of the parameters. The proposed method is applied to characterization of atmospheric stability in which descriptive statistics from the estimated time-changing Hurst exponent and variance classify stable atmosphere flows from unstable ones.

  7. Genetic and environmental influences on blood pressure variability: a study in twins.

    PubMed

    Xu, Xiaojing; Ding, Xiuhua; Zhang, Xinyan; Su, Shaoyong; Treiber, Frank A; Vlietinck, Robert; Fagard, Robert; Derom, Catherine; Gielen, Marij; Loos, Ruth J F; Snieder, Harold; Wang, Xiaoling

    2013-04-01

    Blood pressure variability (BPV) and its reduction in response to antihypertensive treatment are predictors of clinical outcomes; however, little is known about its heritability. In this study, we examined the relative influence of genetic and environmental sources of variance of BPV and the extent to which it may depend on race or sex in young twins. Twins were enrolled from two studies. One study included 703 white twins (308 pairs and 87 singletons) aged 18-34 years, whereas another study included 242 white twins (108 pairs and 26 singletons) and 188 black twins (79 pairs and 30 singletons) aged 12-30 years. BPV was calculated from 24-h ambulatory blood pressure recording. Twin modeling showed similar results in the separate analysis in both twin studies and in the meta-analysis. Familial aggregation was identified for SBP variability (SBPV) and DBP variability (DBPV) with genetic factors and common environmental factors together accounting for 18-40% and 23-31% of the total variance of SBPV and DBPV, respectively. Unique environmental factors were the largest contributor explaining up to 82-77% of the total variance of SBPV and DBPV. No sex or race difference in BPV variance components was observed. The results remained the same after adjustment for 24-h blood pressure levels. The variance in BPV is predominantly determined by unique environment in youth and young adults, although familial aggregation due to additive genetic and/or common environment influences was also identified explaining about 25% of the variance in BPV.

  8. Movement trajectory smoothness is not associated with the endpoint accuracy of rapid multi-joint arm movements in young and older adults

    PubMed Central

    Poston, Brach; Van Gemmert, Arend W.A.; Sharma, Siddharth; Chakrabarti, Somesh; Zavaremi, Shahrzad H.; Stelmach, George

    2013-01-01

    The minimum variance theory proposes that motor commands are corrupted by signal-dependent noise and smooth trajectories with low noise levels are selected to minimize endpoint error and endpoint variability. The purpose of the study was to determine the contribution of trajectory smoothness to the endpoint accuracy and endpoint variability of rapid multi-joint arm movements. Young and older adults performed arm movements (4 blocks of 25 trials) as fast and as accurately as possible to a target with the right (dominant) arm. Endpoint accuracy and endpoint variability along with trajectory smoothness and error were quantified for each block of trials. Endpoint error and endpoint variance were greater in older adults compared with young adults, but decreased at a similar rate with practice for the two age groups. The greater endpoint error and endpoint variance exhibited by older adults were primarily due to impairments in movement extent control and not movement direction control. The normalized jerk was similar for the two age groups, but was not strongly associated with endpoint error or endpoint variance for either group. However, endpoint variance was strongly associated with endpoint error for both the young and older adults. Finally, trajectory error was similar for both groups and was weakly associated with endpoint error for the older adults. The findings are not consistent with the predictions of the minimum variance theory, but support and extend previous observations that movement trajectories and endpoints are planned independently. PMID:23584101

  9. Determining the bias and variance of a deterministic finger-tracking algorithm.

    PubMed

    Morash, Valerie S; van der Velden, Bas H M

    2016-06-01

    Finger tracking has the potential to expand haptic research and applications, as eye tracking has done in vision research. In research applications, it is desirable to know the bias and variance associated with a finger-tracking method. However, assessing the bias and variance of a deterministic method is not straightforward. Multiple measurements of the same finger position data will not produce different results, implying zero variance. Here, we present a method of assessing deterministic finger-tracking variance and bias through comparison to a non-deterministic measure. A proof-of-concept is presented using a video-based finger-tracking algorithm developed for the specific purpose of tracking participant fingers during a psychological research study. The algorithm uses ridge detection on videos of the participant's hand, and estimates the location of the right index fingertip. The algorithm was evaluated using data from four participants, who explored tactile maps using only their right index finger and all right-hand fingers. The algorithm identified the index fingertip in 99.78 % of one-finger video frames and 97.55 % of five-finger video frames. Although the algorithm produced slightly biased and more dispersed estimates relative to a human coder, these differences (x=0.08 cm, y=0.04 cm) and standard deviations (σ x =0.16 cm, σ y =0.21 cm) were small compared to the size of a fingertip (1.5-2.0 cm). Some example finger-tracking results are provided where corrections are made using the bias and variance estimates.

  10. Factors influencing heterogeneity of radiation-induced DNA-damage measured by the alkaline comet assay.

    PubMed

    Seidel, Clemens; Lautenschläger, Christine; Dunst, Jürgen; Müller, Arndt-Christian

    2012-04-20

    To investigate whether different conditions of DNA structure and radiation treatment could modify heterogeneity of response. Additionally to study variance as a potential parameter of heterogeneity for radiosensitivity testing. Two-hundred leukocytes per sample of healthy donors were split into four groups. I: Intact chromatin structure; II: Nucleoids of histone-depleted DNA; III: Nucleoids of histone-depleted DNA with 90 mM DMSO as antioxidant. Response to single (I-III) and twice (IV) irradiation with 4 Gy and repair kinetics were evaluated using %Tail-DNA. Heterogeneity of DNA damage was determined by calculation of variance of DNA-damage (V) and mean variance (Mvar), mutual comparisons were done by one-way analysis of variance (ANOVA). Heterogeneity of initial DNA-damage (I, 0 min repair) increased without histones (II). Absence of histones was balanced by addition of antioxidants (III). Repair reduced heterogeneity of all samples (with and without irradiation). However double irradiation plus repair led to a higher level of heterogeneity distinguishable from single irradiation and repair in intact cells. Increase of mean DNA damage was associated with a similarly elevated variance of DNA damage (r = +0.88). Heterogeneity of DNA-damage can be modified by histone level, antioxidant concentration, repair and radiation dose and was positively correlated with DNA damage. Experimental conditions might be optimized by reducing scatter of comet assay data by repair and antioxidants, potentially allowing better discrimination of small differences. Amount of heterogeneity measured by variance might be an additional useful parameter to characterize radiosensitivity.

  11. Sample size calculation in cost-effectiveness cluster randomized trials: optimal and maximin approaches.

    PubMed

    Manju, Md Abu; Candel, Math J J M; Berger, Martijn P F

    2014-07-10

    In this paper, the optimal sample sizes at the cluster and person levels for each of two treatment arms are obtained for cluster randomized trials where the cost-effectiveness of treatments on a continuous scale is studied. The optimal sample sizes maximize the efficiency or power for a given budget or minimize the budget for a given efficiency or power. Optimal sample sizes require information on the intra-cluster correlations (ICCs) for effects and costs, the correlations between costs and effects at individual and cluster levels, the ratio of the variance of effects translated into costs to the variance of the costs (the variance ratio), sampling and measuring costs, and the budget. When planning, a study information on the model parameters usually is not available. To overcome this local optimality problem, the current paper also presents maximin sample sizes. The maximin sample sizes turn out to be rather robust against misspecifying the correlation between costs and effects at the cluster and individual levels but may lose much efficiency when misspecifying the variance ratio. The robustness of the maximin sample sizes against misspecifying the ICCs depends on the variance ratio. The maximin sample sizes are robust under misspecification of the ICC for costs for realistic values of the variance ratio greater than one but not robust under misspecification of the ICC for effects. Finally, we show how to calculate optimal or maximin sample sizes that yield sufficient power for a test on the cost-effectiveness of an intervention.

  12. Are prescription drug insurance choices consistent with expected utility theory?

    PubMed

    Bundorf, M Kate; Mata, Rui; Schoenbaum, Michael; Bhattacharya, Jay

    2013-09-01

    To determine the extent to which people make choices inconsistent with expected utility theory when choosing among prescription drug insurance plans and whether tabular or graphical presentation format influences the consistency of their choices. Members of an Internet-enabled panel chose between two Medicare prescription drug plans. The "low variance" plan required higher out-of-pocket payments for the drugs respondents usually took but lower out-of-pocket payments for the drugs they might need if they developed a new health condition than the "high variance" plan. The probability of a change in health varied within subjects and the presentation format (text vs. graphical) and the affective salience of the clinical condition (abstract vs. risk related to specific clinical condition) varied between subjects. Respondents were classified based on whether they consistently chose either the low or high variance plan. Logistic regression models were estimated to examine the relationship between decision outcomes and task characteristics. The majority of respondents consistently chose either the low or high variance plan, consistent with expected utility theory. Half of respondents consistently chose the low variance plan. Respondents were less likely to make discrepant choices when information was presented in graphical format. Many people, although not all, make choices consistent with expected utility theory when they have information on differences among plans in the variance of out-of-pocket spending. Medicare beneficiaries would benefit from information on the extent to which prescription drug plans provide risk protection. PsycINFO Database Record (c) 2013 APA, all rights reserved.

  13. Mapping carcass and meat quality QTL on Sus Scrofa chromosome 2 in commercial finishing pigs

    PubMed Central

    Heuven, Henri CM; van Wijk, Rik HJ; Dibbits, Bert; van Kampen, Tony A; Knol, Egbert F; Bovenhuis, Henk

    2009-01-01

    Quantitative trait loci (QTL) affecting carcass and meat quality located on SSC2 were identified using variance component methods. A large number of traits involved in meat and carcass quality was detected in a commercial crossbred population: 1855 pigs sired by 17 boars from a synthetic line, which where homozygous (A/A) for IGF2. Using combined linkage and linkage disequilibrium mapping (LDLA), several QTL significantly affecting loin muscle mass, ham weight and ham muscles (outer ham and knuckle ham) and meat quality traits, such as Minolta-L* and -b*, ultimate pH and Japanese colour score were detected. These results agreed well with previous QTL-studies involving SSC2. Since our study is carried out on crossbreds, different QTL may be segregating in the parental lines. To address this question, we compared models with a single QTL-variance component with models allowing for separate sire and dam QTL-variance components. The same QTL were identified using a single QTL variance component model compared to a model allowing for separate variances with minor differences with respect to QTL location. However, the variance component method made it possible to detect QTL segregating in the paternal line (e.g. HAMB), the maternal lines (e.g. Ham) or in both (e.g. pHu). Combining association and linkage information among haplotypes improved slightly the significance of the QTL compared to an analysis using linkage information only. PMID:19284675

  14. Analysis of the variation in OCT measurements of a structural bottle neck for eye-brain transfer of visual information from 3D-volumes of the optic nerve head, PIMD-Average [02π

    NASA Astrophysics Data System (ADS)

    Söderberg, Per G.; Malmberg, Filip; Sandberg-Melin, Camilla

    2016-03-01

    The present study aimed to analyze the clinical usefulness of the thinnest cross section of the nerve fibers in the optic nerve head averaged over the circumference of the optic nerve head. 3D volumes of the optic nerve head of the same eye was captured at two different visits spaced in time by 1-4 weeks, in 13 subjects diagnosed with early to moderate glaucoma. At each visit 3 volumes containing the optic nerve head were captured independently with a Topcon OCT- 2000 system. In each volume, the average shortest distance between the inner surface of the retina and the central limit of the pigment epithelium around the optic nerve head circumference, PIMD-Average [02π], was determined semiautomatically. The measurements were analyzed with an analysis of variance for estimation of the variance components for subjects, visits, volumes and semi-automatic measurements of PIMD-Average [0;2π]. It was found that the variance for subjects was on the order of five times the variance for visits, and the variance for visits was on the order of 5 times higher than the variance for volumes. The variance for semi-automatic measurements of PIMD-Average [02π] was 3 orders of magnitude lower than the variance for volumes. A 95 % confidence interval for mean PIMD-Average [02π] was estimated to 1.00 +/-0.13 mm (D.f. = 12). The variance estimates indicate that PIMD-Average [02π] is not suitable for comparison between a onetime estimate in a subject and a population reference interval. Cross-sectional independent group comparisons of PIMD-Average [02π] averaged over subjects will require inconveniently large sample sizes. However, cross-sectional independent group comparison of averages of within subject difference between baseline and follow-up can be made with reasonable sample sizes. Assuming a loss rate of 0.1 PIMD-Average [02π] per year and 4 visits per year it was found that approximately 18 months follow up is required before a significant change of PIMDAverage [02π] can be observed with a power of 0.8. This is shorter than what has been observed both for HRT measurements and automated perimetry measurements with a similar observation rate. It is concluded that PIMDAverage [02π] has the potential to detect deterioration of glaucoma quicker than currently available primary diagnostic instruments. To increase the efficiency of PIMD-Average [02π] further, the variation among visits within subject has to be reduced.

  15. Correcting Spatial Variance of RCM for GEO SAR Imaging Based on Time-Frequency Scaling.

    PubMed

    Yu, Ze; Lin, Peng; Xiao, Peng; Kang, Lihong; Li, Chunsheng

    2016-07-14

    Compared with low-Earth orbit synthetic aperture radar (SAR), a geosynchronous (GEO) SAR can have a shorter revisit period and vaster coverage. However, relative motion between this SAR and targets is more complicated, which makes range cell migration (RCM) spatially variant along both range and azimuth. As a result, efficient and precise imaging becomes difficult. This paper analyzes and models spatial variance for GEO SAR in the time and frequency domains. A novel algorithm for GEO SAR imaging with a resolution of 2 m in both the ground cross-range and range directions is proposed, which is composed of five steps. The first is to eliminate linear azimuth variance through the first azimuth time scaling. The second is to achieve RCM correction and range compression. The third is to correct residual azimuth variance by the second azimuth time-frequency scaling. The fourth and final steps are to accomplish azimuth focusing and correct geometric distortion. The most important innovation of this algorithm is implementation of the time-frequency scaling to correct high-order azimuth variance. As demonstrated by simulation results, this algorithm can accomplish GEO SAR imaging with good and uniform imaging quality over the entire swath.

  16. Correcting Spatial Variance of RCM for GEO SAR Imaging Based on Time-Frequency Scaling

    PubMed Central

    Yu, Ze; Lin, Peng; Xiao, Peng; Kang, Lihong; Li, Chunsheng

    2016-01-01

    Compared with low-Earth orbit synthetic aperture radar (SAR), a geosynchronous (GEO) SAR can have a shorter revisit period and vaster coverage. However, relative motion between this SAR and targets is more complicated, which makes range cell migration (RCM) spatially variant along both range and azimuth. As a result, efficient and precise imaging becomes difficult. This paper analyzes and models spatial variance for GEO SAR in the time and frequency domains. A novel algorithm for GEO SAR imaging with a resolution of 2 m in both the ground cross-range and range directions is proposed, which is composed of five steps. The first is to eliminate linear azimuth variance through the first azimuth time scaling. The second is to achieve RCM correction and range compression. The third is to correct residual azimuth variance by the second azimuth time-frequency scaling. The fourth and final steps are to accomplish azimuth focusing and correct geometric distortion. The most important innovation of this algorithm is implementation of the time-frequency scaling to correct high-order azimuth variance. As demonstrated by simulation results, this algorithm can accomplish GEO SAR imaging with good and uniform imaging quality over the entire swath. PMID:27428974

  17. Variance adaptation in navigational decision making

    NASA Astrophysics Data System (ADS)

    Gershow, Marc; Gepner, Ruben; Wolk, Jason; Wadekar, Digvijay

    Drosophila larvae navigate their environments using a biased random walk strategy. A key component of this strategy is the decision to initiate a turn (change direction) in response to declining conditions. We modeled this decision as the output of a Linear-Nonlinear-Poisson cascade and used reverse correlation with visual and fictive olfactory stimuli to find the parameters of this model. Because the larva responds to changes in stimulus intensity, we used stimuli with uncorrelated normally distributed intensity derivatives, i.e. Brownian processes, and took the stimulus derivative as the input to our LNP cascade. In this way, we were able to present stimuli with 0 mean and controlled variance. We found that the nonlinear rate function depended on the variance in the stimulus input, allowing larvae to respond more strongly to small changes in low-noise compared to high-noise environments. We measured the rate at which the larva adapted its behavior following changes in stimulus variance, and found that larvae adapted more quickly to increases in variance than to decreases, consistent with the behavior of an optimal Bayes estimator. Supported by NIH Grant 1DP2EB022359 and NSF Grant PHY-1455015.

  18. False alarms: How early warning signals falsely predict abrupt sea ice loss

    NASA Astrophysics Data System (ADS)

    Wagner, Till J. W.; Eisenman, Ian

    2016-04-01

    Uncovering universal early warning signals for critical transitions has become a coveted goal in diverse scientific disciplines, ranging from climate science to financial mathematics. There has been a flurry of recent research proposing such signals, with increasing autocorrelation and increasing variance being among the most widely discussed candidates. A number of studies have suggested that increasing autocorrelation alone may suffice to signal an impending transition, although some others have questioned this. Here we consider variance and autocorrelation in the context of sea ice loss in an idealized model of the global climate system. The model features no bifurcation, nor increased rate of retreat, as the ice disappears. Nonetheless, the autocorrelation of summer sea ice area is found to increase in a global warming scenario. The variance, by contrast, decreases. A simple physical mechanism is proposed to explain the occurrence of increasing autocorrelation but not variance when there is no approaching bifurcation. Additionally, a similar mechanism is shown to allow an increase in both indicators with no physically attainable bifurcation. This implies that relying on autocorrelation and variance as early warning signals can raise false alarms in the climate system, warning of "tipping points" that are not actually there.

  19. Allosteric effects in bacteriophage HK97 procapsids revealed directly from covariance analysis of cryo EM data.

    PubMed

    Xu, Nan; Veesler, David; Doerschuk, Peter C; Johnson, John E

    2018-05-01

    The information content of cryo EM data sets exceeds that of the electron scattering potential (cryo EM) density initially derived for structure determination. Previously we demonstrated the power of data variance analysis for characterizing regions of cryo EM density that displayed functionally important variance anomalies associated with maturation cleavage events in Nudaurelia Omega Capensis Virus and the presence or absence of a maturation protease in bacteriophage HK97 procapsids. Here we extend the analysis in two ways. First, instead of imposing icosahedral symmetry on every particle in the data set during the variance analysis, we only assume that the data set as a whole has icosahedral symmetry. This change removes artifacts of high variance along icosahedral symmetry axes, but retains all of the features previously reported in the HK97 data set. Second we present a covariance analysis that reveals correlations in structural dynamics (variance) between the interior of the HK97 procapsid with the protease and regions of the exterior (not seen in the absence of the protease). The latter analysis corresponds well with hydrogen deuterium exchange studies previously published that reveal the same correlation. Copyright © 2018 Elsevier Inc. All rights reserved.

  20. [Analysis of variance of repeated data measured by water maze with SPSS].

    PubMed

    Qiu, Hong; Jin, Guo-qin; Jin, Ru-feng; Zhao, Wei-kang

    2007-01-01

    To introduce the method of analyzing repeated data measured by water maze with SPSS 11.0, and offer a reference statistical method to clinical and basic medicine researchers who take the design of repeated measures. Using repeated measures and multivariate analysis of variance (ANOVA) process of the general linear model in SPSS and giving comparison among different groups and different measure time pairwise. Firstly, Mauchly's test of sphericity should be used to judge whether there were relations among the repeatedly measured data. If any (P

  1. Verbal Working Memory in Children With Cochlear Implants

    PubMed Central

    Caldwell-Tarr, Amanda; Low, Keri E.; Lowenstein, Joanna H.

    2017-01-01

    Purpose Verbal working memory in children with cochlear implants and children with normal hearing was examined. Participants Ninety-three fourth graders (47 with normal hearing, 46 with cochlear implants) participated, all of whom were in a longitudinal study and had working memory assessed 2 years earlier. Method A dual-component model of working memory was adopted, and a serial recall task measured storage and processing. Potential predictor variables were phonological awareness, vocabulary knowledge, nonverbal IQ, and several treatment variables. Potential dependent functions were literacy, expressive language, and speech-in-noise recognition. Results Children with cochlear implants showed deficits in storage and processing, similar in size to those at second grade. Predictors of verbal working memory differed across groups: Phonological awareness explained the most variance in children with normal hearing; vocabulary explained the most variance in children with cochlear implants. Treatment variables explained little of the variance. Where potentially dependent functions were concerned, verbal working memory accounted for little variance once the variance explained by other predictors was removed. Conclusions The verbal working memory deficits of children with cochlear implants arise due to signal degradation, which limits their abilities to acquire phonological awareness. That hinders their abilities to store items using a phonological code. PMID:29075747

  2. Seasonal variation of wave activities near the mesopause region observed at King Sejong Station (62.22°S, 58.78°W), Antarctica

    NASA Astrophysics Data System (ADS)

    Lee, Changsup; Kim, Yong Ha; Kim, Jeong-Han; Jee, Geonhwa; Won, Young-In; Wu, Dong L.

    2013-12-01

    We analyzed the neutral wind data at altitudes of 80-100 km obtained from a VHF meteor radar at King Sejong Station (KSS, 62.22°S, 58.78°W), a key location to study wave activities above the stratospheric vortex near the Antarctic Peninsula. The seasonal behavior of the semidiurnal tides is generally consistent with the prediction of Global Scale Wave Model (GSWM02) except in the altitude region above ~96 km. Gravity wave (GW) activities inferred from the neutral wind variances show a seasonal variation very similar to the semidiurnal tide amplitudes, suggesting a strong interaction between gravity waves and the tide. Despite the consistent seasonal variations of the GW wind variances observed at the adjacent Rothera station, the magnitudes of the wind variance obtained at KSS are much larger than those at Rothera, especially during May-September. The enhanced GW activity at KSS is also observed by Aura Microwave Limb Sounder (MLS) from space in its temperature variance. The observed large wind variances at KSS imply that the Antarctic vortex in the stratosphere may act as an effective filter and source for the GWs in the upper atmosphere.

  3. Estimating means and variances: The comparative efficiency of composite and grab samples.

    PubMed

    Brumelle, S; Nemetz, P; Casey, D

    1984-03-01

    This paper compares the efficiencies of two sampling techniques for estimating a population mean and variance. One procedure, called grab sampling, consists of collecting and analyzing one sample per period. The second procedure, called composite sampling, collectsn samples per period which are then pooled and analyzed as a single sample. We review the well known fact that composite sampling provides a superior estimate of the mean. However, it is somewhat surprising that composite sampling does not always generate a more efficient estimate of the variance. For populations with platykurtic distributions, grab sampling gives a more efficient estimate of the variance, whereas composite sampling is better for leptokurtic distributions. These conditions on kurtosis can be related to peakedness and skewness. For example, a necessary condition for composite sampling to provide a more efficient estimate of the variance is that the population density function evaluated at the mean (i.e.f(μ)) be greater than[Formula: see text]. If[Formula: see text], then a grab sample is more efficient. In spite of this result, however, composite sampling does provide a smaller estimate of standard error than does grab sampling in the context of estimating population means.

  4. [A self administered survey to assess bullying in schools].

    PubMed

    Lecannelier, Felipe; Varela, Jorge; Rodríguez, Jorge; Hoffmann, Marianela; Flores, Fernanda; Ascanio, Lorena

    2011-04-01

    Bullying is common in schools and has negative consequences. It can be assessed using a self-reported instrument. To validate a Spanish self-reporting tool called "Survey of High School Bullying Abuse of Power" (MIAP). The instrument has 13 questions, of which 7 are multiple choice, rendering a total of 49 items. It was applied to 2.341 children of seventh and eighth grade attending private, subsidized and municipal schools in the city of Concepción, Chile. Expert judge analysis and estimated reliability using the Cronbach Alpha were used to validate the survey. The instrument obtained a Cronbach Alpha coefficient of 0.8892, classified as good. This analysis generated four scales that explained 30.9% of the variance. They were called "Witness Bullying" with 18 items, accounting for 11.4% of the variance, "Bullying Victim" with 12 items, accounting for 7.5% of the variance, "Bullying Perpetrator and Severe bullying Victim", with 10 items explaining 6.4% of the variance and "Aggressor Bullying" with 6 items accounting for 5.7% of the variance. The MIAP can recognize four basic factors that facilitate the analysis and understanding of bullying, with good levels of reliability and validity. The remaining questions also deliver valuable information.

  5. Choice in experiential learning: True preferences or experimental artifacts?

    PubMed

    Ashby, Nathaniel J S; Konstantinidis, Emmanouil; Yechiam, Eldad

    2017-03-01

    The rate of selecting different options in the decisions-from-feedback paradigm is commonly used to measure preferences resulting from experiential learning. While convergence to a single option increases with experience, some variance in choice remains even when options are static and offer fixed rewards. Employing a decisions-from-feedback paradigm followed by a policy-setting task, we examined whether the observed variance in choice is driven by factors related to the paradigm itself: Continued exploration (e.g., believing options are non-stationary) or exploitation of perceived outcome patterns (i.e., a belief that sequential choices are not independent). Across two studies, participants showed variance in their choices, which was related (i.e., proportional) to the policies they set. In addition, in Study 2, participants' reported under-confidence was associated with the amount of choice variance in later choices and policies. These results suggest that variance in choice is better explained by participants lacking confidence in knowing which option is better, rather than methodological artifacts (i.e., exploration or failures to recognize outcome independence). As such, the current studies provide evidence for the decisions-from-feedback paradigm's validity as a behavioral research method for assessing learned preferences. Copyright © 2017 Elsevier B.V. All rights reserved.

  6. Variation of gene expression in Bacillus subtilis samples of fermentation replicates.

    PubMed

    Zhou, Ying; Yu, Wen-Bang; Ye, Bang-Ce

    2011-06-01

    The application of comprehensive gene expression profiling technologies to compare wild and mutated microorganism samples or to assess molecular differences between various treatments has been widely used. However, little is known about the normal variation of gene expression in microorganisms. In this study, an Agilent customized microarray representing 4,106 genes was used to quantify transcript levels of five-repeated flasks to assess normal variation in Bacillus subtilis gene expression. CV analysis and analysis of variance were employed to investigate the normal variance of genes and the components of variance, respectively. The results showed that above 80% of the total variation was caused by biological variance. For the 12 replicates, 451 of 4,106 genes exhibited variance with CV values over 10%. The functional category enrichment analysis demonstrated that these variable genes were mainly involved in cell type differentiation, cell type localization, cell cycle and DNA processing, and spore or cyst coat. Using power analysis, the minimal biological replicate number for a B. subtilis microarray experiment was determined to be six. The results contribute to the definition of the baseline level of variability in B. subtilis gene expression and emphasize the importance of replicate microarray experiments.

  7. The Pattern Across the Continental United States of Evapotranspiration Variability Associated with Water Availability

    NASA Technical Reports Server (NTRS)

    Koster, Randal D.; Salvucci, Guido D.; Rigden, Angela J.; Jung, Martin; Collatz, G. James; Schubert, Siegfried D.

    2015-01-01

    The spatial pattern across the continental United States of the interannual variance of warm season water-dependent evapotranspiration, a pattern of relevance to land-atmosphere feedback, cannot be measured directly. Alternative and indirect approaches to estimating the pattern, however, do exist, and given the uncertainty of each, we use several such approaches here. We first quantify the water dependent evapotranspiration variance pattern inherent in two derived evapotranspiration datasets available from the literature. We then search for the pattern in proxy geophysical variables (air temperature, stream flow, and NDVI) known to have strong ties to evapotranspiration. The variances inherent in all of the different (and mostly independent) data sources show some differences but are generally strongly consistent they all show a large variance signal down the center of the U.S., with lower variances toward the east and (for the most part) toward the west. The robustness of the pattern across the datasets suggests that it indeed represents the pattern operating in nature. Using Budykos hydroclimatic framework, we show that the pattern can largely be explained by the relative strength of water and energy controls on evapotranspiration across the continent.

  8. Relationships between alexithymia, affect recognition, and empathy after traumatic brain injury.

    PubMed

    Neumann, Dawn; Zupan, Barbra; Malec, James F; Hammond, Flora

    2014-01-01

    To determine (1) alexithymia, affect recognition, and empathy differences in participants with and without traumatic brain injury (TBI); (2) the amount of affect recognition variance explained by alexithymia; and (3) the amount of empathy variance explained by alexithymia and affect recognition. Sixty adults with moderate-to-severe TBI; 60 age and gender-matched controls. Participants were evaluated for alexithymia (difficulty identifying feelings, difficulty describing feelings, and externally-oriented thinking); facial and vocal affect recognition; and affective and cognitive empathy (empathic concern and perspective-taking, respectively). Participants with TBI had significantly higher alexithymia; poorer facial and vocal affect recognition; and lower empathy scores. For TBI participants, facial and vocal affect recognition variances were significantly explained by alexithymia (12% and 8%, respectively); however, the majority of the variances were accounted for by externally-oriented thinking alone. Affect recognition and alexithymia significantly accounted for 16.5% of cognitive empathy. Again, the majority of the variance was primarily explained by externally-oriented thinking. Affect recognition and alexithymia did not explain affective empathy. Results suggest that people who have a tendency to avoid thinking about emotions (externally-oriented thinking) are more likely to have problems recognizing others' emotions and assuming others' points of view. Clinical implications are discussed.

  9. Using the PLUM procedure of SPSS to fit unequal variance and generalized signal detection models.

    PubMed

    DeCarlo, Lawrence T

    2003-02-01

    The recent addition of aprocedure in SPSS for the analysis of ordinal regression models offers a simple means for researchers to fit the unequal variance normal signal detection model and other extended signal detection models. The present article shows how to implement the analysis and how to interpret the SPSS output. Examples of fitting the unequal variance normal model and other generalized signal detection models are given. The approach offers a convenient means for applying signal detection theory to a variety of research.

  10. Predicting the Cost per Flying Hour for the F-16 Using Programmatic and Operational Variables

    DTIC Science & Technology

    2005-06-01

    constant variance assumption is accomplished using the Breusch - Pagan test . This is accomplished and the results are listed in Table 12. Figures 19...and 20 follow and add to the discussion by plotting the residuals by predicted for both models. 52 Table 12: Breusch - Pagan Constant Variance Test ...Model A 13844455 6.97E+11 5 74 9.96 0.0764 Model B 74954796 8.69E+12 5 151 17.63 0.00344 Breusch - Pagan Test for Constant Variance -1000 -500 0 500

  11. The Pricing of European Options Under the Constant Elasticity of Variance with Stochastic Volatility

    NASA Astrophysics Data System (ADS)

    Bock, Bounghun; Choi, Sun-Yong; Kim, Jeong-Hoon

    This paper considers a hybrid risky asset price model given by a constant elasticity of variance multiplied by a stochastic volatility factor. A multiscale analysis leads to an asymptotic pricing formula for both European vanilla option and a Barrier option near the zero elasticity of variance. The accuracy of the approximation is provided in a rigorous manner. A numerical experiment for implied volatilities shows that the hybrid model improves some of the well-known models in view of fitting the data for different maturities.

  12. Classification of local and regional events in central Europe based on estimates of S-wave spectral variance

    NASA Astrophysics Data System (ADS)

    Koch, Karl

    2002-10-01

    The Vogtland region, in the border region of Germany and the Czech Republic, is of special interest for the identification of seismic events on a local and regional scale, since both earthquakes and explosions occur frequently in the same area, and thus are relevant for discrimination research for verification of the Comprehensive Nuclear Test Ban Treaty. Previous research on event discrimination using spectral decay and variance from data recorded by the GERESS array indicated that spectral variance determined for the S phase for the seismic events in the Vogtland region seems to be the most promising parameter for event discrimination, because this parameter provides for almost complete separation of the earthquake and explosion populations. Almost the entire set of Vogtland events used in this research and more than 3000 local events detected in Germany in 1998 and 1999 were analysed to determine spectral slopes and variance for the P- and S-wave windows from stacked spectra of recordings at the GERESS array. The results suggest that small values for the spectral variance are associated not only with earthquakes in the Vogtland region, but also with earthquakes in other parts of Germany and neighbouring countries. While mining blasts show larger spectral variance values, mining-induced events yield a wide range of values, for example, in the Lubin area. A threshold-based identification scheme was applied; almost all events classified as earthquakes are found in seismically active regions. While the earthquakes are uniformly distributed throughout the day, events classified as explosions correlate with normal working hours, which is when blasting is done in Germany. In this study spectral variance provides good event discrimination for events in other parts of Germany, not only for the Vogtland region, showing that this identification parameter may be transported to other geological regions.

  13. In vivo recovery of factor VIII and factor IX: intra- and interindividual variance in a clinical setting.

    PubMed

    Björkman, S; Folkesson, A; Berntorp, E

    2007-01-01

    In vivo recovery (IVR) is traditionally used as a parameter to characterize the pharmacokinetic properties of coagulation factors. It has also been suggested that dosing of factor VIII (FVIII) and factor IX (FIX) can be adjusted according to the need of the individual patient, based on an individually determined IVR value. This approach, however, requires that the individual IVR value is more reliably representative for the patient than the mean value in the population, i.e. that there is less variance within than between the individuals. The aim of this investigation was to compare intra- and interindividual variance in IVR (as U dL1 per U kg1) for FVIII and plasma-derived FIX in a cohort of non-bleeding patients with haemophilia. The data were collected retrospectively from six clinical studies, yielding 297 IVR determinations in 50 patients with haemophilia A and 93 determinations in 13 patients with haemophilia B. For FVIII, the mean variance within patients exceeded the between-patient variance. Thus, an individually determined IVR value is apparently no more informative than an average, or population, value for the dosing of FVIII. There was no apparent relationship between IVR and age of the patient (1.5-67 years). For FIX, the mean variance within patients was lower than the between-patient variance, and there was a significant positive relationship between IVR and age (13-69 years). From these data, it seems probable that using an individual IVR confers little advantage in comparison to using an age-specific population mean value. Dose tailoring of coagulation factor treatment has been applied successfully after determination of the entire single-dose curve of FVIII:C or FIX:C in the patient and calculation of the relevant pharmacokinetic parameters. However, the findings presented here do not support the assumption that dosing of FVIII or FIX can be individualized on the basis of a clinically determined IVR value.

  14. Predicting healthy eating intention and adherence to dietary recommendations during pregnancy in Australia using the Theory of Planned Behaviour.

    PubMed

    Malek, Lenka; Umberger, Wendy J; Makrides, Maria; ShaoJia, Zhou

    2017-09-01

    This study aims to aid in the development of more effective healthy eating intervention strategies for pregnant women by understanding the relationship between healthy eating intention and actual eating behaviour. Specifically, the study explored whether Theory of Planned Behaviour (TPB) constructs [attitude, subjective-norm, perceived-behavioural-control (PBC)] and additional psychosocial variables (perceived stress, health value and self-identity as a healthy eater) are useful in explaining variance in women's 1) intentions to consume a healthy diet during pregnancy and 2) food consumption behaviour (e.g. adherence to food group recommendations) during pregnancy. A cross-sectional sample of 455 Australian pregnant women completed a TPB questionnaire as part of a larger comprehensive web-based nutrition questionnaire. Women's perceived stress, health value and self-identity as a healthy eater were also measured. Dietary intake was assessed using six-items based on the 2013 Australian Dietary Guidelines. Hierarchical multiple linear regression models were estimated (significance level <0.05), which explained 70% of the variance in healthy eating intention scores and 12% of the variance in adherence to food group recommendations. TPB constructs explained 66% of the total variance in healthy eating intention. Significant predictors of stronger healthy eating intention were greater PBC and subjective norm, followed by positive attitude and stronger self-identity as a healthy eater. Conversely, TPB constructs collectively explained only 3.4% of total variance in adherence to food group recommendations. These findings reveal that the TPB framework explains considerable variance in healthy eating intention during pregnancy, but explains little variance in actual food consumption behaviour. Further research is required to understand this weak relationship between healthy eating intention and behaviour during pregnancy. Alternative behavioural frameworks, particularly those that account for the automatic nature of most dietary choices, should also be considered. Copyright © 2017 Elsevier Ltd. All rights reserved.

  15. THE LONGEST TIMESCALE X-RAY VARIABILITY REVEALS EVIDENCE FOR ACTIVE GALACTIC NUCLEI IN THE HIGH ACCRETION STATE

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

    Zhang Youhong, E-mail: youhong.zhang@mail.tsinghua.edu.cn

    2011-01-01

    The All Sky Monitor (ASM) on board the Rossi X-ray Timing Explorer has continuously monitored a number of active galactic nuclei (AGNs) with similar sampling rates for 14 years, from 1996 January to 2009 December. Utilizing the archival ASM data of 27 AGNs, we calculate the normalized excess variances of the 300-day binned X-ray light curves on the longest timescale (between 300 days and 14 years) explored so far. The observed variance appears to be independent of AGN black-hole mass and bolometric luminosity. According to the scaling relation of black-hole mass (and bolometric luminosity) from galactic black hole X-ray binariesmore » (GBHs) to AGNs, the break timescales that correspond to the break frequencies detected in the power spectral density (PSD) of our AGNs are larger than the binsize (300 days) of the ASM light curves. As a result, the singly broken power-law (soft-state) PSD predicts the variance to be independent of mass and luminosity. Nevertheless, the doubly broken power-law (hard-state) PSD predicts, with the widely accepted ratio of the two break frequencies, that the variance increases with increasing mass and decreases with increasing luminosity. Therefore, the independence of the observed variance on mass and luminosity suggests that AGNs should have soft-state PSDs. Taking into account the scaling of the break timescale with mass and luminosity synchronously, the observed variances are also more consistent with the soft-state than the hard-state PSD predictions. With the averaged variance of AGNs and the soft-state PSD assumption, we obtain a universal PSD amplitude of 0.030 {+-} 0.022. By analogy with the GBH PSDs in the high/soft state, the longest timescale variability supports the standpoint that AGNs are scaled-up GBHs in the high accretion state, as already implied by the direct PSD analysis.« less

  16. Inter-individual Differences in the Effects of Aircraft Noise on Sleep Fragmentation.

    PubMed

    McGuire, Sarah; Müller, Uwe; Elmenhorst, Eva-Maria; Basner, Mathias

    2016-05-01

    Environmental noise exposure disturbs sleep and impairs recuperation, and may contribute to the increased risk for (cardiovascular) disease. Noise policy and regulation are usually based on average responses despite potentially large inter-individual differences in the effects of traffic noise on sleep. In this analysis, we investigated what percentage of the total variance in noise-induced awakening reactions can be explained by stable inter-individual differences. We investigated 69 healthy subjects polysomnographically (mean ± standard deviation 40 ± 13 years, range 18-68 years, 32 male) in this randomized, balanced, double-blind, repeated measures laboratory study. This study included one adaptation night, 9 nights with exposure to 40, 80, or 120 road, rail, and/or air traffic noise events (including one noise-free control night), and one recovery night. Mixed-effects models of variance controlling for reaction probability in noise-free control nights, age, sex, number of noise events, and study night showed that 40.5% of the total variance in awakening probability and 52.0% of the total variance in EEG arousal probability were explained by inter-individual differences. If the data set was restricted to nights (4 exposure nights with 80 noise events per night), 46.7% of the total variance in awakening probability and 57.9% of the total variance in EEG arousal probability were explained by inter-individual differences. The results thus demonstrate that, even in this relatively homogeneous, healthy, adult study population, a considerable amount of the variance observed in noise-induced sleep disturbance can be explained by inter-individual differences that cannot be explained by age, gender, or specific study design aspects. It will be important to identify those at higher risk for noise induced sleep disturbance. Furthermore, the custom to base noise policy and legislation on average responses should be re-assessed based on these findings. © 2016 Associated Professional Sleep Societies, LLC.

  17. Sources of Variability in Physical Activity Among Inactive People with Multiple Sclerosis.

    PubMed

    Uszynski, Marcin K; Herring, Matthew P; Casey, Blathin; Hayes, Sara; Gallagher, Stephen; Motl, Robert W; Coote, Susan

    2018-04-01

    Evidence supports that physical activity (PA) improves symptoms of multiple sclerosis (MS). Although application of principles from Social Cognitive Theory (SCT) may facilitate positive changes in PA behaviour among people with multiple sclerosis (pwMS), the constructs often explain limited variance in PA. This study investigated the extent to which MS symptoms, including fatigue, depression, and walking limitations combined with the SCT constructs, explained more variance in PA than SCT constructs alone among pwMS. Baseline data, including objectively assessed PA, exercise self-efficacy, goal setting, outcome expectations, 6-min walk test, fatigue and depression, from 65 participants of the Step It Up randomized controlled trial completed in Ireland (2016), were included. Multiple regression models quantified variance explained in PA and independent associations of (1) SCT constructs, (2) symptoms and (3) SCT constructs and symptoms. Model 1 included exercise self-efficacy, exercise goal setting and multidimensional outcomes expectations for exercise and explained ~14% of the variance in PA (R 2 =0.144, p < 0.05). Model 2 included walking limitations, fatigue and depression and explained 20% of the variance in PA (R 2 =0.196, p < 0.01). Model 3 combined models 1 and 2 and explained variance increased to ~29% (R 2 =0.288; p<0.01). In Model 3, exercise self-efficacy (β=0.30, p < 0.05), walking limitations (β=0.32, p < 0.01), fatigue (β = -0.41, p < 0.01) and depression (β = 0.34, p < 0.05) were significantly and independently associated with PA. Findings suggest that relevant MS symptoms improved by PA, including fatigue, depression and walking limitations, and SCT constructs together explained more variance in PA than SCT constructs alone, providing support for targeting both SCT constructs and these symptoms in the multifactorial promotion of PA among pwMS.

  18. Hierarchical Bayesian modeling of heterogeneous variances in average daily weight gain of commercial feedlot cattle.

    PubMed

    Cernicchiaro, N; Renter, D G; Xiang, S; White, B J; Bello, N M

    2013-06-01

    Variability in ADG of feedlot cattle can affect profits, thus making overall returns more unstable. Hence, knowledge of the factors that contribute to heterogeneity of variances in animal performance can help feedlot managers evaluate risks and minimize profit volatility when making managerial and economic decisions in commercial feedlots. The objectives of the present study were to evaluate heteroskedasticity, defined as heterogeneity of variances, in ADG of cohorts of commercial feedlot cattle, and to identify cattle demographic factors at feedlot arrival as potential sources of variance heterogeneity, accounting for cohort- and feedlot-level information in the data structure. An operational dataset compiled from 24,050 cohorts from 25 U. S. commercial feedlots in 2005 and 2006 was used for this study. Inference was based on a hierarchical Bayesian model implemented with Markov chain Monte Carlo, whereby cohorts were modeled at the residual level and feedlot-year clusters were modeled as random effects. Forward model selection based on deviance information criteria was used to screen potentially important explanatory variables for heteroskedasticity at cohort- and feedlot-year levels. The Bayesian modeling framework was preferred as it naturally accommodates the inherently hierarchical structure of feedlot data whereby cohorts are nested within feedlot-year clusters. Evidence for heterogeneity of variance components of ADG was substantial and primarily concentrated at the cohort level. Feedlot-year specific effects were, by far, the greatest contributors to ADG heteroskedasticity among cohorts, with an estimated ∼12-fold change in dispersion between most and least extreme feedlot-year clusters. In addition, identifiable demographic factors associated with greater heterogeneity of cohort-level variance included smaller cohort sizes, fewer days on feed, and greater arrival BW, as well as feedlot arrival during summer months. These results support that heterogeneity of variances in ADG is prevalent in feedlot performance and indicate potential sources of heteroskedasticity. Further investigation of factors associated with heteroskedasticity in feedlot performance is warranted to increase consistency and uniformity in commercial beef cattle production and subsequent profitability.

  19. Variation in Seed Germination of 134 Common Species on the Eastern Tibetan Plateau: Phylogenetic, Life History and Environmental Correlates

    PubMed Central

    Xu, Jing; Li, Wenlong; Zhang, Chunhui; Liu, Wei; Du, Guozhen

    2014-01-01

    Seed germination is a crucial stage in the life history of a species because it represents the pathway from adult to offspring, and it can affect the distribution and abundance of species in communities. In this study, we examined the effects of phylogenetic, life history and environmental factors on seed germination of 134 common species from an alpine/subalpine meadow on the eastern Tibetan Plateau. In one-way ANOVAs, phylogenetic groups (at or above order) explained 13.0% and 25.9% of the variance in germination percentage and mean germination time, respectively; life history attributes, such as seed size, dispersal mode, explained 3.7%, 2.1% of the variance in germination percentage and 6.3%, 8.7% of the variance in mean germination time, respectively; the environmental factors temperature and habitat explained 4.7%, 1.0% of the variance in germination percentage and 13.5%, 1.7% of the variance in mean germination time, respectively. Our results demonstrated that elevated temperature would lead to a significant increase in germination percentage and an accelerated germination. Multi-factorial ANOVAs showed that the three major factors contributing to differences in germination percentage and mean germination time in this alpine/subalpine meadow were phylogenetic attributes, temperature and seed size (explained 10.5%, 4.7% and 1.4% of the variance in germination percentage independently, respectively; and explained 14.9%, 13.5% and 2.7% of the variance in mean germination time independently, respectively). In addition, there were strong associations between phylogenetic group and life history attributes, and between life history attributes and environmental factors. Therefore, germination variation are constrained mainly by phylogenetic inertia in a community, and seed germination variation correlated with phylogeny is also associated with life history attributes, suggesting a role of niche adaptation in the conservation of germination variation within lineages. Meanwhile, selection can maintain the association between germination behavior and the environmental conditions within a lineage. PMID:24893308

  20. Stratospheric Assimilation of Chemical Tracer Observations Using a Kalman Filter. Pt. 2; Chi-Square Validated Results and Analysis of Variance and Correlation Dynamics

    NASA Technical Reports Server (NTRS)

    Menard, Richard; Chang, Lang-Ping

    1998-01-01

    A Kalman filter system designed for the assimilation of limb-sounding observations of stratospheric chemical tracers, which has four tunable covariance parameters, was developed in Part I (Menard et al. 1998) The assimilation results of CH4 observations from the Cryogenic Limb Array Etalon Sounder instrument (CLAES) and the Halogen Observation Experiment instrument (HALOE) on board of the Upper Atmosphere Research Satellite are described in this paper. A robust (chi)(sup 2) criterion, which provides a statistical validation of the forecast and observational error covariances, was used to estimate the tunable variance parameters of the system. In particular, an estimate of the model error variance was obtained. The effect of model error on the forecast error variance became critical after only three days of assimilation of CLAES observations, although it took 14 days of forecast to double the initial error variance. We further found that the model error due to numerical discretization as arising in the standard Kalman filter algorithm, is comparable in size to the physical model error due to wind and transport modeling errors together. Separate assimilations of CLAES and HALOE observations were compared to validate the state estimate away from the observed locations. A wave-breaking event that took place several thousands of kilometers away from the HALOE observation locations was well captured by the Kalman filter due to highly anisotropic forecast error correlations. The forecast error correlation in the assimilation of the CLAES observations was found to have a structure similar to that in pure forecast mode except for smaller length scales. Finally, we have conducted an analysis of the variance and correlation dynamics to determine their relative importance in chemical tracer assimilation problems. Results show that the optimality of a tracer assimilation system depends, for the most part, on having flow-dependent error correlation rather than on evolving the error variance.

  1. Integrating Variances into an Analytical Database

    NASA Technical Reports Server (NTRS)

    Sanchez, Carlos

    2010-01-01

    For this project, I enrolled in numerous SATERN courses that taught the basics of database programming. These include: Basic Access 2007 Forms, Introduction to Database Systems, Overview of Database Design, and others. My main job was to create an analytical database that can handle many stored forms and make it easy to interpret and organize. Additionally, I helped improve an existing database and populate it with information. These databases were designed to be used with data from Safety Variances and DCR forms. The research consisted of analyzing the database and comparing the data to find out which entries were repeated the most. If an entry happened to be repeated several times in the database, that would mean that the rule or requirement targeted by that variance has been bypassed many times already and so the requirement may not really be needed, but rather should be changed to allow the variance's conditions permanently. This project did not only restrict itself to the design and development of the database system, but also worked on exporting the data from the database to a different format (e.g. Excel or Word) so it could be analyzed in a simpler fashion. Thanks to the change in format, the data was organized in a spreadsheet that made it possible to sort the data by categories or types and helped speed up searches. Once my work with the database was done, the records of variances could be arranged so that they were displayed in numerical order, or one could search for a specific document targeted by the variances and restrict the search to only include variances that modified a specific requirement. A great part that contributed to my learning was SATERN, NASA's resource for education. Thanks to the SATERN online courses I took over the summer, I was able to learn many new things about computers and databases and also go more in depth into topics I already knew about.

  2. Small Drinking Water System Variances

    EPA Pesticide Factsheets

    Small system variances allow a small system to install and maintain technology that can remove a contaminant to the maximum extent that is affordable and protective of public health in lieu of technology that can achieve compliance with the regulation.

  3. Impact of Damping Uncertainty on SEA Model Response Variance

    NASA Technical Reports Server (NTRS)

    Schiller, Noah; Cabell, Randolph; Grosveld, Ferdinand

    2010-01-01

    Statistical Energy Analysis (SEA) is commonly used to predict high-frequency vibroacoustic levels. This statistical approach provides the mean response over an ensemble of random subsystems that share the same gross system properties such as density, size, and damping. Recently, techniques have been developed to predict the ensemble variance as well as the mean response. However these techniques do not account for uncertainties in the system properties. In the present paper uncertainty in the damping loss factor is propagated through SEA to obtain more realistic prediction bounds that account for both ensemble and damping variance. The analysis is performed on a floor-equipped cylindrical test article that resembles an aircraft fuselage. Realistic bounds on the damping loss factor are determined from measurements acquired on the sidewall of the test article. The analysis demonstrates that uncertainties in damping have the potential to significantly impact the mean and variance of the predicted response.

  4. Genetic and environmental contributions to the associations between intraindividual variability in reaction time and cognitive function.

    PubMed

    Finkel, Deborah; Pedersen, Nancy L

    2014-01-01

    Intraindividual variability (IIV) in reaction time has been related to cognitive decline, but questions remain about the nature of this relationship. Mean and range in movement and decision time for simple reaction time were available from 241 individuals aged 51-86 years at the fifth testing wave of the Swedish Adoption/Twin Study of Aging. Cognitive performance on four factors was also available: verbal, spatial, memory, and speed. Analyses indicated that range in reaction time could be used as an indicator of IIV. Heritability estimates were 35% for mean reaction and 20% for range in reaction. Multivariate analysis indicated that the genetic variance on the memory, speed, and spatial factors is shared with genetic variance for mean or range in reaction time. IIV shares significant genetic variance with fluid ability in late adulthood, over and above and genetic variance shared with mean reaction time.

  5. Optimal distribution of integration time for intensity measurements in Stokes polarimetry.

    PubMed

    Li, Xiaobo; Liu, Tiegen; Huang, Bingjing; Song, Zhanjie; Hu, Haofeng

    2015-10-19

    We consider the typical Stokes polarimetry system, which performs four intensity measurements to estimate a Stokes vector. We show that if the total integration time of intensity measurements is fixed, the variance of the Stokes vector estimator depends on the distribution of the integration time at four intensity measurements. Therefore, by optimizing the distribution of integration time, the variance of the Stokes vector estimator can be decreased. In this paper, we obtain the closed-form solution of the optimal distribution of integration time by employing Lagrange multiplier method. According to the theoretical analysis and real-world experiment, it is shown that the total variance of the Stokes vector estimator can be significantly decreased about 40% in the case discussed in this paper. The method proposed in this paper can effectively decrease the measurement variance and thus statistically improves the measurement accuracy of the polarimetric system.

  6. Optimal distribution of integration time for intensity measurements in degree of linear polarization polarimetry.

    PubMed

    Li, Xiaobo; Hu, Haofeng; Liu, Tiegen; Huang, Bingjing; Song, Zhanjie

    2016-04-04

    We consider the degree of linear polarization (DOLP) polarimetry system, which performs two intensity measurements at orthogonal polarization states to estimate DOLP. We show that if the total integration time of intensity measurements is fixed, the variance of the DOLP estimator depends on the distribution of integration time for two intensity measurements. Therefore, by optimizing the distribution of integration time, the variance of the DOLP estimator can be decreased. In this paper, we obtain the closed-form solution of the optimal distribution of integration time in an approximate way by employing Delta method and Lagrange multiplier method. According to the theoretical analyses and real-world experiments, it is shown that the variance of the DOLP estimator can be decreased for any value of DOLP. The method proposed in this paper can effectively decrease the measurement variance and thus statistically improve the measurement accuracy of the polarimetry system.

  7. A consistent transported PDF model for treating differential molecular diffusion

    NASA Astrophysics Data System (ADS)

    Wang, Haifeng; Zhang, Pei

    2016-11-01

    Differential molecular diffusion is a fundamentally significant phenomenon in all multi-component turbulent reacting or non-reacting flows caused by the different rates of molecular diffusion of energy and species concentrations. In the transported probability density function (PDF) method, the differential molecular diffusion can be treated by using a mean drift model developed by McDermott and Pope. This model correctly accounts for the differential molecular diffusion in the scalar mean transport and yields a correct DNS limit of the scalar variance production. The model, however, misses the molecular diffusion term in the scalar variance transport equation, which yields an inconsistent prediction of the scalar variance in the transported PDF method. In this work, a new model is introduced to remedy this problem that can yield a consistent scalar variance prediction. The model formulation along with its numerical implementation is discussed, and the model validation is conducted in a turbulent mixing layer problem.

  8. A time dependent mixing model to close PDF equations for transport in heterogeneous aquifers

    NASA Astrophysics Data System (ADS)

    Schüler, L.; Suciu, N.; Knabner, P.; Attinger, S.

    2016-10-01

    Probability density function (PDF) methods are a promising alternative to predicting the transport of solutes in groundwater under uncertainty. They make it possible to derive the evolution equations of the mean concentration and the concentration variance, used in moment methods. The mixing model, describing the transport of the PDF in concentration space, is essential for both methods. Finding a satisfactory mixing model is still an open question and due to the rather elaborate PDF methods, a difficult undertaking. Both the PDF equation and the concentration variance equation depend on the same mixing model. This connection is used to find and test an improved mixing model for the much easier to handle concentration variance. Subsequently, this mixing model is transferred to the PDF equation and tested. The newly proposed mixing model yields significantly improved results for both variance modelling and PDF modelling.

  9. Cognitive constructs and social anxiety disorder: beyond fearing negative evaluation.

    PubMed

    Teale Sapach, Michelle J N; Carleton, R Nicholas; Mulvogue, Myriah K; Weeks, Justin W; Heimberg, Richard G

    2015-01-01

    Pioneering models of social anxiety disorder (SAD) underscored fear of negative evaluation (FNE) as central in the disorder's development. Additional cognitive predictors have since been identified, including fear of positive evaluation (FPE), anxiety sensitivity, and intolerance of uncertainty (IU), but rarely have these constructs been examined together. The present study concurrently examined the variance accounted for in SAD symptoms by these constructs. Participants meeting criteria for SAD (n = 197; 65% women) completed self-report measures online. FNE, FPE, anxiety sensitivity, and IU all accounted for unique variance in SAD symptoms. FPE accounted for variance comparable to FNE, and the cognitive dimension of anxiety sensitivity and the prospective dimension of IU accounted for comparable variance, though slightly less than that accounted for by FNE and FPE. The results support the theorized roles that these constructs play in the etiology of SAD and highlight both FNE and FPE as central foci in SAD treatment.

  10. Gender Differences in Marital Status Moderation of Genetic and Environmental Influences on Subjective Health.

    PubMed

    Finkel, Deborah; Franz, Carol E; Horwitz, Briana; Christensen, Kaare; Gatz, Margaret; Johnson, Wendy; Kaprio, Jaako; Korhonen, Tellervo; Niederheiser, Jenae; Petersen, Inge; Rose, Richard J; Silventoinen, Karri

    2015-10-14

    From the IGEMS Consortium, data were available from 26,579 individuals aged 23 to 102 years on 3 subjective health items: self-rated health (SRH), health compared to others (COMP), and impact of health on activities (ACT). Marital status was a marker of environmental resources that may moderate genetic and environmental influences on subjective health. Results differed for the 3 subjective health items, indicating that they do not tap the same construct. Although there was little impact of marital status on variance components for women, marital status was a significant modifier of variance in all 3 subjective health measures for men. For both SRH and ACT, single men demonstrated greater shared and nonshared environmental variance than married men. For the COMP variable, genetic variance was greater for single men vs. married men. Results suggest gender differences in the role of marriage as a source of resources that are associated with subjective health.

  11. A comparison of maximum likelihood and other estimators of eigenvalues from several correlated Monte Carlo samples

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

    Beer, M.

    1980-12-01

    The maximum likelihood method for the multivariate normal distribution is applied to the case of several individual eigenvalues. Correlated Monte Carlo estimates of the eigenvalue are assumed to follow this prescription and aspects of the assumption are examined. Monte Carlo cell calculations using the SAM-CE and VIM codes for the TRX-1 and TRX-2 benchmark reactors, and SAM-CE full core results are analyzed with this method. Variance reductions of a few percent to a factor of 2 are obtained from maximum likelihood estimation as compared with the simple average and the minimum variance individual eigenvalue. The numerical results verify that themore » use of sample variances and correlation coefficients in place of the corresponding population statistics still leads to nearly minimum variance estimation for a sufficient number of histories and aggregates.« less

  12. Assessing differential gene expression with small sample sizes in oligonucleotide arrays using a mean-variance model.

    PubMed

    Hu, Jianhua; Wright, Fred A

    2007-03-01

    The identification of the genes that are differentially expressed in two-sample microarray experiments remains a difficult problem when the number of arrays is very small. We discuss the implications of using ordinary t-statistics and examine other commonly used variants. For oligonucleotide arrays with multiple probes per gene, we introduce a simple model relating the mean and variance of expression, possibly with gene-specific random effects. Parameter estimates from the model have natural shrinkage properties that guard against inappropriately small variance estimates, and the model is used to obtain a differential expression statistic. A limiting value to the positive false discovery rate (pFDR) for ordinary t-tests provides motivation for our use of the data structure to improve variance estimates. Our approach performs well compared to other proposed approaches in terms of the false discovery rate.

  13. Internet Gaming Disorder Explains Unique Variance in Psychological Distress and Disability After Controlling for Comorbid Depression, OCD, ADHD, and Anxiety.

    PubMed

    Pearcy, Benjamin T D; McEvoy, Peter M; Roberts, Lynne D

    2017-02-01

    This study extends knowledge about the relationship of Internet Gaming Disorder (IGD) to other established mental disorders by exploring comorbidities with anxiety, depression, Attention Deficit Hyperactivity Disorder (ADHD), and obsessive compulsive disorder (OCD), and assessing whether IGD accounts for unique variance in distress and disability. An online survey was completed by a convenience sample that engages in Internet gaming (N = 404). Participants meeting criteria for IGD based on the Personal Internet Gaming Disorder Evaluation-9 (PIE-9) reported higher comorbidity with depression, OCD, ADHD, and anxiety compared with those who did not meet the IGD criteria. IGD explained a small proportion of unique variance in distress (1%) and disability (3%). IGD accounted for a larger proportion of unique variance in disability than anxiety and ADHD, and a similar proportion to depression. Replications with clinical samples using longitudinal designs and structured diagnostic interviews are required.

  14. Genetic and environmental variance in content dimensions of the MMPI.

    PubMed

    Rose, R J

    1988-08-01

    To evaluate genetic and environmental variance in the Minnesota Multiphasic Personality Inventory (MMPI), I studied nine factor scales identified in the first item factor analysis of normal adult MMPIs in a sample of 820 adolescent and young adult co-twins. Conventional twin comparisons documented heritable variance in six of the nine MMPI factors (Neuroticism, Psychoticism, Extraversion, Somatic Complaints, Inadequacy, and Cynicism), whereas significant influence from shared environmental experience was found for four factors (Masculinity versus Femininity, Extraversion, Religious Orthodoxy, and Intellectual Interests). Genetic variance in the nine factors was more evident in results from twin sisters than those of twin brothers, and a developmental-genetic analysis, using hierarchical multiple regressions of double-entry matrixes of the twins' raw data, revealed that in four MMPI factor scales, genetic effects were significantly modulated by age or gender or their interaction during the developmental period from early adolescence to early adulthood.

  15. Attenuating effects of ecosystem management on coral reefs.

    PubMed

    Steneck, Robert S; Mumby, Peter J; MacDonald, Chancey; Rasher, Douglas B; Stoyle, George

    2018-05-01

    Managing diverse ecosystems is challenging because structuring drivers are often processes having diffuse impacts that attenuate from the people who were "managed" to the expected ecosystem-wide outcome. Coral reef fishes targeted for management only indirectly link to the ecosystem's foundation (reef corals). Three successively weakening interaction tiers separate management of fishing from coral abundance. We studied 12 islands along the 700-km eastern Caribbean archipelago, comparing fished and unfished coral reefs. Fishing reduced biomass of carnivorous (snappers and groupers) and herbivorous (parrotfish and surgeonfish) fishes. We document attenuating but important effects of managing fishing, which explained 37% of variance in parrotfish abundance, 20% of variance in harmful algal abundance, and 17% of variance in juvenile coral abundance. The explained variance increased when we quantified herbivory using area-specific bite rates. Local fisheries management resulted in a 62% increase in the archipelago's juvenile coral density, improving the ecosystem's recovery potential from major disturbances.

  16. Empirical Bayes estimation of undercount in the decennial census.

    PubMed

    Cressie, N

    1989-12-01

    Empirical Bayes methods are used to estimate the extent of the undercount at the local level in the 1980 U.S. census. "Grouping of like subareas from areas such as states, counties, and so on into strata is a useful way of reducing the variance of undercount estimators. By modeling the subareas within a stratum to have a common mean and variances inversely proportional to their census counts, and by taking into account sampling of the areas (e.g., by dual-system estimation), empirical Bayes estimators that compromise between the (weighted) stratum average and the sample value can be constructed. The amount of compromise is shown to depend on the relative importance of stratum variance to sampling variance. These estimators are evaluated at the state level (51 states, including Washington, D.C.) and stratified on race/ethnicity (3 strata) using data from the 1980 postenumeration survey (PEP 3-8, for the noninstitutional population)." excerpt

  17. Attenuating effects of ecosystem management on coral reefs

    PubMed Central

    Rasher, Douglas B.; Stoyle, George

    2018-01-01

    Managing diverse ecosystems is challenging because structuring drivers are often processes having diffuse impacts that attenuate from the people who were “managed” to the expected ecosystem-wide outcome. Coral reef fishes targeted for management only indirectly link to the ecosystem’s foundation (reef corals). Three successively weakening interaction tiers separate management of fishing from coral abundance. We studied 12 islands along the 700-km eastern Caribbean archipelago, comparing fished and unfished coral reefs. Fishing reduced biomass of carnivorous (snappers and groupers) and herbivorous (parrotfish and surgeonfish) fishes. We document attenuating but important effects of managing fishing, which explained 37% of variance in parrotfish abundance, 20% of variance in harmful algal abundance, and 17% of variance in juvenile coral abundance. The explained variance increased when we quantified herbivory using area-specific bite rates. Local fisheries management resulted in a 62% increase in the archipelago’s juvenile coral density, improving the ecosystem’s recovery potential from major disturbances. PMID:29750192

  18. Structural and incremental validity of the Wechsler Adult Intelligence Scale-Fourth Edition with a clinical sample.

    PubMed

    Nelson, Jason M; Canivez, Gary L; Watkins, Marley W

    2013-06-01

    Structural and incremental validity of the Wechsler Adult Intelligence Scale-Fourth Edition (WAIS-IV; Wechsler, 2008a) was examined with a sample of 300 individuals referred for evaluation at a university-based clinic. Confirmatory factor analysis indicated that the WAIS-IV structure was best represented by 4 first-order factors as well as a general intelligence factor in a direct hierarchical model. The general intelligence factor accounted for the most common and total variance among the subtests. Incremental validity analyses indicated that the Full Scale IQ (FSIQ) generally accounted for medium to large portions of academic achievement variance. For all measures of academic achievement, the first-order factors combined accounted for significant achievement variance beyond that accounted for by the FSIQ, but individual factor index scores contributed trivial amounts of achievement variance. Implications for interpreting WAIS-IV results are discussed. (PsycINFO Database Record (c) 2013 APA, all rights reserved).

  19. Estimation variance bounds of importance sampling simulations in digital communication systems

    NASA Technical Reports Server (NTRS)

    Lu, D.; Yao, K.

    1991-01-01

    In practical applications of importance sampling (IS) simulation, two basic problems are encountered, that of determining the estimation variance and that of evaluating the proper IS parameters needed in the simulations. The authors derive new upper and lower bounds on the estimation variance which are applicable to IS techniques. The upper bound is simple to evaluate and may be minimized by the proper selection of the IS parameter. Thus, lower and upper bounds on the improvement ratio of various IS techniques relative to the direct Monte Carlo simulation are also available. These bounds are shown to be useful and computationally simple to obtain. Based on the proposed technique, one can readily find practical suboptimum IS parameters. Numerical results indicate that these bounding techniques are useful for IS simulations of linear and nonlinear communication systems with intersymbol interference in which bit error rate and IS estimation variances cannot be obtained readily using prior techniques.

  20. High variance in reproductive success generates a false signature of a genetic bottleneck in populations of constant size: a simulation study

    PubMed Central

    2013-01-01

    Background Demographic bottlenecks can severely reduce the genetic variation of a population or a species. Establishing whether low genetic variation is caused by a bottleneck or a constantly low effective number of individuals is important to understand a species’ ecology and evolution, and it has implications for conservation management. Recent studies have evaluated the power of several statistical methods developed to identify bottlenecks. However, the false positive rate, i.e. the rate with which a bottleneck signal is misidentified in demographically stable populations, has received little attention. We analyse this type of error (type I) in forward computer simulations of stable populations having greater than Poisson variance in reproductive success (i.e., variance in family sizes). The assumption of Poisson variance underlies bottleneck tests, yet it is commonly violated in species with high fecundity. Results With large variance in reproductive success (Vk ≥ 40, corresponding to a ratio between effective and census size smaller than 0.1), tests based on allele frequencies, allelic sizes, and DNA sequence polymorphisms (heterozygosity excess, M-ratio, and Tajima’s D test) tend to show erroneous signals of a bottleneck. Similarly, strong evidence of population decline is erroneously detected when ancestral and current population sizes are estimated with the model based method MSVAR. Conclusions Our results suggest caution when interpreting the results of bottleneck tests in species showing high variance in reproductive success. Particularly in species with high fecundity, computer simulations are recommended to confirm the occurrence of a population bottleneck. PMID:24131797

  1. Correlational structure of ‘frontal’ tests and intelligence tests indicates two components with asymmetrical neurostructural correlates in old age

    PubMed Central

    Cox, Simon R.; MacPherson, Sarah E.; Ferguson, Karen J.; Nissan, Jack; Royle, Natalie A.; MacLullich, Alasdair M.J.; Wardlaw, Joanna M.; Deary, Ian J.

    2014-01-01

    Both general fluid intelligence (gf) and performance on some ‘frontal tests’ of cognition decline with age. Both types of ability are at least partially dependent on the integrity of the frontal lobes, which also deteriorate with age. Overlap between these two methods of assessing complex cognition in older age remains unclear. Such overlap could be investigated using inter-test correlations alone, as in previous studies, but this would be enhanced by ascertaining whether frontal test performance and gf share neurobiological variance. To this end, we examined relationships between gf and 6 frontal tests (Tower, Self-Ordered Pointing, Simon, Moral Dilemmas, Reversal Learning and Faux Pas tests) in 90 healthy males, aged ~ 73 years. We interpreted their correlational structure using principal component analysis, and in relation to MRI-derived regional frontal lobe volumes (relative to maximal healthy brain size). gf correlated significantly and positively (.24 ≤ r ≤ .53) with the majority of frontal test scores. Some frontal test scores also exhibited shared variance after controlling for gf. Principal component analysis of test scores identified units of gf-common and gf-independent variance. The former was associated with variance in the left dorsolateral (DL) and anterior cingulate (AC) regions, and the latter with variance in the right DL and AC regions. Thus, we identify two biologically-meaningful components of variance in complex cognitive performance in older age and suggest that age-related changes to DL and AC have the greatest cognitive impact. PMID:25278641

  2. Shifting patterns of variance in adolescent alcohol use: Testing consumption as a developing trait-state.

    PubMed

    Nealis, Logan J; Thompson, Kara D; Krank, Marvin D; Stewart, Sherry H

    2016-04-01

    While average rates of change in adolescent alcohol consumption are frequently studied, variability arising from situational and dispositional influences on alcohol use has been comparatively neglected. We used variance decomposition to test differences in variability resulting from year-to-year fluctuations in use (i.e., state-like) and from stable individual differences (i.e., trait-like) using data from the Project on Adolescent Trajectories and Health (PATH), a cohort-sequential study spanning grades 7 to 11 using three cohorts starting in grades seven, eight, and nine, respectively. We tested variance components for alcohol volume, frequency, and quantity in the overall sample, and changes in components over time within each cohort. Sex differences were tested. Most variability in alcohol use reflected state-like variation (47-76%), with a relatively smaller proportion of trait-like variation (19-36%). These proportions shifted across cohorts as youth got older, with increases in trait-like variance from early adolescence (14-30%) to later adolescence (30-50%). Trends were similar for males and females, although females showed higher trait-like variance in alcohol frequency than males throughout development (26-43% vs. 11-25%). For alcohol volume and frequency, males showed the greatest increase in trait-like variance earlier in development (i.e., grades 8-10) compared to females (i.e., grades 9-11). The relative strength of situational and dispositional influences on adolescent alcohol use has important implications for preventative interventions. Interventions should ideally target problematic alcohol use before it becomes more ingrained and trait-like. Copyright © 2015 Elsevier Ltd. All rights reserved.

  3. Determining the size of a complete disturbance landscape: multi-scale, continental analysis of forest change.

    PubMed

    Buma, Brian; Costanza, Jennifer K; Riitters, Kurt

    2017-11-21

    The scale of investigation for disturbance-influenced processes plays a critical role in theoretical assumptions about stability, variance, and equilibrium, as well as conservation reserve and long-term monitoring program design. Critical consideration of scale is required for robust planning designs, especially when anticipating future disturbances whose exact locations are unknown. This research quantified disturbance proportion and pattern (as contagion) at multiple scales across North America. This pattern of scale-associated variability can guide selection of study and management extents, for example, to minimize variance (measured as standard deviation) between any landscapes within an ecoregion. We identified the proportion and pattern of forest disturbance (30 m grain size) across multiple landscape extents up to 180 km 2 . We explored the variance in proportion of disturbed area and the pattern of that disturbance between landscapes (within an ecoregion) as a function of the landscape extent. In many ecoregions, variance between landscapes within an ecoregion was minimal at broad landscape extents (low standard deviation). Gap-dominated regions showed the least variance, while fire-dominated showed the largest. Intensively managed ecoregions displayed unique patterns. A majority of the ecoregions showed low variance between landscapes at some scale, indicating an appropriate extent for incorporating natural regimes and unknown future disturbances was identified. The quantification of the scales of disturbance at the ecoregion level provides guidance for individuals interested in anticipating future disturbances which will occur in unknown spatial locations. Information on the extents required to incorporate disturbance patterns into planning is crucial for that process.

  4. Correlational structure of 'frontal' tests and intelligence tests indicates two components with asymmetrical neurostructural correlates in old age.

    PubMed

    Cox, Simon R; MacPherson, Sarah E; Ferguson, Karen J; Nissan, Jack; Royle, Natalie A; MacLullich, Alasdair M J; Wardlaw, Joanna M; Deary, Ian J

    2014-09-01

    Both general fluid intelligence ( g f ) and performance on some 'frontal tests' of cognition decline with age. Both types of ability are at least partially dependent on the integrity of the frontal lobes, which also deteriorate with age. Overlap between these two methods of assessing complex cognition in older age remains unclear. Such overlap could be investigated using inter-test correlations alone, as in previous studies, but this would be enhanced by ascertaining whether frontal test performance and g f share neurobiological variance. To this end, we examined relationships between g f and 6 frontal tests (Tower, Self-Ordered Pointing, Simon, Moral Dilemmas, Reversal Learning and Faux Pas tests) in 90 healthy males, aged ~ 73 years. We interpreted their correlational structure using principal component analysis, and in relation to MRI-derived regional frontal lobe volumes (relative to maximal healthy brain size). g f correlated significantly and positively (.24 ≤  r  ≤ .53) with the majority of frontal test scores. Some frontal test scores also exhibited shared variance after controlling for g f . Principal component analysis of test scores identified units of g f -common and g f -independent variance. The former was associated with variance in the left dorsolateral (DL) and anterior cingulate (AC) regions, and the latter with variance in the right DL and AC regions. Thus, we identify two biologically-meaningful components of variance in complex cognitive performance in older age and suggest that age-related changes to DL and AC have the greatest cognitive impact.

  5. Factors influencing heterogeneity of radiation-induced DNA-damage measured by the alkaline comet assay

    PubMed Central

    2012-01-01

    Background To investigate whether different conditions of DNA structure and radiation treatment could modify heterogeneity of response. Additionally to study variance as a potential parameter of heterogeneity for radiosensitivity testing. Methods Two-hundred leukocytes per sample of healthy donors were split into four groups. I: Intact chromatin structure; II: Nucleoids of histone-depleted DNA; III: Nucleoids of histone-depleted DNA with 90 mM DMSO as antioxidant. Response to single (I-III) and twice (IV) irradiation with 4 Gy and repair kinetics were evaluated using %Tail-DNA. Heterogeneity of DNA damage was determined by calculation of variance of DNA-damage (V) and mean variance (Mvar), mutual comparisons were done by one-way analysis of variance (ANOVA). Results Heterogeneity of initial DNA-damage (I, 0 min repair) increased without histones (II). Absence of histones was balanced by addition of antioxidants (III). Repair reduced heterogeneity of all samples (with and without irradiation). However double irradiation plus repair led to a higher level of heterogeneity distinguishable from single irradiation and repair in intact cells. Increase of mean DNA damage was associated with a similarly elevated variance of DNA damage (r = +0.88). Conclusions Heterogeneity of DNA-damage can be modified by histone level, antioxidant concentration, repair and radiation dose and was positively correlated with DNA damage. Experimental conditions might be optimized by reducing scatter of comet assay data by repair and antioxidants, potentially allowing better discrimination of small differences. Amount of heterogeneity measured by variance might be an additional useful parameter to characterize radiosensitivity. PMID:22520045

  6. On the multiple imputation variance estimator for control-based and delta-adjusted pattern mixture models.

    PubMed

    Tang, Yongqiang

    2017-12-01

    Control-based pattern mixture models (PMM) and delta-adjusted PMMs are commonly used as sensitivity analyses in clinical trials with non-ignorable dropout. These PMMs assume that the statistical behavior of outcomes varies by pattern in the experimental arm in the imputation procedure, but the imputed data are typically analyzed by a standard method such as the primary analysis model. In the multiple imputation (MI) inference, Rubin's variance estimator is generally biased when the imputation and analysis models are uncongenial. One objective of the article is to quantify the bias of Rubin's variance estimator in the control-based and delta-adjusted PMMs for longitudinal continuous outcomes. These PMMs assume the same observed data distribution as the mixed effects model for repeated measures (MMRM). We derive analytic expressions for the MI treatment effect estimator and the associated Rubin's variance in these PMMs and MMRM as functions of the maximum likelihood estimator from the MMRM analysis and the observed proportion of subjects in each dropout pattern when the number of imputations is infinite. The asymptotic bias is generally small or negligible in the delta-adjusted PMM, but can be sizable in the control-based PMM. This indicates that the inference based on Rubin's rule is approximately valid in the delta-adjusted PMM. A simple variance estimator is proposed to ensure asymptotically valid MI inferences in these PMMs, and compared with the bootstrap variance. The proposed method is illustrated by the analysis of an antidepressant trial, and its performance is further evaluated via a simulation study. © 2017, The International Biometric Society.

  7. Simulation of variation of apparent resistivity in resistivity surveys using finite difference modelling with Monte Carlo analysis

    NASA Astrophysics Data System (ADS)

    Aguirre, E. E.; Karchewski, B.

    2017-12-01

    DC resistivity surveying is a geophysical method that quantifies the electrical properties of the subsurface of the earth by applying a source current between two electrodes and measuring potential differences between electrodes at known distances from the source. Analytical solutions for a homogeneous half-space and simple subsurface models are well known, as the former is used to define the concept of apparent resistivity. However, in situ properties are heterogeneous meaning that simple analytical models are only an approximation, and ignoring such heterogeneity can lead to misinterpretation of survey results costing time and money. The present study examines the extent to which random variations in electrical properties (i.e. electrical conductivity) affect potential difference readings and therefore apparent resistivities, relative to an assumed homogeneous subsurface model. We simulate the DC resistivity survey using a Finite Difference (FD) approximation of an appropriate simplification of Maxwell's equations implemented in Matlab. Electrical resistivity values at each node in the simulation were defined as random variables with a given mean and variance, and are assumed to follow a log-normal distribution. The Monte Carlo analysis for a given variance of electrical resistivity was performed until the mean and variance in potential difference measured at the surface converged. Finally, we used the simulation results to examine the relationship between variance in resistivity and variation in surface potential difference (or apparent resistivity) relative to a homogeneous half-space model. For relatively low values of standard deviation in the material properties (<10% of mean), we observed a linear correlation between variance of resistivity and variance in apparent resistivity.

  8. Stabilization of cat paw trajectory during locomotion

    PubMed Central

    Klishko, Alexander N.; Farrell, Bradley J.; Beloozerova, Irina N.; Latash, Mark L.

    2014-01-01

    We investigated which of cat limb kinematic variables during swing of regular walking and accurate stepping along a horizontal ladder are stabilized by coordinated changes of limb segment angles. Three hypotheses were tested: 1) animals stabilize the entire swing trajectory of specific kinematic variables (performance variables); and 2) the level of trajectory stabilization is similar between regular and ladder walking and 3) is higher for forelimbs compared with hindlimbs. We used the framework of the uncontrolled manifold (UCM) hypothesis to quantify the structure of variance of limb kinematics in the limb segment orientation space across steps. Two components of variance were quantified for each potential performance variable, one of which affected it (“bad variance,” variance orthogonal to the UCM, VORT) while the other one did not (“good variance,” variance within the UCM, VUCM). The analysis of five candidate performance variables revealed that cats during both locomotor behaviors stabilize 1) paw vertical position during the entire swing (VUCM > VORT, except in mid-hindpaw swing of ladder walking) and 2) horizontal paw position in initial and terminal swing (except for the entire forepaw swing of regular walking). We also found that the limb length was typically stabilized in midswing, whereas limb orientation was not (VUCM ≤ VORT) for both limbs and behaviors during entire swing. We conclude that stabilization of paw position in early and terminal swing enables accurate and stable locomotion, while stabilization of vertical paw position in midswing helps paw clearance. This study is the first to demonstrate the applicability of the UCM-based analysis to nonhuman movement. PMID:24899676

  9. Hydrograph variances over different timescales in hydropower production networks

    NASA Astrophysics Data System (ADS)

    Zmijewski, Nicholas; Wörman, Anders

    2016-08-01

    The operation of water reservoirs involves a spectrum of timescales based on the distribution of stream flow travel times between reservoirs, as well as the technical, environmental, and social constraints imposed on the operation. In this research, a hydrodynamically based description of the flow between hydropower stations was implemented to study the relative importance of wave diffusion on the spectrum of hydrograph variance in a regulated watershed. Using spectral decomposition of the effluence hydrograph of a watershed, an exact expression of the variance in the outflow response was derived, as a function of the trends of hydraulic and geomorphologic dispersion and management of production and reservoirs. We show that the power spectra of involved time-series follow nearly fractal patterns, which facilitates examination of the relative importance of wave diffusion and possible changes in production demand on the outflow spectrum. The exact spectral solution can also identify statistical bounds of future demand patterns due to limitations in storage capacity. The impact of the hydraulic description of the stream flow on the reservoir discharge was examined for a given power demand in River Dalälven, Sweden, as function of a stream flow Peclet number. The regulation of hydropower production on the River Dalälven generally increased the short-term variance in the effluence hydrograph, whereas wave diffusion decreased the short-term variance over periods of <1 week, depending on the Peclet number (Pe) of the stream reach. This implies that flow variance becomes more erratic (closer to white noise) as a result of current production objectives.

  10. Empirical single sample quantification of bias and variance in Q-ball imaging.

    PubMed

    Hainline, Allison E; Nath, Vishwesh; Parvathaneni, Prasanna; Blaber, Justin A; Schilling, Kurt G; Anderson, Adam W; Kang, Hakmook; Landman, Bennett A

    2018-02-06

    The bias and variance of high angular resolution diffusion imaging methods have not been thoroughly explored in the literature and may benefit from the simulation extrapolation (SIMEX) and bootstrap techniques to estimate bias and variance of high angular resolution diffusion imaging metrics. The SIMEX approach is well established in the statistics literature and uses simulation of increasingly noisy data to extrapolate back to a hypothetical case with no noise. The bias of calculated metrics can then be computed by subtracting the SIMEX estimate from the original pointwise measurement. The SIMEX technique has been studied in the context of diffusion imaging to accurately capture the bias in fractional anisotropy measurements in DTI. Herein, we extend the application of SIMEX and bootstrap approaches to characterize bias and variance in metrics obtained from a Q-ball imaging reconstruction of high angular resolution diffusion imaging data. The results demonstrate that SIMEX and bootstrap approaches provide consistent estimates of the bias and variance of generalized fractional anisotropy, respectively. The RMSE for the generalized fractional anisotropy estimates shows a 7% decrease in white matter and an 8% decrease in gray matter when compared with the observed generalized fractional anisotropy estimates. On average, the bootstrap technique results in SD estimates that are approximately 97% of the true variation in white matter, and 86% in gray matter. Both SIMEX and bootstrap methods are flexible, estimate population characteristics based on single scans, and may be extended for bias and variance estimation on a variety of high angular resolution diffusion imaging metrics. © 2018 International Society for Magnetic Resonance in Medicine.

  11. Shape variation in the human pelvis and limb skeleton: Implications for obstetric adaptation.

    PubMed

    Kurki, Helen K; Decrausaz, Sarah-Louise

    2016-04-01

    Under the obstetrical dilemma (OD) hypothesis, selection acts on the human female pelvis to ensure a sufficiently sized obstetric canal for birthing a large-brained, broad shouldered neonate, while bipedal locomotion selects for a narrower and smaller pelvis. Despite this female-specific stabilizing selection, variability of linear dimensions of the pelvic canal and overall size are not reduced in females, suggesting shape may instead be variable among females of a population. Female canal shape has been shown to vary among populations, while male canal shape does not. Within this context, we examine within-population canal shape variation in comparison with that of noncanal aspects of the pelvis and the limbs. Nine skeletal samples (total female n = 101, male n = 117) representing diverse body sizes and shapes were included. Principal components analysis was applied to size-adjusted variables of each skeletal region. A multivariate variance was calculated using the weighted PC scores for all components in each model and F-ratios used to assess differences in within-population variances between sexes and skeletal regions. Within both sexes, multivariate canal shape variance is significantly greater than noncanal pelvis and limb variances, while limb variance is greater than noncanal pelvis variance in some populations. Multivariate shape variation is not consistently different between the sexes in any of the skeletal regions. Diverse selective pressures, including obstetrics, locomotion, load carrying, and others may act on canal shape, as well as genetic drift and plasticity, thus increasing variation in morphospace while protecting obstetric sufficiency. © 2015 Wiley Periodicals, Inc.

  12. More than Drought: Precipitation Variance, Excessive Wetness, Pathogens and the Future of the Western Edge of the Eastern Deciduous Forest.

    PubMed

    Hubbart, Jason A; Guyette, Richard; Muzika, Rose-Marie

    2016-10-01

    For many regions of the Earth, anthropogenic climate change is expected to result in increasingly divergent climate extremes. However, little is known about how increasing climate variance may affect ecosystem productivity. Forest ecosystems may be particularly susceptible to this problem considering the complex organizational structure of specialized species niche adaptations. Forest decline is often attributable to multiple stressors including prolonged heat, wildfire and insect outbreaks. These disturbances, often categorized as megadisturbances, can push temperate forests beyond sustainability thresholds. Absent from much of the contemporary forest health literature, however, is the discussion of excessive precipitation that may affect other disturbances synergistically or that might represent a principal stressor. Here, specific points of evidence are provided including historic climatology, variance predictions from global change modeling, Midwestern paleo climate data, local climate influences on net ecosystem exchange and productivity, and pathogen influences on oak mortality. Data sources reveal potential trends, deserving further investigation, indicating that the western edge of the Eastern Deciduous forest may be impacted by ongoing increased precipitation, precipitation variance and excessive wetness. Data presented, in conjunction with recent regional forest health concerns, suggest that climate variance including drought and excessive wetness should be equally considered for forest ecosystem resilience against increasingly dynamic climate. This communication serves as an alert to the need for studies on potential impacts of increasing climate variance and excessive wetness in forest ecosystem health and productivity in the Midwest US and similar forest ecosystems globally. Copyright © 2016 Elsevier B.V. All rights reserved.

  13. The Role of Rainfall Patterns in Seasonal Malaria Transmission

    NASA Astrophysics Data System (ADS)

    Bomblies, A.

    2010-12-01

    Seasonal total precipitation is well known to affect malaria transmission because Anopheles mosquitoes depend on standing water for breeding habitat. However, the within-season temporal pattern of the rainfall influences persistence of standing water and thus rainfall patterns also affect mosquito population dynamics. In this talk, I show that intraseasonal rainfall pattern describes 40% of the variance in simulated mosquito abundance in a Niger Sahel village where malaria is endemic but highly seasonal, demonstrating the necessity for detailed distributed hydrology modeling to explain the variance from this important effect. I apply a field validated, high spatial- and temporal-resolution hydrology model coupled with an entomology model. Using synthetic rainfall time series generated using a stationary first-order Markov Chain model, I hold all variables except hourly rainfall constant, thus isolating the contribution of rainfall pattern to variance in mosquito abundance. I further show the utility of hydrology modeling to assess precipitation effects by analyzing collected water. Time-integrated surface area of pools explains 70% of the variance in mosquito abundance, and time-integrated surface area of pools persisting longer than seven days explains 82% of the variance, showing an improved predictive ability when pool persistence is explicitly modeled at high spatio-temporal resolution. I extend this analysis to investigate the impacts of this effect on malaria vector mosquito populations under climate shift scenarios, holding all climate variables except precipitation constant. In these scenarios, rainfall mean and variance change with climatic change, and the modeling approach evaluates the impact of non-stationarity in rainfall and the associated rainfall patterns on expected mosquito activity.

  14. Adaptive cyclic physiologic noise modeling and correction in functional MRI.

    PubMed

    Beall, Erik B

    2010-03-30

    Physiologic noise in BOLD-weighted MRI data is known to be a significant source of the variance, reducing the statistical power and specificity in fMRI and functional connectivity analyses. We show a dramatic improvement on current noise correction methods in both fMRI and fcMRI data that avoids overfitting. The traditional noise model is a Fourier series expansion superimposed on the periodicity of parallel measured breathing and cardiac cycles. Correction using this model results in removal of variance matching the periodicity of the physiologic cycles. Using this framework allows easy modeling of noise. However, using a large number of regressors comes at the cost of removing variance unrelated to physiologic noise, such as variance due to the signal of functional interest (overfitting the data). It is our hypothesis that there are a small variety of fits that describe all of the significantly coupled physiologic noise. If this is true, we can replace a large number of regressors used in the model with a smaller number of the fitted regressors and thereby account for the noise sources with a smaller reduction in variance of interest. We describe these extensions and demonstrate that we can preserve variance in the data unrelated to physiologic noise while removing physiologic noise equivalently, resulting in data with a higher effective SNR than with current corrections techniques. Our results demonstrate a significant improvement in the sensitivity of fMRI (up to a 17% increase in activation volume for fMRI compared with higher order traditional noise correction) and functional connectivity analyses. Copyright (c) 2010 Elsevier B.V. All rights reserved.

  15. 7 CFR 205.290 - Temporary variances.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 7 Agriculture 3 2010-01-01 2010-01-01 false Temporary variances. 205.290 Section 205.290 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE (CONTINUED) ORGANIC FOODS PRODUCTION ACT...

  16. Teaching Principles of Inference with ANOVA

    ERIC Educational Resources Information Center

    Tarlow, Kevin R.

    2016-01-01

    Analysis of variance (ANOVA) is a test of "mean" differences, but the reference to "variances" in the name is often overlooked. Classroom activities are presented to illustrate how ANOVA works with emphasis on how to think critically about inferential reasoning.

  17. Control algorithms for dynamic attenuators.

    PubMed

    Hsieh, Scott S; Pelc, Norbert J

    2014-06-01

    The authors describe algorithms to control dynamic attenuators in CT and compare their performance using simulated scans. Dynamic attenuators are prepatient beam shaping filters that modulate the distribution of x-ray fluence incident on the patient on a view-by-view basis. These attenuators can reduce dose while improving key image quality metrics such as peak or mean variance. In each view, the attenuator presents several degrees of freedom which may be individually adjusted. The total number of degrees of freedom across all views is very large, making many optimization techniques impractical. The authors develop a theory for optimally controlling these attenuators. Special attention is paid to a theoretically perfect attenuator which controls the fluence for each ray individually, but the authors also investigate and compare three other, practical attenuator designs which have been previously proposed: the piecewise-linear attenuator, the translating attenuator, and the double wedge attenuator. The authors pose and solve the optimization problems of minimizing the mean and peak variance subject to a fixed dose limit. For a perfect attenuator and mean variance minimization, this problem can be solved in simple, closed form. For other attenuator designs, the problem can be decomposed into separate problems for each view to greatly reduce the computational complexity. Peak variance minimization can be approximately solved using iterated, weighted mean variance (WMV) minimization. Also, the authors develop heuristics for the perfect and piecewise-linear attenuators which do not require a priori knowledge of the patient anatomy. The authors compare these control algorithms on different types of dynamic attenuators using simulated raw data from forward projected DICOM files of a thorax and an abdomen. The translating and double wedge attenuators reduce dose by an average of 30% relative to current techniques (bowtie filter with tube current modulation) without increasing peak variance. The 15-element piecewise-linear dynamic attenuator reduces dose by an average of 42%, and the perfect attenuator reduces dose by an average of 50%. Improvements in peak variance are several times larger than improvements in mean variance. Heuristic control eliminates the need for a prescan. For the piecewise-linear attenuator, the cost of heuristic control is an increase in dose of 9%. The proposed iterated WMV minimization produces results that are within a few percent of the true solution. Dynamic attenuators show potential for significant dose reduction. A wide class of dynamic attenuators can be accurately controlled using the described methods.

  18. Non-destructive X-ray Computed Tomography (XCT) Analysis of Sediment Variance in Marine Cores

    NASA Astrophysics Data System (ADS)

    Oti, E.; Polyak, L. V.; Dipre, G.; Sawyer, D.; Cook, A.

    2015-12-01

    Benthic activity within marine sediments can alter the physical properties of the sediment as well as indicate nutrient flux and ocean temperatures. We examine burrowing features in sediment cores from the western Arctic Ocean collected during the 2005 Healy-Oden TransArctic Expedition (HOTRAX) and from the Gulf of Mexico Integrated Ocean Drilling Program (IODP) Expedition 308. While traditional methods for studying bioturbation require physical dissection of the cores, we assess burrowing using an X-ray computed tomography (XCT) scanner. XCT noninvasively images the sediment cores in three dimensions and produces density sensitive images suitable for quantitative analysis. XCT units are recorded as Hounsfield Units (HU), where -999 is air, 0 is water, and 4000-5000 would be a higher density mineral, such as pyrite. We rely on the fundamental assumption that sediments are deposited horizontally, and we analyze the variance over each flat-lying slice. The variance describes the spread of pixel values over a slice. When sediments are reworked, drawing higher and lower density matrix into a layer, the variance increases. Examples of this can be seen in two slices in core 19H-3A from Site U1324 of IODP Expedition 308. The first slice, located 165.6 meters below sea floor consists of relatively undisturbed sediment. Because of this, the majority of the sediment values fall between 1406 and 1497 HU, thus giving the slice a comparatively small variance of 819.7. The second slice, located 166.1 meters below sea floor, features a lower density sediment matrix disturbed by burrow tubes and the inclusion of a high density mineral. As a result, the Hounsfield Units have a larger variance of 1,197.5, which is a result of sediment matrix values that range from 1220 to 1260 HU, the high-density mineral value of 1920 HU and the burrow tubes that range from 1300 to 1410 HU. Analyzing this variance allows us to observe changes in the sediment matrix and more specifically capture where, and to what extent, the burrow tubes deviate from the sediment matrix. Future research will correlate changes in variance due to bioturbation to other features indicating ocean temperatures and nutrient flux, such as foraminifera counts and oxygen isotope data.

  19. Measuring kinetics of complex single ion channel data using mean-variance histograms.

    PubMed

    Patlak, J B

    1993-07-01

    The measurement of single ion channel kinetics is difficult when those channels exhibit subconductance events. When the kinetics are fast, and when the current magnitudes are small, as is the case for Na+, Ca2+, and some K+ channels, these difficulties can lead to serious errors in the estimation of channel kinetics. I present here a method, based on the construction and analysis of mean-variance histograms, that can overcome these problems. A mean-variance histogram is constructed by calculating the mean current and the current variance within a brief "window" (a set of N consecutive data samples) superimposed on the digitized raw channel data. Systematic movement of this window over the data produces large numbers of mean-variance pairs which can be assembled into a two-dimensional histogram. Defined current levels (open, closed, or sublevel) appear in such plots as low variance regions. The total number of events in such low variance regions is estimated by curve fitting and plotted as a function of window width. This function decreases with the same time constants as the original dwell time probability distribution for each of the regions. The method can therefore be used: 1) to present a qualitative summary of the single channel data from which the signal-to-noise ratio, open channel noise, steadiness of the baseline, and number of conductance levels can be quickly determined; 2) to quantify the dwell time distribution in each of the levels exhibited. In this paper I present the analysis of a Na+ channel recording that had a number of complexities. The signal-to-noise ratio was only about 8 for the main open state, open channel noise, and fast flickers to other states were present, as were a substantial number of subconductance states. "Standard" half-amplitude threshold analysis of these data produce open and closed time histograms that were well fitted by the sum of two exponentials, but with apparently erroneous time constants, whereas the mean-variance histogram technique provided a more credible analysis of the open, closed, and subconductance times for the patch. I also show that the method produces accurate results on simulated data in a wide variety of conditions, whereas the half-amplitude method, when applied to complex simulated data shows the same errors as were apparent in the real data. The utility and the limitations of this new method are discussed.

  20. Improved classification accuracy in 1- and 2-dimensional NMR metabolomics data using the variance stabilising generalised logarithm transformation

    PubMed Central

    Parsons, Helen M; Ludwig, Christian; Günther, Ulrich L; Viant, Mark R

    2007-01-01

    Background Classifying nuclear magnetic resonance (NMR) spectra is a crucial step in many metabolomics experiments. Since several multivariate classification techniques depend upon the variance of the data, it is important to first minimise any contribution from unwanted technical variance arising from sample preparation and analytical measurements, and thereby maximise any contribution from wanted biological variance between different classes. The generalised logarithm (glog) transform was developed to stabilise the variance in DNA microarray datasets, but has rarely been applied to metabolomics data. In particular, it has not been rigorously evaluated against other scaling techniques used in metabolomics, nor tested on all forms of NMR spectra including 1-dimensional (1D) 1H, projections of 2D 1H, 1H J-resolved (pJRES), and intact 2D J-resolved (JRES). Results Here, the effects of the glog transform are compared against two commonly used variance stabilising techniques, autoscaling and Pareto scaling, as well as unscaled data. The four methods are evaluated in terms of the effects on the variance of NMR metabolomics data and on the classification accuracy following multivariate analysis, the latter achieved using principal component analysis followed by linear discriminant analysis. For two of three datasets analysed, classification accuracies were highest following glog transformation: 100% accuracy for discriminating 1D NMR spectra of hypoxic and normoxic invertebrate muscle, and 100% accuracy for discriminating 2D JRES spectra of fish livers sampled from two rivers. For the third dataset, pJRES spectra of urine from two breeds of dog, the glog transform and autoscaling achieved equal highest accuracies. Additionally we extended the glog algorithm to effectively suppress noise, which proved critical for the analysis of 2D JRES spectra. Conclusion We have demonstrated that the glog and extended glog transforms stabilise the technical variance in NMR metabolomics datasets. This significantly improves the discrimination between sample classes and has resulted in higher classification accuracies compared to unscaled, autoscaled or Pareto scaled data. Additionally we have confirmed the broad applicability of the glog approach using three disparate datasets from different biological samples using 1D NMR spectra, 1D projections of 2D JRES spectra, and intact 2D JRES spectra. PMID:17605789

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