Science.gov

Sample records for additional statistical methods

  1. Testing for Additivity at Select Mixture Groups of Interest Based on Statistical Equivalence Testing Methods

    SciTech Connect

    Stork, LeAnna M.; Gennings, Chris; Carchman, Richard; Carter, Jr., Walter H.; Pounds, Joel G.; Mumtaz, Moiz

    2006-12-01

    Several assumptions, defined and undefined, are used in the toxicity assessment of chemical mixtures. In scientific practice mixture components in the low-dose region, particularly subthreshold doses, are often assumed to behave additively (i.e., zero interaction) based on heuristic arguments. This assumption has important implications in the practice of risk assessment, but has not been experimentally tested. We have developed methodology to test for additivity in the sense of Berenbaum (Advances in Cancer Research, 1981), based on the statistical equivalence testing literature where the null hypothesis of interaction is rejected for the alternative hypothesis of additivity when data support the claim. The implication of this approach is that conclusions of additivity are made with a false positive rate controlled by the experimenter. The claim of additivity is based on prespecified additivity margins, which are chosen using expert biological judgment such that small deviations from additivity, which are not considered to be biologically important, are not statistically significant. This approach is in contrast to the usual hypothesis-testing framework that assumes additivity in the null hypothesis and rejects when there is significant evidence of interaction. In this scenario, failure to reject may be due to lack of statistical power making the claim of additivity problematic. The proposed method is illustrated in a mixture of five organophosphorus pesticides that were experimentally evaluated alone and at relevant mixing ratios. Motor activity was assessed in adult male rats following acute exposure. Four low-dose mixture groups were evaluated. Evidence of additivity is found in three of the four low-dose mixture groups.The proposed method tests for additivity of the whole mixture and does not take into account subset interactions (e.g., synergistic, antagonistic) that may have occurred and cancelled each other out.

  2. Statistical addition method for external noise sources affecting HF-MF-LF systems

    NASA Astrophysics Data System (ADS)

    Neudegg, David

    2001-01-01

    The current statistical method for the addition of external component noise sources in the LF, MF, and lower HF band (100 kHz to 3 MHz) produces total median noise levels that may be less than the largest-component median in some cases. Several case studies illustrate this anomaly. Methods used to sum the components rely on their power (decibels) distributions being represented as normal by the statistical parameters. The atmospheric noise component is not correctly represented by its decile values when it is assumed to have a normal distribution, causing anomalies in the noise summation when components are similar in magnitude. A revised component summation method is proposed, and the way it provides a more physically realistic total noise median for LF, MF, and lower HF frequencies is illustrated.

  3. Statistical Methods for Astronomy

    NASA Astrophysics Data System (ADS)

    Feigelson, Eric D.; Babu, G. Jogesh

    Statistical methodology, with deep roots in probability theory, providesquantitative procedures for extracting scientific knowledge from astronomical dataand for testing astrophysical theory. In recent decades, statistics has enormouslyincreased in scope and sophistication. After a historical perspective, this reviewoutlines concepts of mathematical statistics, elements of probability theory,hypothesis tests, and point estimation. Least squares, maximum likelihood, andBayesian approaches to statistical inference are outlined. Resampling methods,particularly the bootstrap, provide valuable procedures when distributionsfunctions of statistics are not known. Several approaches to model selection andgoodness of fit are considered.

  4. Testing for Additivity in Chemical Mixtures Using a Fixed-Ratio Ray Design and Statistical Equivalence Testing Methods

    EPA Science Inventory

    Fixed-ratio ray designs have been used for detecting and characterizing interactions of large numbers of chemicals in combination. Single chemical dose-response data are used to predict an “additivity curve” along an environmentally relevant ray. A “mixture curve” is estimated fr...

  5. Statistical Methods in Cosmology

    NASA Astrophysics Data System (ADS)

    Verde, L.

    2010-03-01

    The advent of large data-set in cosmology has meant that in the past 10 or 20 years our knowledge and understanding of the Universe has changed not only quantitatively but also, and most importantly, qualitatively. Cosmologists rely on data where a host of useful information is enclosed, but is encoded in a non-trivial way. The challenges in extracting this information must be overcome to make the most of a large experimental effort. Even after having converged to a standard cosmological model (the LCDM model) we should keep in mind that this model is described by 10 or more physical parameters and if we want to study deviations from it, the number of parameters is even larger. Dealing with such a high dimensional parameter space and finding parameters constraints is a challenge on itself. Cosmologists want to be able to compare and combine different data sets both for testing for possible disagreements (which could indicate new physics) and for improving parameter determinations. Finally, cosmologists in many cases want to find out, before actually doing the experiment, how much one would be able to learn from it. For all these reasons, sophisiticated statistical techniques are being employed in cosmology, and it has become crucial to know some statistical background to understand recent literature in the field. I will introduce some statistical tools that any cosmologist should know about in order to be able to understand recently published results from the analysis of cosmological data sets. I will not present a complete and rigorous introduction to statistics as there are several good books which are reported in the references. The reader should refer to those.

  6. Statistical Methods in Psychology Journals.

    ERIC Educational Resources Information Center

    Willkinson, Leland

    1999-01-01

    Proposes guidelines for revising the American Psychological Association (APA) publication manual or other APA materials to clarify the application of statistics in research reports. The guidelines are intended to induce authors and editors to recognize the thoughtless application of statistical methods. Contains 54 references. (SLD)

  7. Statistical methods for evolutionary trees.

    PubMed

    Edwards, A W F

    2009-09-01

    In 1963 and 1964, L. L. Cavalli-Sforza and A. W. F. Edwards introduced novel methods for computing evolutionary trees from genetical data, initially for human populations from blood-group gene frequencies. The most important development was their introduction of statistical methods of estimation applied to stochastic models of evolution.

  8. Statistical tests of additional plate boundaries from plate motion inversions

    NASA Technical Reports Server (NTRS)

    Stein, S.; Gordon, R. G.

    1984-01-01

    The application of the F-ratio test, a standard statistical technique, to the results of relative plate motion inversions has been investigated. The method tests whether the improvement in fit of the model to the data resulting from the addition of another plate to the model is greater than that expected purely by chance. This approach appears to be useful in determining whether additional plate boundaries are justified. Previous results have been confirmed favoring separate North American and South American plates with a boundary located beween 30 N and the equator. Using Chase's global relative motion data, it is shown that in addition to separate West African and Somalian plates, separate West Indian and Australian plates, with a best-fitting boundary between 70 E and 90 E, can be resolved. These results are generally consistent with the observation that the Indian plate's internal deformation extends somewhat westward of the Ninetyeast Ridge. The relative motion pole is similar to Minster and Jordan's and predicts the NW-SE compression observed in earthquake mechanisms near the Ninetyeast Ridge.

  9. Statistical Methods for Cardiovascular Researchers

    PubMed Central

    Moyé, Lem

    2016-01-01

    Rationale Biostatistics continues to play an essential role in contemporary cardiovascular investigations, but successful implementation of biostatistical methods can be complex. Objective To present the rationale behind statistical applications and to review useful tools for cardiology research. Methods and Results Prospective declaration of the research question, clear methodology, and study execution that adheres to the protocol together serve as the critical foundation of a research endeavor. Both parametric and distribution-free measures of central tendency and dispersion are presented. T-testing, analysis of variance, and regression analyses are reviewed. Survival analysis, logistic regression, and interim monitoring are also discussed. Finally, common weaknesses in statistical analyses are considered. Conclusion Biostatistics can be productively applied to cardiovascular research if investigators 1) develop and rely on a well-written protocol and analysis plan, 2) consult with a biostatistician when necessary, and 3) write results clearly, differentiating confirmatory from exploratory findings. PMID:26846639

  10. Bond additivity corrections for quantum chemistry methods

    SciTech Connect

    Melius, C.F.; Allendorf, M.D.

    2000-03-23

    New bond additivity correction (BAC) methods have been developed for the G2 method, BAC-G2, as well as for a hybrid density functional theory (DFT) Moller-Plesset (MP)2 method, BAC-hybrid. These BAC methods use a new form of BAC corrections, involving atomic, molecular, and bond-wise additive terms. These terms enable one to treat positive and negative ions as well as neutrals. The BAC-G2 method reduces errors in the G2 method due to nearest-neighbor bonds. The parameters within the BAC-G2 method only depend on atom types. Thus the BAC-G2 method can be used to determine the parameters needed by BAC methods involving lower levels of theory, such as BAC-hybrid and BAC-MP4. The BAC-hybrid method is expected to scale well for large molecules. The BAC-hybrid method uses the differences between the DFT and MP2 predictions as an indication of the method's accuracy, whereas the BAC-G2 method uses its internal methods (G1 and G2MP2) to accomplish this. A statistical analysis of the error in each of the methods is presented on the basis of calculations performed for large sets (more than 120) of molecules.

  11. Statistical methods in physical mapping

    SciTech Connect

    Nelson, David O.

    1995-05-01

    One of the great success stories of modern molecular genetics has been the ability of biologists to isolate and characterize the genes responsible for serious inherited diseases like fragile X syndrome, cystic fibrosis and myotonic muscular dystrophy. This dissertation concentrates on constructing high-resolution physical maps. It demonstrates how probabilistic modeling and statistical analysis can aid molecular geneticists in the tasks of planning, execution, and evaluation of physical maps of chromosomes and large chromosomal regions. The dissertation is divided into six chapters. Chapter 1 provides an introduction to the field of physical mapping, describing the role of physical mapping in gene isolation and ill past efforts at mapping chromosomal regions. The next two chapters review and extend known results on predicting progress in large mapping projects. Such predictions help project planners decide between various approaches and tactics for mapping large regions of the human genome. Chapter 2 shows how probability models have been used in the past to predict progress in mapping projects. Chapter 3 presents new results, based on stationary point process theory, for progress measures for mapping projects based on directed mapping strategies. Chapter 4 describes in detail the construction of all initial high-resolution physical map for human chromosome 19. This chapter introduces the probability and statistical models involved in map construction in the context of a large, ongoing physical mapping project. Chapter 5 concentrates on one such model, the trinomial model. This chapter contains new results on the large-sample behavior of this model, including distributional results, asymptotic moments, and detection error rates. In addition, it contains an optimality result concerning experimental procedures based on the trinomial model. The last chapter explores unsolved problems and describes future work.

  12. Modern Statistical Methods for Astronomy

    NASA Astrophysics Data System (ADS)

    Feigelson, Eric D.; Babu, G. Jogesh

    2012-07-01

    1. Introduction; 2. Probability; 3. Statistical inference; 4. Probability distribution functions; 5. Nonparametric statistics; 6. Density estimation or data smoothing; 7. Regression; 8. Multivariate analysis; 9. Clustering, classification and data mining; 10. Nondetections: censored and truncated data; 11. Time series analysis; 12. Spatial point processes; Appendices; Index.

  13. Weak additivity principle for current statistics in d dimensions.

    PubMed

    Pérez-Espigares, C; Garrido, P L; Hurtado, P I

    2016-04-01

    The additivity principle (AP) allows one to compute the current distribution in many one-dimensional nonequilibrium systems. Here we extend this conjecture to general d-dimensional driven diffusive systems, and validate its predictions against both numerical simulations of rare events and microscopic exact calculations of three paradigmatic models of diffusive transport in d=2. Crucially, the existence of a structured current vector field at the fluctuating level, coupled to the local mobility, turns out to be essential to understand current statistics in d>1. We prove that, when compared to the straightforward extension of the AP to high d, the so-called weak AP always yields a better minimizer of the macroscopic fluctuation theory action for current statistics.

  14. Statistical methods in translational medicine.

    PubMed

    Chow, Shein-Chung; Tse, Siu-Keung; Lin, Min

    2008-12-01

    This study focuses on strategies and statistical considerations for assessment of translation in language (e.g. translation of case report forms in multinational clinical trials), information (e.g. translation of basic discoveries to the clinic) and technology (e.g. translation of Chinese diagnostic techniques to well-established clinical study endpoints) in pharmaceutical/clinical research and development. However, most of our efforts will be directed to statistical considerations for translation in information. Translational medicine has been defined as bench-to-bedside research, where a basic laboratory discovery becomes applicable to the diagnosis, treatment or prevention of a specific disease, and is brought forth by either a physicianscientist who works at the interface between the research laboratory and patient care, or by a team of basic and clinical science investigators. Statistics plays an important role in translational medicine to ensure that the translational process is accurate and reliable with certain statistical assurance. Statistical inference for the applicability of an animal model to a human model is also discussed. Strategies for selection of clinical study endpoints (e.g. absolute changes, relative changes, or responder-defined, based on either absolute or relative change) are reviewed.

  15. Recent statistical methods for orientation data

    NASA Technical Reports Server (NTRS)

    Batschelet, E.

    1972-01-01

    The application of statistical methods for determining the areas of animal orientation and navigation are discussed. The method employed is limited to the two-dimensional case. Various tests for determining the validity of the statistical analysis are presented. Mathematical models are included to support the theoretical considerations and tables of data are developed to show the value of information obtained by statistical analysis.

  16. Statistical methods for nuclear material management

    SciTech Connect

    Bowen W.M.; Bennett, C.A.

    1988-12-01

    This book is intended as a reference manual of statistical methodology for nuclear material management practitioners. It describes statistical methods currently or potentially important in nuclear material management, explains the choice of methods for specific applications, and provides examples of practical applications to nuclear material management problems. Together with the accompanying training manual, which contains fully worked out problems keyed to each chapter, this book can also be used as a textbook for courses in statistical methods for nuclear material management. It should provide increased understanding and guidance to help improve the application of statistical methods to nuclear material management problems.

  17. Robust statistical methods for automated outlier detection

    NASA Technical Reports Server (NTRS)

    Jee, J. R.

    1987-01-01

    The computational challenge of automating outlier, or blunder point, detection in radio metric data requires the use of nonstandard statistical methods because the outliers have a deleterious effect on standard least squares methods. The particular nonstandard methods most applicable to the task are the robust statistical techniques that have undergone intense development since the 1960s. These new methods are by design more resistant to the effects of outliers than standard methods. Because the topic may be unfamiliar, a brief introduction to the philosophy and methods of robust statistics is presented. Then the application of these methods to the automated outlier detection problem is detailed for some specific examples encountered in practice.

  18. Some useful statistical methods for model validation.

    PubMed Central

    Marcus, A H; Elias, R W

    1998-01-01

    Although formal hypothesis tests provide a convenient framework for displaying the statistical results of empirical comparisons, standard tests should not be used without consideration of underlying measurement error structure. As part of the validation process, predictions of individual blood lead concentrations from models with site-specific input parameters are often compared with blood lead concentrations measured in field studies that also report lead concentrations in environmental media (soil, dust, water, paint) as surrogates for exposure. Measurements of these environmental media are subject to several sources of variability, including temporal and spatial sampling, sample preparation and chemical analysis, and data entry or recording. Adjustments for measurement error must be made before statistical tests can be used to empirically compare environmental data with model predictions. This report illustrates the effect of measurement error correction using a real dataset of child blood lead concentrations for an undisclosed midwestern community. We illustrate both the apparent failure of some standard regression tests and the success of adjustment of such tests for measurement error using the SIMEX (simulation-extrapolation) procedure. This procedure adds simulated measurement error to model predictions and then subtracts the total measurement error, analogous to the method of standard additions used by analytical chemists. Images Figure 1 Figure 3 PMID:9860913

  19. Statistical Methods for Environmental Pollution Monitoring

    SciTech Connect

    Gilbert, Richard O.

    1987-01-01

    The application of statistics to environmental pollution monitoring studies requires a knowledge of statistical analysis methods particularly well suited to pollution data. This book fills that need by providing sampling plans, statistical tests, parameter estimation procedure techniques, and references to pertinent publications. Most of the statistical techniques are relatively simple, and examples, exercises, and case studies are provided to illustrate procedures. The book is logically divided into three parts. Chapters 1, 2, and 3 are introductory chapters. Chapters 4 through 10 discuss field sampling designs and Chapters 11 through 18 deal with a broad range of statistical analysis procedures. Some statistical techniques given here are not commonly seen in statistics book. For example, see methods for handling correlated data (Sections 4.5 and 11.12), for detecting hot spots (Chapter 10), and for estimating a confidence interval for the mean of a lognormal distribution (Section 13.2). Also, Appendix B lists a computer code that estimates and tests for trends over time at one or more monitoring stations using nonparametric methods (Chapters 16 and 17). Unfortunately, some important topics could not be included because of their complexity and the need to limit the length of the book. For example, only brief mention could be made of time series analysis using Box-Jenkins methods and of kriging techniques for estimating spatial and spatial-time patterns of pollution, although multiple references on these topics are provided. Also, no discussion of methods for assessing risks from environmental pollution could be included.

  20. Seasonal UK Drought Forecasting using Statistical Methods

    NASA Astrophysics Data System (ADS)

    Richardson, Doug; Fowler, Hayley; Kilsby, Chris; Serinaldi, Francesco

    2016-04-01

    In the UK drought is a recurrent feature of climate with potentially large impacts on public water supply. Water companies' ability to mitigate the impacts of drought by managing diminishing availability depends on forward planning and it would be extremely valuable to improve forecasts of drought on monthly to seasonal time scales. By focusing on statistical forecasting methods, this research aims to provide techniques that are simpler, faster and computationally cheaper than physically based models. In general, statistical forecasting is done by relating the variable of interest (some hydro-meteorological variable such as rainfall or streamflow, or a drought index) to one or more predictors via some formal dependence. These predictors are generally antecedent values of the response variable or external factors such as teleconnections. A candidate model is Generalised Additive Models for Location, Scale and Shape parameters (GAMLSS). GAMLSS is a very flexible class allowing for more general distribution functions (e.g. highly skewed and/or kurtotic distributions) and the modelling of not just the location parameter but also the scale and shape parameters. Additionally GAMLSS permits the forecasting of an entire distribution, allowing the output to be assessed in probabilistic terms rather than simply the mean and confidence intervals. Exploratory analysis of the relationship between long-memory processes (e.g. large-scale atmospheric circulation patterns, sea surface temperatures and soil moisture content) and drought should result in the identification of suitable predictors to be included in the forecasting model, and further our understanding of the drivers of UK drought.

  1. Modern statistical methods in respiratory medicine.

    PubMed

    Wolfe, Rory; Abramson, Michael J

    2014-01-01

    Statistics sits right at the heart of scientific endeavour in respiratory medicine and many other disciplines. In this introductory article, some key epidemiological concepts such as representativeness, random sampling, association and causation, and confounding are reviewed. A brief introduction to basic statistics covering topics such as frequentist methods, confidence intervals, hypothesis testing, P values and Type II error is provided. Subsequent articles in this series will cover some modern statistical methods including regression models, analysis of repeated measures, causal diagrams, propensity scores, multiple imputation, accounting for measurement error, survival analysis, risk prediction, latent class analysis and meta-analysis.

  2. Tsallis statistics in reliability analysis: Theory and methods

    NASA Astrophysics Data System (ADS)

    Zhang, Fode; Shi, Yimin; Keung Tony Ng, Hon; Wang, Ruibing

    2016-10-01

    Tsallis statistics, which is based on a non-additive entropy characterized by an index q, is a very useful tool in physics and statistical mechanics. This paper presents an application of Tsallis statistics in reliability analysis. We first show that the q-gamma and incomplete q-gamma functions are q-generalized. Then, three commonly used statistical distributions in reliability analysis are introduced in Tsallis statistics, and the corresponding reliability characteristics including the reliability function, hazard function, cumulative hazard function and mean time to failure are investigated. In addition, we study the statistical inference based on censored reliability data. Specifically, we investigate the point and interval estimation of the model parameters of the q-exponential distribution based on the maximum likelihood method. Simulated and real-life datasets are used to illustrate the methodologies discussed in this paper. Finally, some concluding remarks are provided.

  3. Component outage data analysis methods. Volume 2: Basic statistical methods

    NASA Astrophysics Data System (ADS)

    Marshall, J. A.; Mazumdar, M.; McCutchan, D. A.

    1981-08-01

    Statistical methods for analyzing outage data on major power system components such as generating units, transmission lines, and transformers are identified. The analysis methods produce outage statistics from component failure and repair data that help in understanding the failure causes and failure modes of various types of components. Methods for forecasting outage statistics for those components used in the evaluation of system reliability are emphasized.

  4. Bond additivity corrections for quantum chemistry methods

    SciTech Connect

    C. F. Melius; M. D. Allendorf

    1999-04-01

    In the 1980's, the authors developed a bond-additivity correction procedure for quantum chemical calculations called BAC-MP4, which has proven reliable in calculating the thermochemical properties of molecular species, including radicals as well as stable closed-shell species. New Bond Additivity Correction (BAC) methods have been developed for the G2 method, BAC-G2, as well as for a hybrid DFT/MP2 method, BAC-Hybrid. These BAC methods use a new form of BAC corrections, involving atomic, molecular, and bond-wise additive terms. These terms enable one to treat positive and negative ions as well as neutrals. The BAC-G2 method reduces errors in the G2 method due to nearest-neighbor bonds. The parameters within the BAC-G2 method only depend on atom types. Thus the BAC-G2 method can be used to determine the parameters needed by BAC methods involving lower levels of theory, such as BAC-Hybrid and BAC-MP4. The BAC-Hybrid method should scale well for large molecules. The BAC-Hybrid method uses the differences between the DFT and MP2 as an indicator of the method's accuracy, while the BAC-G2 method uses its internal methods (G1 and G2MP2) to provide an indicator of its accuracy. Indications of the average error as well as worst cases are provided for each of the BAC methods.

  5. Multiobjective Statistical Method for Interior Drainage Systems

    NASA Astrophysics Data System (ADS)

    Haimes, Y. Y.; Loparo, K. A.; Olenik, S. C.; Nanda, S. K.

    1980-06-01

    In this paper the design of a levee drainage system is formulated as a multiobjective optimization problem in a probabilistic framework. The statistical nature of the problem is reflected by the probabilistic behavior of rainfall and river stage events in any given month. The multiobjective approach allows for the incorporation of noncommensurable objectives such as aesthetics, economics, and social issues into the optimization problem, providing a more realistic quantification of the impact of a flood or high water situation in an interior basin. A new method referred to as the multiobjective statistical method, which integrates statistical attributes with multiobjective optimization methodologies such as the surrogate worth trade-off method, is developed in this paper. A case study using data from the Moline area in Illinois suggests the use of the procedure.

  6. Statistical Methods in Algorithm Design and Analysis.

    ERIC Educational Resources Information Center

    Weide, Bruce W.

    The use of statistical methods in the design and analysis of discrete algorithms is explored. The introductory chapter contains a literature survey and background material on probability theory. In Chapter 2, probabilistic approximation algorithms are discussed with the goal of exposing and correcting some oversights in previous work. Chapter 3…

  7. Modern Statistical Methods for GLAST Event Analysis

    SciTech Connect

    Morris, Robin D.; Cohen-Tanugi, Johann; /SLAC /KIPAC, Menlo Park

    2007-04-10

    We describe a statistical reconstruction methodology for the GLAST LAT. The methodology incorporates in detail the statistics of the interactions of photons and charged particles with the tungsten layers in the LAT, and uses the scattering distributions to compute the full probability distribution over the energy and direction of the incident photons. It uses model selection methods to estimate the probabilities of the possible geometrical configurations of the particles produced in the detector, and numerical marginalization over the energy loss and scattering angles at each layer. Preliminary results show that it can improve on the tracker-only energy estimates for muons and electrons incident on the LAT.

  8. Statistical classification methods applied to seismic discrimination

    SciTech Connect

    Ryan, F.M.; Anderson, D.N.; Anderson, K.K.; Hagedorn, D.N.; Higbee, K.T.; Miller, N.E.; Redgate, T.; Rohay, A.C.

    1996-06-11

    To verify compliance with a Comprehensive Test Ban Treaty (CTBT), low energy seismic activity must be detected and discriminated. Monitoring small-scale activity will require regional (within {approx}2000 km) monitoring capabilities. This report provides background information on various statistical classification methods and discusses the relevance of each method in the CTBT seismic discrimination setting. Criteria for classification method selection are explained and examples are given to illustrate several key issues. This report describes in more detail the issues and analyses that were initially outlined in a poster presentation at a recent American Geophysical Union (AGU) meeting. Section 2 of this report describes both the CTBT seismic discrimination setting and the general statistical classification approach to this setting. Seismic data examples illustrate the importance of synergistically using multivariate data as well as the difficulties due to missing observations. Classification method selection criteria are presented and discussed in Section 3. These criteria are grouped into the broad classes of simplicity, robustness, applicability, and performance. Section 4 follows with a description of several statistical classification methods: linear discriminant analysis, quadratic discriminant analysis, variably regularized discriminant analysis, flexible discriminant analysis, logistic discriminant analysis, K-th Nearest Neighbor discrimination, kernel discrimination, and classification and regression tree discrimination. The advantages and disadvantages of these methods are summarized in Section 5.

  9. Protein fold class prediction: new methods of statistical classification.

    PubMed

    Grassmann, J; Reczko, M; Suhai, S; Edler, L

    1999-01-01

    Feed forward neural networks are compared with standard and new statistical classification procedures for the classification of proteins. We applied logistic regression, an additive model and projection pursuit regression from the methods based on a posterior probabilities; linear, quadratic and a flexible discriminant analysis from the methods based on class conditional probabilities, and the K-nearest-neighbors classification rule. Both, the apparent error rate obtained with the training sample (n = 143) and the test error rate obtained with the test sample (n = 125) and the 10-fold cross validation error were calculated. We conclude that some of the standard statistical methods are potent competitors to the more flexible tools of machine learning.

  10. Effusion plate using additive manufacturing methods

    DOEpatents

    Johnson, Thomas Edward; Keener, Christopher Paul; Ostebee, Heath Michael; Wegerif, Daniel Gerritt

    2016-04-12

    Additive manufacturing techniques may be utilized to construct effusion plates. Such additive manufacturing techniques may include defining a configuration for an effusion plate having one or more internal cooling channels. The manufacturing techniques may further include depositing a powder into a chamber, applying an energy source to the deposited powder, and consolidating the powder into a cross-sectional shape corresponding to the defined configuration. Such methods may be implemented to construct an effusion plate having one or more channels with a curved cross-sectional geometry.

  11. Peer-Assisted Learning in Research Methods and Statistics

    ERIC Educational Resources Information Center

    Stone, Anna; Meade, Claire; Watling, Rosamond

    2012-01-01

    Feedback from students on a Level 1 Research Methods and Statistics module, studied as a core part of a BSc Psychology programme, highlighted demand for additional tutorials to help them to understand basic concepts. Students in their final year of study commonly request work experience to enhance their employability. All students on the Level 1…

  12. Computational Statistical Methods for Social Network Models

    PubMed Central

    Hunter, David R.; Krivitsky, Pavel N.; Schweinberger, Michael

    2013-01-01

    We review the broad range of recent statistical work in social network models, with emphasis on computational aspects of these methods. Particular focus is applied to exponential-family random graph models (ERGM) and latent variable models for data on complete networks observed at a single time point, though we also briefly review many methods for incompletely observed networks and networks observed at multiple time points. Although we mention far more modeling techniques than we can possibly cover in depth, we provide numerous citations to current literature. We illustrate several of the methods on a small, well-known network dataset, Sampson’s monks, providing code where possible so that these analyses may be duplicated. PMID:23828720

  13. Supplier Selection Using Weighted Utility Additive Method

    NASA Astrophysics Data System (ADS)

    Karande, Prasad; Chakraborty, Shankar

    2015-10-01

    Supplier selection is a multi-criteria decision-making (MCDM) problem which mainly involves evaluating a number of available suppliers according to a set of common criteria for choosing the best one to meet the organizational needs. For any manufacturing or service organization, selecting the right upstream suppliers is a key success factor that will significantly reduce purchasing cost, increase downstream customer satisfaction and improve competitive ability. The past researchers have attempted to solve the supplier selection problem employing different MCDM techniques which involve active participation of the decision makers in the decision-making process. This paper deals with the application of weighted utility additive (WUTA) method for solving supplier selection problems. The WUTA method, an extension of utility additive approach, is based on ordinal regression and consists of building a piece-wise linear additive decision model from a preference structure using linear programming (LP). It adopts preference disaggregation principle and addresses the decision-making activities through operational models which need implicit preferences in the form of a preorder of reference alternatives or a subset of these alternatives present in the process. The preferential preorder provided by the decision maker is used as a restriction of a LP problem, which has its own objective function, minimization of the sum of the errors associated with the ranking of each alternative. Based on a given reference ranking of alternatives, one or more additive utility functions are derived. Using these utility functions, the weighted utilities for individual criterion values are combined into an overall weighted utility for a given alternative. It is observed that WUTA method, having a sound mathematical background, can provide accurate ranking to the candidate suppliers and choose the best one to fulfill the organizational requirements. Two real time examples are illustrated to prove

  14. Anonymous statistical methods versus cryptographic methods in epidemiology.

    PubMed

    Quantin; Allaert; Dusserre

    2000-11-01

    Sensitive data are most often indirectly identifiable and so need to be rendered anonymous in order to ensure privacy. Statistical methods to provide anonymity require data perturbation and so generate data processing difficulties. Encryption methods, while preserving confidentiality, do not require data modification.

  15. A novel classification method of halftone image via statistics matrices.

    PubMed

    Wen, Zhi-Qiang; Hu, Yong-Xiang; Zhu, Wen-Qiu

    2014-11-01

    Existing classification methods tend not to work well on various error diffusion patterns. Thus a novel classification method for halftone image via statistics matrices is proposed. The statistics matrix descriptor of halftone image is constructed according to the characteristic of error diffusion filters. On this basis, an extraction algorithm is developed based on halftone image patches. The feature modeling is formulated as an optimization problem and then a gradient descent method is used to seek optimum class feature matrices by minimizing the total square error. A maximum likelihood method is proposed according to priori knowledge of training samples. In experiments, the performance evaluation method is provided and comparisons of performance between our method and seven similar methods are made. Then, the influence of parameters, performance under various attacks, computational time complexity and the limitations are discussed. From our experimental study, it is observed that our method has lower classification error rate when compared with other similar methods. In addition, it is robust against usual attacks.

  16. Statistical methods of estimating mining costs

    USGS Publications Warehouse

    Long, K.R.

    2011-01-01

    Until it was defunded in 1995, the U.S. Bureau of Mines maintained a Cost Estimating System (CES) for prefeasibility-type economic evaluations of mineral deposits and estimating costs at producing and non-producing mines. This system had a significant role in mineral resource assessments to estimate costs of developing and operating known mineral deposits and predicted undiscovered deposits. For legal reasons, the U.S. Geological Survey cannot update and maintain CES. Instead, statistical tools are under development to estimate mining costs from basic properties of mineral deposits such as tonnage, grade, mineralogy, depth, strip ratio, distance from infrastructure, rock strength, and work index. The first step was to reestimate "Taylor's Rule" which relates operating rate to available ore tonnage. The second step was to estimate statistical models of capital and operating costs for open pit porphyry copper mines with flotation concentrators. For a sample of 27 proposed porphyry copper projects, capital costs can be estimated from three variables: mineral processing rate, strip ratio, and distance from nearest railroad before mine construction began. Of all the variables tested, operating costs were found to be significantly correlated only with strip ratio.

  17. A power comparison of generalized additive models and the spatial scan statistic in a case-control setting

    PubMed Central

    2010-01-01

    Background A common, important problem in spatial epidemiology is measuring and identifying variation in disease risk across a study region. In application of statistical methods, the problem has two parts. First, spatial variation in risk must be detected across the study region and, second, areas of increased or decreased risk must be correctly identified. The location of such areas may give clues to environmental sources of exposure and disease etiology. One statistical method applicable in spatial epidemiologic settings is a generalized additive model (GAM) which can be applied with a bivariate LOESS smoother to account for geographic location as a possible predictor of disease status. A natural hypothesis when applying this method is whether residential location of subjects is associated with the outcome, i.e. is the smoothing term necessary? Permutation tests are a reasonable hypothesis testing method and provide adequate power under a simple alternative hypothesis. These tests have yet to be compared to other spatial statistics. Results This research uses simulated point data generated under three alternative hypotheses to evaluate the properties of the permutation methods and compare them to the popular spatial scan statistic in a case-control setting. Case 1 was a single circular cluster centered in a circular study region. The spatial scan statistic had the highest power though the GAM method estimates did not fall far behind. Case 2 was a single point source located at the center of a circular cluster and Case 3 was a line source at the center of the horizontal axis of a square study region. Each had linearly decreasing logodds with distance from the point. The GAM methods outperformed the scan statistic in Cases 2 and 3. Comparing sensitivity, measured as the proportion of the exposure source correctly identified as high or low risk, the GAM methods outperformed the scan statistic in all three Cases. Conclusions The GAM permutation testing methods

  18. Statistical methods and computing for big data

    PubMed Central

    Wang, Chun; Chen, Ming-Hui; Schifano, Elizabeth; Wu, Jing

    2016-01-01

    Big data are data on a massive scale in terms of volume, intensity, and complexity that exceed the capacity of standard analytic tools. They present opportunities as well as challenges to statisticians. The role of computational statisticians in scientific discovery from big data analyses has been under-recognized even by peer statisticians. This article summarizes recent methodological and software developments in statistics that address the big data challenges. Methodologies are grouped into three classes: subsampling-based, divide and conquer, and online updating for stream data. As a new contribution, the online updating approach is extended to variable selection with commonly used criteria, and their performances are assessed in a simulation study with stream data. Software packages are summarized with focuses on the open source R and R packages, covering recent tools that help break the barriers of computer memory and computing power. Some of the tools are illustrated in a case study with a logistic regression for the chance of airline delay. PMID:27695593

  19. Statistical Methods Used in Gifted Education Journals, 2006-2010

    ERIC Educational Resources Information Center

    Warne, Russell T.; Lazo, Maria; Ramos, Tammy; Ritter, Nicola

    2012-01-01

    This article describes the statistical methods used in quantitative and mixed methods articles between 2006 and 2010 in five gifted education research journals. Results indicate that the most commonly used statistical methods are means (85.9% of articles), standard deviations (77.8%), Pearson's "r" (47.8%), X[superscript 2] (32.2%), ANOVA (30.7%),…

  20. Problems of applicability of statistical methods in cosmology

    SciTech Connect

    Levin, S. F.

    2015-12-15

    The problems arising from the incorrect formulation of measuring problems of identification for cosmological models and violations of conditions of applicability of statistical methods are considered.

  1. Cratering statistics on asteroids: Methods and perspectives

    NASA Astrophysics Data System (ADS)

    Chapman, C.

    2014-07-01

    Crater size-frequency distributions (SFDs) on the surfaces of solid-surfaced bodies in the solar system have provided valuable insights about planetary surface processes and about impactor populations since the first spacecraft images were obtained in the 1960s. They can be used to determine relative age differences between surficial units, to obtain absolute model ages if the impactor flux and scaling laws are understood, to assess various endogenic planetary or asteroidal processes that degrade craters or resurface units, as well as assess changes in impactor populations across the solar system and/or with time. The first asteroid SFDs were measured from Galileo images of Gaspra and Ida (cf., Chapman 2002). Despite the superficial simplicity of these studies, they are fraught with many difficulties, including confusion by secondary and/or endogenic cratering and poorly understood aspects of varying target properties (including regoliths, ejecta blankets, and nearly-zero-g rubble piles), widely varying attributes of impactors, and a host of methodological problems including recognizability of degraded craters, which is affected by illumination angle and by the ''personal equations'' of analysts. Indeed, controlled studies (Robbins et al. 2014) demonstrate crater-density differences of a factor of two or more between experienced crater counters. These inherent difficulties have been especially apparent in divergent results for Vesta from different members of the Dawn Science Team (cf. Russell et al. 2013). Indeed, they have been exacerbated by misuse of a widely available tool (Craterstats: hrscview.fu- berlin.de/craterstats.html), which incorrectly computes error bars for proper interpretation of cumulative SFDs, resulting in derived model ages specified to three significant figures and interpretations of statistically insignificant kinks. They are further exacerbated, and for other small-body crater SFDs analyzed by the Berlin group, by stubbornly adopting

  2. Statistical methods for studying disease subtype heterogeneity.

    PubMed

    Wang, Molin; Spiegelman, Donna; Kuchiba, Aya; Lochhead, Paul; Kim, Sehee; Chan, Andrew T; Poole, Elizabeth M; Tamimi, Rulla; Tworoger, Shelley S; Giovannucci, Edward; Rosner, Bernard; Ogino, Shuji

    2016-02-28

    A fundamental goal of epidemiologic research is to investigate the relationship between exposures and disease risk. Cases of the disease are often considered a single outcome and assumed to share a common etiology. However, evidence indicates that many human diseases arise and evolve through a range of heterogeneous molecular pathologic processes, influenced by diverse exposures. Pathogenic heterogeneity has been considered in various neoplasms such as colorectal, lung, prostate, and breast cancers, leukemia and lymphoma, and non-neoplastic diseases, including obesity, type II diabetes, glaucoma, stroke, cardiovascular disease, autism, and autoimmune disease. In this article, we discuss analytic options for studying disease subtype heterogeneity, emphasizing methods for evaluating whether the association of a potential risk factor with disease varies by disease subtype. Methods are described for scenarios where disease subtypes are categorical and ordinal and for cohort studies, matched and unmatched case-control studies, and case-case study designs. For illustration, we apply the methods to a molecular pathological epidemiology study of alcohol intake and colon cancer risk by tumor LINE-1 methylation subtypes. User-friendly software to implement the methods is publicly available.

  3. Statistical Methods for Image Registration and Denoising

    DTIC Science & Technology

    2008-06-19

    21 2.5.4 Nonlocal Means . . . . . . . . . . . . . . . . . 22 2.5.5 Patch -Based Denoising with Optimal Spatial Adap- tation...24 2.5.6 Other Patch -Based Methods . . . . . . . . . . 25 2.6 Chapter Summary...the nonlocal means [9], and an optimal patch -based algorithm [31]. These algorithms all include some measure of pixel similarity that allows the

  4. Hybrid perturbation methods based on statistical time series models

    NASA Astrophysics Data System (ADS)

    San-Juan, Juan Félix; San-Martín, Montserrat; Pérez, Iván; López, Rosario

    2016-04-01

    In this work we present a new methodology for orbit propagation, the hybrid perturbation theory, based on the combination of an integration method and a prediction technique. The former, which can be a numerical, analytical or semianalytical theory, generates an initial approximation that contains some inaccuracies derived from the fact that, in order to simplify the expressions and subsequent computations, not all the involved forces are taken into account and only low-order terms are considered, not to mention the fact that mathematical models of perturbations not always reproduce physical phenomena with absolute precision. The prediction technique, which can be based on either statistical time series models or computational intelligence methods, is aimed at modelling and reproducing missing dynamics in the previously integrated approximation. This combination results in the precision improvement of conventional numerical, analytical and semianalytical theories for determining the position and velocity of any artificial satellite or space debris object. In order to validate this methodology, we present a family of three hybrid orbit propagators formed by the combination of three different orders of approximation of an analytical theory and a statistical time series model, and analyse their capability to process the effect produced by the flattening of the Earth. The three considered analytical components are the integration of the Kepler problem, a first-order and a second-order analytical theories, whereas the prediction technique is the same in the three cases, namely an additive Holt-Winters method.

  5. Online Statistics Labs in MSW Research Methods Courses: Reducing Reluctance toward Statistics

    ERIC Educational Resources Information Center

    Elliott, William; Choi, Eunhee; Friedline, Terri

    2013-01-01

    This article presents results from an evaluation of an online statistics lab as part of a foundations research methods course for master's-level social work students. The article discusses factors that contribute to an environment in social work that fosters attitudes of reluctance toward learning and teaching statistics in research methods…

  6. The estimation of the measurement results with using statistical methods

    NASA Astrophysics Data System (ADS)

    Velychko, O.; Gordiyenko, T.

    2015-02-01

    The row of international standards and guides describe various statistical methods that apply for a management, control and improvement of processes with the purpose of realization of analysis of the technical measurement results. The analysis of international standards and guides on statistical methods estimation of the measurement results recommendations for those applications in laboratories is described. For realization of analysis of standards and guides the cause-and-effect Ishikawa diagrams concerting to application of statistical methods for estimation of the measurement results are constructed.

  7. Statistical methods for evaluating the attainment of cleanup standards

    SciTech Connect

    Gilbert, R.O.; Simpson, J.C.

    1992-12-01

    This document is the third volume in a series of volumes sponsored by the US Environmental Protection Agency (EPA), Statistical Policy Branch, that provide statistical methods for evaluating the attainment of cleanup Standards at Superfund sites. Volume 1 (USEPA 1989a) provides sampling designs and tests for evaluating attainment of risk-based standards for soils and solid media. Volume 2 (USEPA 1992) provides designs and tests for evaluating attainment of risk-based standards for groundwater. The purpose of this third volume is to provide statistical procedures for designing sampling programs and conducting statistical tests to determine whether pollution parameters in remediated soils and solid media at Superfund sites attain site-specific reference-based standards. This.document is written for individuals who may not have extensive training or experience with statistical methods. The intended audience includes EPA regional remedial project managers, Superfund-site potentially responsible parties, state environmental protection agencies, and contractors for these groups.

  8. [Statistical prediction methods in violence risk assessment and its application].

    PubMed

    Liu, Yuan-Yuan; Hu, Jun-Mei; Yang, Min; Li, Xiao-Song

    2013-06-01

    It is an urgent global problem how to improve the violence risk assessment. As a necessary part of risk assessment, statistical methods have remarkable impacts and effects. In this study, the predicted methods in violence risk assessment from the point of statistics are reviewed. The application of Logistic regression as the sample of multivariate statistical model, decision tree model as the sample of data mining technique, and neural networks model as the sample of artificial intelligence technology are all reviewed. This study provides data in order to contribute the further research of violence risk assessment.

  9. Development and testing of improved statistical wind power forecasting methods.

    SciTech Connect

    Mendes, J.; Bessa, R.J.; Keko, H.; Sumaili, J.; Miranda, V.; Ferreira, C.; Gama, J.; Botterud, A.; Zhou, Z.; Wang, J.

    2011-12-06

    Wind power forecasting (WPF) provides important inputs to power system operators and electricity market participants. It is therefore not surprising that WPF has attracted increasing interest within the electric power industry. In this report, we document our research on improving statistical WPF algorithms for point, uncertainty, and ramp forecasting. Below, we provide a brief introduction to the research presented in the following chapters. For a detailed overview of the state-of-the-art in wind power forecasting, we refer to [1]. Our related work on the application of WPF in operational decisions is documented in [2]. Point forecasts of wind power are highly dependent on the training criteria used in the statistical algorithms that are used to convert weather forecasts and observational data to a power forecast. In Chapter 2, we explore the application of information theoretic learning (ITL) as opposed to the classical minimum square error (MSE) criterion for point forecasting. In contrast to the MSE criterion, ITL criteria do not assume a Gaussian distribution of the forecasting errors. We investigate to what extent ITL criteria yield better results. In addition, we analyze time-adaptive training algorithms and how they enable WPF algorithms to cope with non-stationary data and, thus, to adapt to new situations without requiring additional offline training of the model. We test the new point forecasting algorithms on two wind farms located in the U.S. Midwest. Although there have been advancements in deterministic WPF, a single-valued forecast cannot provide information on the dispersion of observations around the predicted value. We argue that it is essential to generate, together with (or as an alternative to) point forecasts, a representation of the wind power uncertainty. Wind power uncertainty representation can take the form of probabilistic forecasts (e.g., probability density function, quantiles), risk indices (e.g., prediction risk index) or scenarios

  10. Using the statistical analysis method to assess the landslide susceptibility

    NASA Astrophysics Data System (ADS)

    Chan, Hsun-Chuan; Chen, Bo-An; Wen, Yo-Ting

    2015-04-01

    This study assessed the landslide susceptibility in Jing-Shan River upstream watershed, central Taiwan. The landslide inventories during typhoons Toraji in 2001, Mindulle in 2004, Kalmaegi and Sinlaku in 2008, Morakot in 2009, and the 0719 rainfall event in 2011, which were established by Taiwan Central Geological Survey, were used as landslide data. This study aims to assess the landslide susceptibility by using different statistical methods including logistic regression, instability index method and support vector machine (SVM). After the evaluations, the elevation, slope, slope aspect, lithology, terrain roughness, slope roughness, plan curvature, profile curvature, total curvature, average of rainfall were chosen as the landslide factors. The validity of the three established models was further examined by the receiver operating characteristic curve. The result of logistic regression showed that the factor of terrain roughness and slope roughness had a stronger impact on the susceptibility value. Instability index method showed that the factor of terrain roughness and lithology had a stronger impact on the susceptibility value. Due to the fact that the use of instability index method may lead to possible underestimation around the river side. In addition, landslide susceptibility indicated that the use of instability index method laid a potential issue about the number of factor classification. An increase of the number of factor classification may cause excessive variation coefficient of the factor. An decrease of the number of factor classification may make a large range of nearby cells classified into the same susceptibility level. Finally, using the receiver operating characteristic curve discriminate the three models. SVM is a preferred method than the others in assessment of landslide susceptibility. Moreover, SVM is further suggested to be nearly logistic regression in terms of recognizing the medium-high and high susceptibility.

  11. [Evaluation of using statistical methods in selected national medical journals].

    PubMed

    Sych, Z

    1996-01-01

    The paper covers the performed evaluation of frequency with which the statistical methods were applied in analyzed works having been published in six selected, national medical journals in the years 1988-1992. For analysis the following journals were chosen, namely: Klinika Oczna, Medycyna Pracy, Pediatria Polska, Polski Tygodnik Lekarski, Roczniki Państwowego Zakładu Higieny, Zdrowie Publiczne. Appropriate number of works up to the average in the remaining medical journals was randomly selected from respective volumes of Pol. Tyg. Lek. The studies did not include works wherein the statistical analysis was not implemented, which referred both to national and international publications. That exemption was also extended to review papers, casuistic ones, reviews of books, handbooks, monographies, reports from scientific congresses, as well as papers on historical topics. The number of works was defined in each volume. Next, analysis was performed to establish the mode of finding out a suitable sample in respective studies, differentiating two categories: random and target selections. Attention was also paid to the presence of control sample in the individual works. In the analysis attention was also focussed on the existence of sample characteristics, setting up three categories: complete, partial and lacking. In evaluating the analyzed works an effort was made to present the results of studies in tables and figures (Tab. 1, 3). Analysis was accomplished with regard to the rate of employing statistical methods in analyzed works in relevant volumes of six selected, national medical journals for the years 1988-1992, simultaneously determining the number of works, in which no statistical methods were used. Concurrently the frequency of applying the individual statistical methods was analyzed in the scrutinized works. Prominence was given to fundamental statistical methods in the field of descriptive statistics (measures of position, measures of dispersion) as well as

  12. Methods for detecting additional genes underlying Alzheimer disease

    SciTech Connect

    Locke, P.A.; Haines, J.L.; Ter-Minassian, M.

    1994-09-01

    Alzheimer`s disease (AD) is a complex inherited disorder with proven genetic heterogeneity. To date, genes on chromosome 21 (APP) and 14 (not yet identified) are associated with early-onset familial AD, while the APOE gene on chromosome 19 is associated with both late onset familial and sporadic AD and early onset sporadic AD. Although these genes likely account for the majority of AD, many familial cases cannot be traced to any of these genes. From a set of 127 late-onset multiplex families screened for APOE, 43 (34%) families have at least one affected individual with no APOE-4 allele, suggesting an alternative genetic etiology. Simulation studies indicated that additional loci could be identified through a genomic screen with a 10 cM sieve on a subset of 21 well documented, non-APOE-4 families. Given the uncertainties in the mode of inheritance, reliance on a single analytical method could result in a missed linkage. Therefore, we have developed a strategy of using multiple overlapping yet complementary methods to detect linkage. These include sib-pair analysis and affected-pedigree-member analysis, neither of which makes assumptions about mode of inheritance, and lod score analysis (using two predefined genetic models). In order for a marker to qualify for follow-up, it must fit at least two of three criteria. These are nominal P values of 0.05 or less for the non-parametric methods, and/or a lod score greater than 1.0. Adjacent markers each fulfilling a single criterion also warrant follow-up. To date, we have screened 61 markers on chromosomes 1, 2, 3, 18, 19, 21, and 22. One marker, D2S163, generated a lod score of 1.06 ({theta} = 0.15) and an APMT statistic of 3.68 (P < 0.001). This region is currently being investigated in more detail. Updated results of this region plus additional screening data will be presented.

  13. METHOD OF OBTAINING AN ADDITIVE FOR LUBRICATING OILS,

    DTIC Science & Technology

    The method of obtaining an additive to lubricating oils , consisting of treating boron trifluoride with alkylphenol and alkylamine, is known. In this...case, (aminotrifluoralkyl)phenoxyborate is obtained which may be used as an antiwear additive for lubricating oils . The proposed method differs from

  14. Statistical Methods for Characterizing Variability in Stellar Spectra

    NASA Astrophysics Data System (ADS)

    Cisewski, Jessi; Yale Astrostatistics

    2017-01-01

    Recent years have seen a proliferation in the number of exoplanets discovered. One technique for uncovering exoplanets relies on the detection of subtle shifts in the stellar spectra due to the Doppler effect caused by an orbiting object. However, stellar activity can cause distortions in the spectra that mimic the imprint of an orbiting exoplanet. The collection of stellar spectra potentially contains more information than is traditionally used for estimating its radial velocity curve. I will discuss some statistical methods that can be used for characterizing the sources of variability in the spectra. Statistical assessment of stellar spectra is a focus of the Statistical and Applied Mathematical Sciences Institute (SAMSI)'s yearlong program on Statistical, Mathematical and Computational Methods for Astronomy's Working Group IV (Astrophysical Populations).

  15. The Metropolis Monte Carlo Method in Statistical Physics

    NASA Astrophysics Data System (ADS)

    Landau, David P.

    2003-11-01

    A brief overview is given of some of the advances in statistical physics that have been made using the Metropolis Monte Carlo method. By complementing theory and experiment, these have increased our understanding of phase transitions and other phenomena in condensed matter systems. A brief description of a new method, commonly known as "Wang-Landau sampling," will also be presented.

  16. Statistical Methods for Detecting Anomalous Voting Patterns: A Case Study

    DTIC Science & Technology

    2011-09-23

    voting data. As a case study, we apply methods developed by Beber and Scacco to analyze polling station counts in Helmand province for the four...1  2) STATISTICAL MODELS FOR ANOMALY ANALYSIS .............................................. 2  a) The Beber -Scacco Model...carry out the necessary analysis. Beber and Scacco [4] have developed one such model for analyzing voting tallies. Their methods exploit the apparent

  17. Statistical Methods for Establishing Personalized Treatment Rules in Oncology

    PubMed Central

    Ma, Junsheng; Hobbs, Brian P.; Stingo, Francesco C.

    2015-01-01

    The process for using statistical inference to establish personalized treatment strategies requires specific techniques for data-analysis that optimize the combination of competing therapies with candidate genetic features and characteristics of the patient and disease. A wide variety of methods have been developed. However, heretofore the usefulness of these recent advances has not been fully recognized by the oncology community, and the scope of their applications has not been summarized. In this paper, we provide an overview of statistical methods for establishing optimal treatment rules for personalized medicine and discuss specific examples in various medical contexts with oncology as an emphasis. We also point the reader to statistical software for implementation of the methods when available. PMID:26446492

  18. Statistical Methods for Establishing Personalized Treatment Rules in Oncology.

    PubMed

    Ma, Junsheng; Hobbs, Brian P; Stingo, Francesco C

    2015-01-01

    The process for using statistical inference to establish personalized treatment strategies requires specific techniques for data-analysis that optimize the combination of competing therapies with candidate genetic features and characteristics of the patient and disease. A wide variety of methods have been developed. However, heretofore the usefulness of these recent advances has not been fully recognized by the oncology community, and the scope of their applications has not been summarized. In this paper, we provide an overview of statistical methods for establishing optimal treatment rules for personalized medicine and discuss specific examples in various medical contexts with oncology as an emphasis. We also point the reader to statistical software for implementation of the methods when available.

  19. Advances in Statistical Methods for Substance Abuse Prevention Research

    PubMed Central

    MacKinnon, David P.; Lockwood, Chondra M.

    2010-01-01

    The paper describes advances in statistical methods for prevention research with a particular focus on substance abuse prevention. Standard analysis methods are extended to the typical research designs and characteristics of the data collected in prevention research. Prevention research often includes longitudinal measurement, clustering of data in units such as schools or clinics, missing data, and categorical as well as continuous outcome variables. Statistical methods to handle these features of prevention data are outlined. Developments in mediation, moderation, and implementation analysis allow for the extraction of more detailed information from a prevention study. Advancements in the interpretation of prevention research results include more widespread calculation of effect size and statistical power, the use of confidence intervals as well as hypothesis testing, detailed causal analysis of research findings, and meta-analysis. The increased availability of statistical software has contributed greatly to the use of new methods in prevention research. It is likely that the Internet will continue to stimulate the development and application of new methods. PMID:12940467

  20. Landslide Susceptibility Statistical Methods: A Critical and Systematic Literature Review

    NASA Astrophysics Data System (ADS)

    Mihir, Monika; Malamud, Bruce; Rossi, Mauro; Reichenbach, Paola; Ardizzone, Francesca

    2014-05-01

    Landslide susceptibility assessment, the subject of this systematic review, is aimed at understanding the spatial probability of slope failures under a set of geomorphological and environmental conditions. It is estimated that about 375 landslides that occur globally each year are fatal, with around 4600 people killed per year. Past studies have brought out the increasing cost of landslide damages which primarily can be attributed to human occupation and increased human activities in the vulnerable environments. Many scientists, to evaluate and reduce landslide risk, have made an effort to efficiently map landslide susceptibility using different statistical methods. In this paper, we do a critical and systematic landslide susceptibility literature review, in terms of the different statistical methods used. For each of a broad set of studies reviewed we note: (i) study geography region and areal extent, (ii) landslide types, (iii) inventory type and temporal period covered, (iv) mapping technique (v) thematic variables used (vi) statistical models, (vii) assessment of model skill, (viii) uncertainty assessment methods, (ix) validation methods. We then pulled out broad trends within our review of landslide susceptibility, particularly regarding the statistical methods. We found that the most common statistical methods used in the study of landslide susceptibility include logistic regression, artificial neural network, discriminant analysis and weight of evidence. Although most of the studies we reviewed assessed the model skill, very few assessed model uncertainty. In terms of geographic extent, the largest number of landslide susceptibility zonations were in Turkey, Korea, Spain, Italy and Malaysia. However, there are also many landslides and fatalities in other localities, particularly India, China, Philippines, Nepal and Indonesia, Guatemala, and Pakistan, where there are much fewer landslide susceptibility studies available in the peer-review literature. This

  1. Epidemiology and statistical methods in prediction of patient outcome.

    PubMed

    Bostwick, David G; Adolfsson, Jan; Burke, Harry B; Damber, Jan-Erik; Huland, Hartwig; Pavone-Macaluso, Michele; Waters, David J

    2005-05-01

    Substantial gaps exist in the data of the assessment of risk and prognosis that limit our understanding of the complex mechanisms that contribute to the greatest cancer epidemic, prostate cancer, of our time. This report was prepared by an international multidisciplinary committee of the World Health Organization to address contemporary issues of epidemiology and statistical methods in prostate cancer, including a summary of current risk assessment methods and prognostic factors. Emphasis was placed on the relative merits of each of the statistical methods available. We concluded that: 1. An international committee should be created to guide the assessment and validation of molecular biomarkers. The goal is to achieve more precise identification of those who would benefit from treatment. 2. Prostate cancer is a predictable disease despite its biologic heterogeneity. However, the accuracy of predicting it must be improved. We expect that more precise statistical methods will supplant the current staging system. The simplicity and intuitive ease of using the current staging system must be balanced against the serious compromise in accuracy for the individual patient. 3. The most useful new statistical approaches will integrate molecular biomarkers with existing prognostic factors to predict conditional life expectancy (i.e. the expected remaining years of a patient's life) and take into account all-cause mortality.

  2. Recent development on statistical methods for personalized medicine discovery.

    PubMed

    Zhao, Yingqi; Zeng, Donglin

    2013-03-01

    It is well documented that patients can show significant heterogeneous responses to treatments so the best treatment strategies may require adaptation over individuals and time. Recently, a number of new statistical methods have been developed to tackle the important problem of estimating personalized treatment rules using single-stage or multiple-stage clinical data. In this paper, we provide an overview of these methods and list a number of challenges.

  3. System and method for statistically monitoring and analyzing sensed conditions

    DOEpatents

    Pebay, Philippe P.; Brandt, James M.; Gentile, Ann C.; Marzouk, Youssef M.; Hale, Darrian J.; Thompson, David C.

    2011-01-04

    A system and method of monitoring and analyzing a plurality of attributes for an alarm condition is disclosed. The attributes are processed and/or unprocessed values of sensed conditions of a collection of a statistically significant number of statistically similar components subjected to varying environmental conditions. The attribute values are used to compute the normal behaviors of some of the attributes and also used to infer parameters of a set of models. Relative probabilities of some attribute values are then computed and used along with the set of models to determine whether an alarm condition is met. The alarm conditions are used to prevent or reduce the impact of impending failure.

  4. System and method for statistically monitoring and analyzing sensed conditions

    DOEpatents

    Pebay, Philippe P.; Brandt, James M. , Gentile; Ann C. , Marzouk; Youssef M. , Hale; Darrian J. , Thompson; David C.

    2010-07-13

    A system and method of monitoring and analyzing a plurality of attributes for an alarm condition is disclosed. The attributes are processed and/or unprocessed values of sensed conditions of a collection of a statistically significant number of statistically similar components subjected to varying environmental conditions. The attribute values are used to compute the normal behaviors of some of the attributes and also used to infer parameters of a set of models. Relative probabilities of some attribute values are then computed and used along with the set of models to determine whether an alarm condition is met. The alarm conditions are used to prevent or reduce the impact of impending failure.

  5. System and method for statistically monitoring and analyzing sensed conditions

    DOEpatents

    Pebay, Philippe P.; Brandt, James M.; Gentile, Ann C.; Marzouk, Youssef M.; Hale, Darrian J.; Thompson, David C.

    2011-01-25

    A system and method of monitoring and analyzing a plurality of attributes for an alarm condition is disclosed. The attributes are processed and/or unprocessed values of sensed conditions of a collection of a statistically significant number of statistically similar components subjected to varying environmental conditions. The attribute values are used to compute the normal behaviors of some of the attributes and also used to infer parameters of a set of models. Relative probabilities of some attribute values are then computed and used along with the set of models to determine whether an alarm condition is met. The alarm conditions are used to prevent or reduce the impact of impending failure.

  6. Physical mechanism and statistics of occurrence of an additional layer in the equatorial ionosphere

    NASA Astrophysics Data System (ADS)

    Balan, N.; Batista, I. S.; Abdu, M. A.; MacDougall, J.; Bailey, G. J.

    1998-12-01

    A physical mechanism and the location and latitudinal extent of an additional layer, called the F3 layer, that exists in the equatorial ionosphere are presented. A statistical analysis of the occurrence of the layer recorded at the equatorial station Fortaleza (4°S, 38°W dip 9°S) in Brazil is also presented. The F3 layer forms during the morning-noon period in that equatorial region where the combined effect of the upward E×B drift and neutral wind provides a vertically upward plasma drift velocity at altitudes near and above the F2 peak. This velocity causes the F2 peak to drift upward and form the F3 layer while the normal F2 layer develops at lower altitudes through the usual photochemical and dynamical effects of the equatorial region. The peak electron density of the F3 layer can exceed that of the F2 layer. The F3 layer is predicted to be distinct on the summer side of the geomagnetic equator during periods of low solar activity and to become less distinct as the solar activity increases. Ionograms recorded at Fortaleza in 1995 show the existence of an F3 layer on 49% of the days, with the occurrence being most frequent (75%) and distinct in summer, as expected. During summer the layer occurs earlier and lasts longer compared to the other seasons; on the average, the layer occurs at around 0930 LT and lasts for about 3 hours. The altitude of the layer is also high in summer, with the mean peak virtual height being about 570 km. However, the critical frequency of the layer (foF3) exceeds that of the F2 layer (foF2) by the largest amounts in winter and equinox; foF3 exceeds foF2 by a yearly average of about 1.3 MHz.

  7. Optimal Multicomponent Analysis Using the Generalized Standard Addition Method.

    ERIC Educational Resources Information Center

    Raymond, Margaret; And Others

    1983-01-01

    Describes an experiment on the simultaneous determination of chromium and magnesium by spectophotometry modified to include the Generalized Standard Addition Method computer program, a multivariate calibration method that provides optimal multicomponent analysis in the presence of interference and matrix effects. Provides instructions for…

  8. Statistical methods to estimate treatment effects from multichannel electroencephalography (EEG) data in clinical trials.

    PubMed

    Ma, Junshui; Wang, Shubing; Raubertas, Richard; Svetnik, Vladimir

    2010-07-15

    With the increasing popularity of using electroencephalography (EEG) to reveal the treatment effect in drug development clinical trials, the vast volume and complex nature of EEG data compose an intriguing, but challenging, topic. In this paper the statistical analysis methods recommended by the EEG community, along with methods frequently used in the published literature, are first reviewed. A straightforward adjustment of the existing methods to handle multichannel EEG data is then introduced. In addition, based on the spatial smoothness property of EEG data, a new category of statistical methods is proposed. The new methods use a linear combination of low-degree spherical harmonic (SPHARM) basis functions to represent a spatially smoothed version of the EEG data on the scalp, which is close to a sphere in shape. In total, seven statistical methods, including both the existing and the newly proposed methods, are applied to two clinical datasets to compare their power to detect a drug effect. Contrary to the EEG community's recommendation, our results suggest that (1) the nonparametric method does not outperform its parametric counterpart; and (2) including baseline data in the analysis does not always improve the statistical power. In addition, our results recommend that (3) simple paired statistical tests should be avoided due to their poor power; and (4) the proposed spatially smoothed methods perform better than their unsmoothed versions.

  9. Additives

    NASA Technical Reports Server (NTRS)

    Smalheer, C. V.

    1973-01-01

    The chemistry of lubricant additives is discussed to show what the additives are chemically and what functions they perform in the lubrication of various kinds of equipment. Current theories regarding the mode of action of lubricant additives are presented. The additive groups discussed include the following: (1) detergents and dispersants, (2) corrosion inhibitors, (3) antioxidants, (4) viscosity index improvers, (5) pour point depressants, and (6) antifouling agents.

  10. Teaching biology through statistics: application of statistical methods in genetics and zoology courses.

    PubMed

    Colon-Berlingeri, Migdalisel; Burrowes, Patricia A

    2011-01-01

    Incorporation of mathematics into biology curricula is critical to underscore for undergraduate students the relevance of mathematics to most fields of biology and the usefulness of developing quantitative process skills demanded in modern biology. At our institution, we have made significant changes to better integrate mathematics into the undergraduate biology curriculum. The curricular revision included changes in the suggested course sequence, addition of statistics and precalculus as prerequisites to core science courses, and incorporating interdisciplinary (math-biology) learning activities in genetics and zoology courses. In this article, we describe the activities developed for these two courses and the assessment tools used to measure the learning that took place with respect to biology and statistics. We distinguished the effectiveness of these learning opportunities in helping students improve their understanding of the math and statistical concepts addressed and, more importantly, their ability to apply them to solve a biological problem. We also identified areas that need emphasis in both biology and mathematics courses. In light of our observations, we recommend best practices that biology and mathematics academic departments can implement to train undergraduates for the demands of modern biology.

  11. Teaching Biology through Statistics: Application of Statistical Methods in Genetics and Zoology Courses

    PubMed Central

    Colon-Berlingeri, Migdalisel; Burrowes, Patricia A.

    2011-01-01

    Incorporation of mathematics into biology curricula is critical to underscore for undergraduate students the relevance of mathematics to most fields of biology and the usefulness of developing quantitative process skills demanded in modern biology. At our institution, we have made significant changes to better integrate mathematics into the undergraduate biology curriculum. The curricular revision included changes in the suggested course sequence, addition of statistics and precalculus as prerequisites to core science courses, and incorporating interdisciplinary (math–biology) learning activities in genetics and zoology courses. In this article, we describe the activities developed for these two courses and the assessment tools used to measure the learning that took place with respect to biology and statistics. We distinguished the effectiveness of these learning opportunities in helping students improve their understanding of the math and statistical concepts addressed and, more importantly, their ability to apply them to solve a biological problem. We also identified areas that need emphasis in both biology and mathematics courses. In light of our observations, we recommend best practices that biology and mathematics academic departments can implement to train undergraduates for the demands of modern biology. PMID:21885822

  12. Predicting recreational water quality advisories: A comparison of statistical methods

    USGS Publications Warehouse

    Brooks, Wesley R.; Corsi, Steven R.; Fienen, Michael N.; Carvin, Rebecca B.

    2016-01-01

    Epidemiological studies indicate that fecal indicator bacteria (FIB) in beach water are associated with illnesses among people having contact with the water. In order to mitigate public health impacts, many beaches are posted with an advisory when the concentration of FIB exceeds a beach action value. The most commonly used method of measuring FIB concentration takes 18–24 h before returning a result. In order to avoid the 24 h lag, it has become common to ”nowcast” the FIB concentration using statistical regressions on environmental surrogate variables. Most commonly, nowcast models are estimated using ordinary least squares regression, but other regression methods from the statistical and machine learning literature are sometimes used. This study compares 14 regression methods across 7 Wisconsin beaches to identify which consistently produces the most accurate predictions. A random forest model is identified as the most accurate, followed by multiple regression fit using the adaptive LASSO.

  13. Statistical inference for the additive hazards model under outcome-dependent sampling.

    PubMed

    Yu, Jichang; Liu, Yanyan; Sandler, Dale P; Zhou, Haibo

    2015-09-01

    Cost-effective study design and proper inference procedures for data from such designs are always of particular interests to study investigators. In this article, we propose a biased sampling scheme, an outcome-dependent sampling (ODS) design for survival data with right censoring under the additive hazards model. We develop a weighted pseudo-score estimator for the regression parameters for the proposed design and derive the asymptotic properties of the proposed estimator. We also provide some suggestions for using the proposed method by evaluating the relative efficiency of the proposed method against simple random sampling design and derive the optimal allocation of the subsamples for the proposed design. Simulation studies show that the proposed ODS design is more powerful than other existing designs and the proposed estimator is more efficient than other estimators. We apply our method to analyze a cancer study conducted at NIEHS, the Cancer Incidence and Mortality of Uranium Miners Study, to study the risk of radon exposure to cancer.

  14. Statistical inference for the additive hazards model under outcome-dependent sampling

    PubMed Central

    Yu, Jichang; Liu, Yanyan; Sandler, Dale P.; Zhou, Haibo

    2015-01-01

    Cost-effective study design and proper inference procedures for data from such designs are always of particular interests to study investigators. In this article, we propose a biased sampling scheme, an outcome-dependent sampling (ODS) design for survival data with right censoring under the additive hazards model. We develop a weighted pseudo-score estimator for the regression parameters for the proposed design and derive the asymptotic properties of the proposed estimator. We also provide some suggestions for using the proposed method by evaluating the relative efficiency of the proposed method against simple random sampling design and derive the optimal allocation of the subsamples for the proposed design. Simulation studies show that the proposed ODS design is more powerful than other existing designs and the proposed estimator is more efficient than other estimators. We apply our method to analyze a cancer study conducted at NIEHS, the Cancer Incidence and Mortality of Uranium Miners Study, to study the risk of radon exposure to cancer. PMID:26379363

  15. Comparison of different approaches to evaluation of statistical error of the DSMC method

    NASA Astrophysics Data System (ADS)

    Plotnikov, M. Yu.; Shkarupa, E. V.

    2012-11-01

    Although the direct simulation Monte Carlo (DSMC) method is widely used for solving the steady problems of the rarefied gas dynamics, the questions of its statistical error evaluation are far from being absolutely clear. Typically, the statistical error in the Monte Carlo method is estimated by the standard deviation determined by the variance of the estimate and the number of its realizations. It is assumed that sampled realizations are independent. In distinction from the classical Monte Carlo method, in the DSMC method the time-averaged estimate is used and the sampled realizations are dependent. Additional difficulties in the evaluation of the statistical error are caused by the complexity of the estimates used in the DSMC method. In the presented work we compare two approaches to evaluating the statistical error. One of them is based on the results of the equilibrium statistical mechanics and the "persistent random walk". Another approach is based on the central limit theorem for Markov processes. Each of these approaches has its own benefits and disadvantages. The first approach mentioned above does not require additional computations to construct estimates of the statistical error. On the other hand it allows evaluating statistical error only in the case when all components of velocity and temperature are equivalent. The second approach to evaluating the statistical error is applicable to simulation by the DSMC method a flows with any degree of nonequilibrium. It allows evaluating the statistical errors of the estimates of velocity and temperature components. The comparison of these approaches was realized on the example of a number of classic problems with different degree of nonequilibrium.

  16. Additive manufacturing method for SRF components of various geometries

    SciTech Connect

    Rimmer, Robert; Frigola, Pedro E; Murokh, Alex Y

    2015-05-05

    An additive manufacturing method for forming nearly monolithic SRF niobium cavities and end group components of arbitrary shape with features such as optimized wall thickness and integral stiffeners, greatly reducing the cost and technical variability of conventional cavity construction. The additive manufacturing method for forming an SRF cavity, includes atomizing niobium to form a niobium powder, feeding the niobium powder into an electron beam melter under a vacuum, melting the niobium powder under a vacuum in the electron beam melter to form an SRF cavity; and polishing the inside surface of the SRF cavity.

  17. 10 CFR 2.705 - Discovery-additional methods.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... 10 Energy 1 2012-01-01 2012-01-01 false Discovery-additional methods. 2.705 Section 2.705 Energy NUCLEAR REGULATORY COMMISSION RULES OF PRACTICE FOR DOMESTIC LICENSING PROCEEDINGS AND ISSUANCE OF ORDERS... 147 and 181 of the Atomic Energy Act of 1954, as amended, the presiding officer may issue an...

  18. 10 CFR 2.705 - Discovery-additional methods.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... 10 Energy 1 2013-01-01 2013-01-01 false Discovery-additional methods. 2.705 Section 2.705 Energy NUCLEAR REGULATORY COMMISSION AGENCY RULES OF PRACTICE AND PROCEDURE Rules for Formal Adjudications § 2... 147 and 181 of the Atomic Energy Act of 1954, as amended, the presiding officer may issue an...

  19. 10 CFR 2.705 - Discovery-additional methods.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 10 Energy 1 2011-01-01 2011-01-01 false Discovery-additional methods. 2.705 Section 2.705 Energy NUCLEAR REGULATORY COMMISSION RULES OF PRACTICE FOR DOMESTIC LICENSING PROCEEDINGS AND ISSUANCE OF ORDERS... 147 and 181 of the Atomic Energy Act of 1954, as amended, the presiding officer may issue an...

  20. 10 CFR 2.705 - Discovery-additional methods.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... 10 Energy 1 2014-01-01 2014-01-01 false Discovery-additional methods. 2.705 Section 2.705 Energy NUCLEAR REGULATORY COMMISSION AGENCY RULES OF PRACTICE AND PROCEDURE Rules for Formal Adjudications § 2... 147 and 181 of the Atomic Energy Act of 1954, as amended, the presiding officer may issue an...

  1. Statistical methods for the geographical analysis of rare diseases.

    PubMed

    Gómez-Rubio, Virgilio; López-Quílez, Antonio

    2010-01-01

    In this chapter we provide a summary of different methods for the detection of disease clusters. First of all, we give a summary of methods for computing estimates of the relative risk. These estimates provide smoothed values of the relative risks that can account for its spatial variation. Some methods for assessing spatial autocorrelation and general clustering are also discussed to test for significant spatial variation of the risk. In order to find the actual location of the clusters, scan methods are introduced. The spatial scan statistic is discussed as well as its extension by means of Generalised Linear Models that allows for the inclusion of covariates and cluster effects. In this context, zero-inflated models are introduced to account for the high number of zeros that appear when studying rare diseases. Finally, two applications of these methods are shown using data of Systemic Lupus Erythematosus in Spain and brain cancer in Navarre (Spain).

  2. Statistical method for detecting structural change in the growth process.

    PubMed

    Ninomiya, Yoshiyuki; Yoshimoto, Atsushi

    2008-03-01

    Due to competition among individual trees and other exogenous factors that change the growth environment, each tree grows following its own growth trend with some structural changes in growth over time. In the present article, a new method is proposed to detect a structural change in the growth process. We formulate the method as a simple statistical test for signal detection without constructing any specific model for the structural change. To evaluate the p-value of the test, the tube method is developed because the regular distribution theory is insufficient. Using two sets of tree diameter growth data sampled from planted forest stands of Cryptomeria japonica in Japan, we conduct an analysis of identifying the effect of thinning on the growth process as a structural change. Our results demonstrate that the proposed method is useful to identify the structural change caused by thinning. We also provide the properties of the method in terms of the size and power of the test.

  3. A review of analytical techniques for gait data. Part 1: Fuzzy, statistical and fractal methods.

    PubMed

    Chau, T

    2001-02-01

    In recent years, several new approaches to gait data analysis have been explored, including fuzzy systems, multivariate statistical techniques and fractal dynamics. Through a critical survey of recent gait studies, this paper reviews the potential of these methods to strengthen the gait laboratory's analytical arsenal. It is found that time-honoured multivariate statistical methods are the most widely applied and understood. Although initially promising, fuzzy and fractal analyses of gait data remain largely unknown and their full potential is yet to be realized. The trend towards fusing multiple techniques in a given analysis means that additional research into the application of these two methods will benefit gait data analysis.

  4. Methods for estimating low-flow statistics for Massachusetts streams

    USGS Publications Warehouse

    Ries, Kernell G.; Friesz, Paul J.

    2000-01-01

    Methods and computer software are described in this report for determining flow duration, low-flow frequency statistics, and August median flows. These low-flow statistics can be estimated for unregulated streams in Massachusetts using different methods depending on whether the location of interest is at a streamgaging station, a low-flow partial-record station, or an ungaged site where no data are available. Low-flow statistics for streamgaging stations can be estimated using standard U.S. Geological Survey methods described in the report. The MOVE.1 mathematical method and a graphical correlation method can be used to estimate low-flow statistics for low-flow partial-record stations. The MOVE.1 method is recommended when the relation between measured flows at a partial-record station and daily mean flows at a nearby, hydrologically similar streamgaging station is linear, and the graphical method is recommended when the relation is curved. Equations are presented for computing the variance and equivalent years of record for estimates of low-flow statistics for low-flow partial-record stations when either a single or multiple index stations are used to determine the estimates. The drainage-area ratio method or regression equations can be used to estimate low-flow statistics for ungaged sites where no data are available. The drainage-area ratio method is generally as accurate as or more accurate than regression estimates when the drainage-area ratio for an ungaged site is between 0.3 and 1.5 times the drainage area of the index data-collection site. Regression equations were developed to estimate the natural, long-term 99-, 98-, 95-, 90-, 85-, 80-, 75-, 70-, 60-, and 50-percent duration flows; the 7-day, 2-year and the 7-day, 10-year low flows; and the August median flow for ungaged sites in Massachusetts. Streamflow statistics and basin characteristics for 87 to 133 streamgaging stations and low-flow partial-record stations were used to develop the equations. The

  5. Application of the Bootstrap Statistical Method in Deriving Vibroacoustic Specifications

    NASA Technical Reports Server (NTRS)

    Hughes, William O.; Paez, Thomas L.

    2006-01-01

    This paper discusses the Bootstrap Method for specification of vibroacoustic test specifications. Vibroacoustic test specifications are necessary to properly accept or qualify a spacecraft and its components for the expected acoustic, random vibration and shock environments seen on an expendable launch vehicle. Traditionally, NASA and the U.S. Air Force have employed methods of Normal Tolerance Limits to derive these test levels based upon the amount of data available, and the probability and confidence levels desired. The Normal Tolerance Limit method contains inherent assumptions about the distribution of the data. The Bootstrap is a distribution-free statistical subsampling method which uses the measured data themselves to establish estimates of statistical measures of random sources. This is achieved through the computation of large numbers of Bootstrap replicates of a data measure of interest and the use of these replicates to derive test levels consistent with the probability and confidence desired. The comparison of the results of these two methods is illustrated via an example utilizing actual spacecraft vibroacoustic data.

  6. Development of an optomechanical statistical tolerancing method for cost reduction

    NASA Astrophysics Data System (ADS)

    Lamontagne, Frédéric; Doucet, Michel

    2012-10-01

    Optical systems generally require a high level of optical components positioning precision resulting in elevated manufacturing cost. The optomechanical tolerance analysis is usually performed by the optomechanical engineer using his personal knowledge of the manufacturing precision capability. Worst case or root sum square (RSS) tolerance calculation methods are frequently used for their simplicity. In most situations, the chance to encounter the worst case error is statistically almost impossible. On the other hand, RSS method is generally not an accurate representation of the reality since it assumes centered normal distributions. Moreover, the RSS method is not suitable for multidimensional tolerance analysis that combines translational and rotational variations. An optomechanical tolerance analysis method based on Monte Carlo simulation has been developed at INO to reduce overdesign caused by pessimist manufacturing and assembly error predictions. Manufacturing data errors have been compiled and computed to be used as input for the optomechanical Monte Carlo tolerance model. This is resulting in a more realistic prediction of the optical components positioning errors (decenter, tilt and air gap). Calculated errors probabilities were validated on a real lenses barrels assembly using a high precision centering machine. Results show that the statistical error prediction is more accurate and that can relax significantly the precision required in comparison to the worst case method. Manufacturing, inspection, adjustment mechanism and alignment cost can then be reduced considerably.

  7. Introduction to statistical methods for microRNA analysis.

    PubMed

    Zararsiz, Gökmen; Coşgun, Erdal

    2014-01-01

    MicroRNA profiling is an important task to investigate miRNA functions and recent technologies such as microarray, single nucleotide polymorphism (SNP), quantitative real-time PCR (qPCR), and next-generation sequencing (NGS) have played a major role for miRNA analysis. In this chapter, we give an overview on statistical approaches for gene expressions, SNP, qPCR, and NGS data including preliminary analyses (pre-processing, differential expression, classification, clustering, exploration of interactions, and the use of ontologies). Our goal is to outline the key approaches with a brief discussion of problems avenues for their solutions and to give some examples for real-world use. Readers will be able to understand the different data formats (expression levels, sequences etc.) and they will be able to choose appropriate methods for their own research and application. On the other hand, we give brief notes on most popular tools/packages for statistical genetic analysis. This chapter aims to serve as a brief introduction to different kinds of statistical methods and also provides an extensive source of references.

  8. Statistics

    Cancer.gov

    Links to sources of cancer-related statistics, including the Surveillance, Epidemiology and End Results (SEER) Program, SEER-Medicare datasets, cancer survivor prevalence data, and the Cancer Trends Progress Report.

  9. Review of statistical methods used in enhanced-oil-recovery research and performance prediction. [131 references

    SciTech Connect

    Selvidge, J.E.

    1982-06-01

    Recent literature in the field of enhanced oil recovery (EOR) was surveyed to determine the extent to which researchers in EOR take advantage of statistical techniques in analyzing their data. In addition to determining the current level of reliance on statistical tools, another objective of this study is to promote by example the greater use of these tools. To serve this objective, the discussion of the techniques highlights the observed trend toward the use of increasingly more sophisticated methods and points out the strengths and pitfalls of different approaches. Several examples are also given of opportunities for extending EOR research findings by additional statistical manipulation. The search of the EOR literature, conducted mainly through computerized data bases, yielded nearly 200 articles containing mathematical analysis of the research. Of these, 21 were found to include examples of statistical approaches to data analysis and are discussed in detail in this review. The use of statistical techniques, as might be expected from their general purpose nature, extends across nearly all types of EOR research covering thermal methods of recovery, miscible processes, and micellar polymer floods. Data come from field tests, the laboratory, and computer simulation. The statistical methods range from simple comparisons of mean values to multiple non-linear regression equations and to probabilistic decision functions. The methods are applied to both engineering and economic data. The results of the survey are grouped by statistical technique and include brief descriptions of each of the 21 relevant papers. Complete abstracts of the papers are included in the bibliography. Brief bibliographic information (without abstracts) is also given for the articles identified in the initial search as containing mathematical analyses using other than statistical methods.

  10. Huffman and linear scanning methods with statistical language models.

    PubMed

    Roark, Brian; Fried-Oken, Melanie; Gibbons, Chris

    2015-03-01

    Current scanning access methods for text generation in AAC devices are limited to relatively few options, most notably row/column variations within a matrix. We present Huffman scanning, a new method for applying statistical language models to binary-switch, static-grid typing AAC interfaces, and compare it to other scanning options under a variety of conditions. We present results for 16 adults without disabilities and one 36-year-old man with locked-in syndrome who presents with complex communication needs and uses AAC scanning devices for writing. Huffman scanning with a statistical language model yielded significant typing speedups for the 16 participants without disabilities versus any of the other methods tested, including two row/column scanning methods. A similar pattern of results was found with the individual with locked-in syndrome. Interestingly, faster typing speeds were obtained with Huffman scanning using a more leisurely scan rate than relatively fast individually calibrated scan rates. Overall, the results reported here demonstrate great promise for the usability of Huffman scanning as a faster alternative to row/column scanning.

  11. Statistical and Mathematical Methods for Synoptic Time Domain Surveys

    NASA Astrophysics Data System (ADS)

    Mahabal, Ashish A.; SAMSI Synoptic Surveys Time Domain Working Group

    2017-01-01

    Recent advances in detector technology, electronics, data storage, and computation have enabled astronomers to collect larger and larger datasets, and moreover, pose interesting questions to answer with those data. The complexity of the data allows data science techniques to be used. These have to be grounded in sound techniques. Identify interesting mathematical and statistical challenges and working on their solutions is one of the aims of the year-long ‘Statistical, Mathematical and Computational Methods for Astronomy (ASTRO)’ program of SAMSI. Of the many working groups that have been formed, one is on Synoptic Time Domain Surveys. Within this we have various subgroups discussing topics such as Designing Statistical Features for Optimal Classification, Scheduling Observations, Incorporating Unstructured Information, Detecting Outliers, Lightcurve Decomposition and Interpolation, Domain Adaptation, and also Designing a Data Challenge. We will briefly highlight some of the work going on in these subgroups along with their interconnections, and the plans for the near future. We will also highlight the overlaps with the other SAMSI working groups and also indicate how the wider astronomy community can both participate and benefit from the activities.

  12. Feasibility of voxel-based statistical analysis method for myocardial PET

    NASA Astrophysics Data System (ADS)

    Ram Yu, A.; Kim, Jin Su; Paik, Chang H.; Kim, Kyeong Min; Moo Lim, Sang

    2014-09-01

    Although statistical parametric mapping (SPM) analysis is widely used in neuroimaging studies, to our best knowledge, there was no application to myocardial PET data analysis. In this study, we developed the voxel based statistical analysis method for myocardial PET which provides statistical comparison results between groups in image space. PET Emission data of normal and myocardial infarction rats were acquired For the SPM analysis, a rat heart template was created. In addition, individual PET data was spatially normalized and smoothed. Two sample t-tests were performed to identify the myocardial infarct region. This developed SPM method was compared with conventional ROI methods. Myocardial glucose metabolism was decreased in the lateral wall of the left ventricle. In the result of ROI analysis, the mean value of the lateral wall was 29% decreased. The newly developed SPM method for myocardial PET could provide quantitative information in myocardial PET study.

  13. How to eradicate fraudulent statistical methods: statisticians must do science

    SciTech Connect

    Bross, I.D. )

    1990-12-01

    The two steps necessary for the clinical expression of a mutagenic disease, genetic damage and viability, are countervailing forces and therefore the dosage response curve for mutagens must have a maximum. To illustrate that science is common sense reduced to calculation, a new mathematical derivation of this result and supporting data are given. This example also shows that the term 'context-free' is a snare and a delusion. When statistical methods are used in a scientific context where their assumptions are known to fail and where there is a reasonable presumption of intent to deceive, they are fraudulent. Estimation of low-level mutagenic risks by linear extrapolation from high-dose data is one example of such a method that is widely used by Executive Branch agencies. Other examples are given of fraudulent statistical methods that are currently used in biomedical research done by or for U.S. government agencies. In the long run, it is argued, the surest way to eradicate such fraud is for biostatisticians to do their own science.

  14. Estimated Accuracy of Three Common Trajectory Statistical Methods

    NASA Technical Reports Server (NTRS)

    Kabashnikov, Vitaliy P.; Chaikovsky, Anatoli P.; Kucsera, Tom L.; Metelskaya, Natalia S.

    2011-01-01

    Three well-known trajectory statistical methods (TSMs), namely concentration field (CF), concentration weighted trajectory (CWT), and potential source contribution function (PSCF) methods were tested using known sources and artificially generated data sets to determine the ability of TSMs to reproduce spatial distribution of the sources. In the works by other authors, the accuracy of the trajectory statistical methods was estimated for particular species and at specified receptor locations. We have obtained a more general statistical estimation of the accuracy of source reconstruction and have found optimum conditions to reconstruct source distributions of atmospheric trace substances. Only virtual pollutants of the primary type were considered. In real world experiments, TSMs are intended for application to a priori unknown sources. Therefore, the accuracy of TSMs has to be tested with all possible spatial distributions of sources. An ensemble of geographical distributions of virtual sources was generated. Spearman s rank order correlation coefficient between spatial distributions of the known virtual and the reconstructed sources was taken to be a quantitative measure of the accuracy. Statistical estimates of the mean correlation coefficient and a range of the most probable values of correlation coefficients were obtained. All the TSMs that were considered here showed similar close results. The maximum of the ratio of the mean correlation to the width of the correlation interval containing the most probable correlation values determines the optimum conditions for reconstruction. An optimal geographical domain roughly coincides with the area supplying most of the substance to the receptor. The optimal domain s size is dependent on the substance decay time. Under optimum reconstruction conditions, the mean correlation coefficients can reach 0.70 0.75. The boundaries of the interval with the most probable correlation values are 0.6 0.9 for the decay time of 240 h

  15. FOREWORD: Special issue on Statistical and Probabilistic Methods for Metrology

    NASA Astrophysics Data System (ADS)

    Bich, Walter; Cox, Maurice G.

    2006-08-01

    This special issue of Metrologia is the first that is not devoted to units, or constants, or measurement techniques in some specific field of metrology, but to the generic topic of statistical and probabilistic methods for metrology. The number of papers on this subject in measurement journals, and in Metrologia in particular, has continued to increase over the years, driven by the publication of the Guide to the Expression of Uncertainty in Measurement (GUM) [1] and the Mutual Recognition Arrangement (MRA) of the CIPM [2]. The former stimulated metrologists to think in greater depth about the appropriate modelling of their measurements, in order to provide uncertainty evaluations associated with measurement results. The latter obliged the metrological community to investigate reliable measures for assessing the calibration and measurement capabilities declared by the national metrology institutes (NMIs). Furthermore, statistical analysis of measurement data became even more important than hitherto, with the need, on the one hand, to treat the greater quantities of data provided by sophisticated measurement systems, and, on the other, to deal appropriately with relatively small sets of data that are difficult or expensive to obtain. The importance of supporting the GUM and extending its provisions was recognized by the formation in the year 2000 of Working Group 1, Measurement uncertainty, of the Joint Committee for Guides in Metrology. The need to provide guidance on key comparison data evaluation was recognized by the formation in the year 2001 of the BIPM Director's Advisory Group on Uncertainty. A further international initiative was the revision, in the year 2004, of the remit and title of a working group of ISO/TC 69, Application of Statistical Methods, to reflect the need to concentrate more on statistical methods to support measurement uncertainty evaluation. These international activities are supplemented by national programmes such as the Software Support

  16. A test statistic for the affected-sib-set method.

    PubMed

    Lange, K

    1986-07-01

    This paper discusses generalizations of the affected-sib-pair method. First, the requirement that sib identity-by-descent relations be known unambiguously is relaxed by substituting sib identity-by-state relations. This permits affected sibs to be used even when their parents are unavailable for typing. In the limit of an infinite number of marker alleles each of infinitesimal population frequency, the identity-by-state relations coincide with the usual identity-by-descent relations. Second, a weighted pairs test statistic is proposed that covers affected sib sets of size greater than two. These generalizations make the affected-sib-pair method a more powerful technique for detecting departures from independent segregation of disease and marker phenotypes. A sample calculation suggests such a departure for tuberculoid leprosy and the HLA D locus.

  17. Statistical methods for active pharmacovigilance, with applications to diabetes drugs.

    PubMed

    Zhuo, Lan; Farrell, Patrick J; McNair, Doug; Krewski, Daniel

    2014-01-01

    Pharmacovigilance aims to identify adverse drug reactions using postmarket surveillance data under real-world conditions of use. Unlike passive pharmacovigilance, which is based on largely voluntary (and hence incomplete) spontaneous reports of adverse drug reactions with limited information on patient characteristics, active pharmacovigilance is based on electronic health records containing detailed information about patient populations, thereby allowing consideration of modifying factors such as polypharmacy and comorbidity, as well as sociodemographic characteristics. With the present shift toward active pharmacovigilance, statistical methods capable of addressing the complexities of such data are needed. We describe four such methods here, and demonstrate their application in the analysis of a large retrospective cohort of diabetics taking anti-hyperglycemic medications that may increase the risk of adverse cardiovascular events.

  18. New Statistical Learning Methods for Estimating Optimal Dynamic Treatment Regimes

    PubMed Central

    Zhao, Ying-Qi; Zeng, Donglin; Laber, Eric B.; Kosorok, Michael R.

    2014-01-01

    Dynamic treatment regimes (DTRs) are sequential decision rules for individual patients that can adapt over time to an evolving illness. The goal is to accommodate heterogeneity among patients and find the DTR which will produce the best long term outcome if implemented. We introduce two new statistical learning methods for estimating the optimal DTR, termed backward outcome weighted learning (BOWL), and simultaneous outcome weighted learning (SOWL). These approaches convert individualized treatment selection into an either sequential or simultaneous classification problem, and can thus be applied by modifying existing machine learning techniques. The proposed methods are based on directly maximizing over all DTRs a nonparametric estimator of the expected long-term outcome; this is fundamentally different than regression-based methods, for example Q-learning, which indirectly attempt such maximization and rely heavily on the correctness of postulated regression models. We prove that the resulting rules are consistent, and provide finite sample bounds for the errors using the estimated rules. Simulation results suggest the proposed methods produce superior DTRs compared with Q-learning especially in small samples. We illustrate the methods using data from a clinical trial for smoking cessation. PMID:26236062

  19. Developing improved metamodels by combining phenomenological reasoning with statistical methods

    NASA Astrophysics Data System (ADS)

    Bigelow, James H.; Davis, Paul K.

    2002-07-01

    A metamodel is relatively small, simple model that approximates the behavior of a large, complex model. A common and superficially attractive way to develop a metamodel is to generate data from a number of large-model runs and to then use off-the-shelf statistical methods without attempting to understand the models internal workings. This paper describes research illuminating why it is important and fruitful, in some problems, to improve the quality of such metamodels by using various types of phenomenological knowledge. The benefits are sometimes mathematically subtle, but strategically important, as when one is dealing with a system that could fail if any of several critical components fail. Naive metamodels may fail to reflect the individual criticality of such components and may therefore be quite misleading if used for policy analysis. Na*ve metamodeling may also give very misleading results on the relative importance of inputs, thereby skewing resource-allocation decisions. By inserting an appropriate dose of theory, however, such problems can be greatly mitigated. Our work is intended to be a contribution to the emerging understanding of multiresolution, multiperspective modeling (MRMPM), as well as a contribution to interdisciplinary work combining virtues of statistical methodology with virtues of more theory-based work. Although the analysis we present is based on a particular experiment with a particular large and complex model, we believe that the insights are more general.

  20. A Statistical Method for Estimating Luminosity Functions Using Truncated Data

    NASA Astrophysics Data System (ADS)

    Schafer, Chad M.

    2007-06-01

    The observational limitations of astronomical surveys lead to significant statistical inference challenges. One such challenge is the estimation of luminosity functions given redshift (z) and absolute magnitude (M) measurements from an irregularly truncated sample of objects. This is a bivariate density estimation problem; we develop here a statistically rigorous method which (1) does not assume a strict parametric form for the bivariate density; (2) does not assume independence between redshift and absolute magnitude (and hence allows evolution of the luminosity function with redshift); (3) does not require dividing the data into arbitrary bins; and (4) naturally incorporates a varying selection function. We accomplish this by decomposing the bivariate density φ(z,M) vialogφ(z,M)=f(z)+g(M)+h(z,M,θ), where f and g are estimated nonparametrically and h takes an assumed parametric form. There is a simple way of estimating the integrated mean squared error of the estimator; smoothing parameters are selected to minimize this quantity. Results are presented from the analysis of a sample of quasars.

  1. A Statistical Method to Distinguish Functional Brain Networks

    PubMed Central

    Fujita, André; Vidal, Maciel C.; Takahashi, Daniel Y.

    2017-01-01

    One major problem in neuroscience is the comparison of functional brain networks of different populations, e.g., distinguishing the networks of controls and patients. Traditional algorithms are based on search for isomorphism between networks, assuming that they are deterministic. However, biological networks present randomness that cannot be well modeled by those algorithms. For instance, functional brain networks of distinct subjects of the same population can be different due to individual characteristics. Moreover, networks of subjects from different populations can be generated through the same stochastic process. Thus, a better hypothesis is that networks are generated by random processes. In this case, subjects from the same group are samples from the same random process, whereas subjects from different groups are generated by distinct processes. Using this idea, we developed a statistical test called ANOGVA to test whether two or more populations of graphs are generated by the same random graph model. Our simulations' results demonstrate that we can precisely control the rate of false positives and that the test is powerful to discriminate random graphs generated by different models and parameters. The method also showed to be robust for unbalanced data. As an example, we applied ANOGVA to an fMRI dataset composed of controls and patients diagnosed with autism or Asperger. ANOGVA identified the cerebellar functional sub-network as statistically different between controls and autism (p < 0.001). PMID:28261045

  2. A Statistical Method to Distinguish Functional Brain Networks.

    PubMed

    Fujita, André; Vidal, Maciel C; Takahashi, Daniel Y

    2017-01-01

    One major problem in neuroscience is the comparison of functional brain networks of different populations, e.g., distinguishing the networks of controls and patients. Traditional algorithms are based on search for isomorphism between networks, assuming that they are deterministic. However, biological networks present randomness that cannot be well modeled by those algorithms. For instance, functional brain networks of distinct subjects of the same population can be different due to individual characteristics. Moreover, networks of subjects from different populations can be generated through the same stochastic process. Thus, a better hypothesis is that networks are generated by random processes. In this case, subjects from the same group are samples from the same random process, whereas subjects from different groups are generated by distinct processes. Using this idea, we developed a statistical test called ANOGVA to test whether two or more populations of graphs are generated by the same random graph model. Our simulations' results demonstrate that we can precisely control the rate of false positives and that the test is powerful to discriminate random graphs generated by different models and parameters. The method also showed to be robust for unbalanced data. As an example, we applied ANOGVA to an fMRI dataset composed of controls and patients diagnosed with autism or Asperger. ANOGVA identified the cerebellar functional sub-network as statistically different between controls and autism (p < 0.001).

  3. Comparison of prediction performance using statistical postprocessing methods

    NASA Astrophysics Data System (ADS)

    Han, Keunhee; Choi, JunTae; Kim, Chansoo

    2016-11-01

    As the 2018 Winter Olympics are to be held in Pyeongchang, both general weather information on Pyeongchang and specific weather information on this region, which can affect game operation and athletic performance, are required. An ensemble prediction system has been applied to provide more accurate weather information, but it has bias and dispersion due to the limitations and uncertainty of its model. In this study, homogeneous and nonhomogeneous regression models as well as Bayesian model averaging (BMA) were used to reduce the bias and dispersion existing in ensemble prediction and to provide probabilistic forecast. Prior to applying the prediction methods, reliability of the ensemble forecasts was tested by using a rank histogram and a residualquantile-quantile plot to identify the ensemble forecasts and the corresponding verifications. The ensemble forecasts had a consistent positive bias, indicating over-forecasting, and were under-dispersed. To correct such biases, statistical post-processing methods were applied using fixed and sliding windows. The prediction skills of methods were compared by using the mean absolute error, root mean square error, continuous ranked probability score, and continuous ranked probability skill score. Under the fixed window, BMA exhibited better prediction skill than the other methods in most observation station. Under the sliding window, on the other hand, homogeneous and non-homogeneous regression models with positive regression coefficients exhibited better prediction skill than BMA. In particular, the homogeneous regression model with positive regression coefficients exhibited the best prediction skill.

  4. Methods for the additive manufacturing of semiconductor and crystal materials

    SciTech Connect

    Stowe, Ashley C.; Speight, Douglas

    2016-11-22

    A method for the additive manufacturing of inorganic crystalline materials, including: physically combining a plurality of starting materials that are used to form an inorganic crystalline compound to be used as one or more of a semiconductor, scintillator, laser crystal, and optical filter; heating or melting successive regions of the combined starting materials using a directed heat source having a predetermined energy characteristic, thereby facilitating the reaction of the combined starting materials; and allowing each region of the combined starting materials to cool in a controlled manner, such that the desired inorganic crystalline compound results. The method also includes, prior to heating or melting the successive regions of the combined starting materials using the directed heat source, heating the combined starting materials to facilitate initial reaction of the combined starting materials. The method further includes translating the combined starting materials and/or the directed heat source between successive locations. The method still further includes controlling the mechanical, electrical, photonic, and/or optical properties of the inorganic crystalline compound.

  5. Jet Noise Diagnostics Supporting Statistical Noise Prediction Methods

    NASA Technical Reports Server (NTRS)

    Bridges, James E.

    2006-01-01

    compared against measurements of mean and rms velocity statistics over a range of jet speeds and temperatures. Models for flow parameters used in the acoustic analogy, most notably the space-time correlations of velocity, have been compared against direct measurements, and modified to better fit the observed data. These measurements have been extremely challenging for hot, high speed jets, and represent a sizeable investment in instrumentation development. As an intermediate check that the analysis is predicting the physics intended, phased arrays have been employed to measure source distributions for a wide range of jet cases. And finally, careful far-field spectral directivity measurements have been taken for final validation of the prediction code. Examples of each of these experimental efforts will be presented. The main result of these efforts is a noise prediction code, named JeNo, which is in middevelopment. JeNo is able to consistently predict spectral directivity, including aft angle directivity, for subsonic cold jets of most geometries. Current development on JeNo is focused on extending its capability to hot jets, requiring inclusion of a previously neglected second source associated with thermal fluctuations. A secondary result of the intensive experimentation is the archiving of various flow statistics applicable to other acoustic analogies and to development of time-resolved prediction methods. These will be of lasting value as we look ahead at future challenges to the aeroacoustic experimentalist.

  6. Statistical Methods for Rapid Aerothermal Analysis and Design Technology: Validation

    NASA Technical Reports Server (NTRS)

    DePriest, Douglas; Morgan, Carolyn

    2003-01-01

    The cost and safety goals for NASA s next generation of reusable launch vehicle (RLV) will require that rapid high-fidelity aerothermodynamic design tools be used early in the design cycle. To meet these requirements, it is desirable to identify adequate statistical models that quantify and improve the accuracy, extend the applicability, and enable combined analyses using existing prediction tools. The initial research work focused on establishing suitable candidate models for these purposes. The second phase is focused on assessing the performance of these models to accurately predict the heat rate for a given candidate data set. This validation work compared models and methods that may be useful in predicting the heat rate.

  7. Data and statistical methods for analysis of trends and patterns

    SciTech Connect

    Atwood, C.L.; Gentillon, C.D.; Wilson, G.E.

    1992-11-01

    This report summarizes topics considered at a working meeting on data and statistical methods for analysis of trends and patterns in US commercial nuclear power plants. This meeting was sponsored by the Office of Analysis and Evaluation of Operational Data (AEOD) of the Nuclear Regulatory Commission (NRC). Three data sets are briefly described: Nuclear Plant Reliability Data System (NPRDS), Licensee Event Report (LER) data, and Performance Indicator data. Two types of study are emphasized: screening studies, to see if any trends or patterns appear to be present; and detailed studies, which are more concerned with checking the analysis assumptions, modeling any patterns that are present, and searching for causes. A prescription is given for a screening study, and ideas are suggested for a detailed study, when the data take of any of three forms: counts of events per time, counts of events per demand, and non-event data.

  8. Efficacy of lipase from Aspergillus niger as an additive in detergent formulations: a statistical approach.

    PubMed

    Saisubramanian, N; Edwinoliver, N G; Nandakumar, N; Kamini, N R; Puvanakrishnan, R

    2006-08-01

    The efficacy of lipase from Aspergillus niger MTCC 2594 as an additive in laundry detergent formulations was assessed using response surface methodology (RSM). A five-level four-factorial central composite design was chosen to explain the washing protocol with four critical factors, viz. detergent concentration, lipase concentration, buffer pH and washing temperature. The model suggested that all the factors chosen had a significant impact on oil removal and the optimal conditions for the removal of olive oil from cotton fabric were 1.0% detergent, 75 U of lipase, buffer pH of 9.5 and washing temperature of 25 degrees C. Under optimal conditions, the removal of olive oil from cotton fabric was 33 and 17.1% at 25 and 49 degrees C, respectively, in the presence of lipase over treatment with detergent alone. Hence, lipase from A. niger could be effectively used as an additive in detergent formulation for the removal of triglyceride soil both in cold and warm wash conditions.

  9. Characterization of hourly NOx atmospheric concentrations near the Venice International Airport with additive semi-parametric statistical models

    NASA Astrophysics Data System (ADS)

    Valotto, Gabrio; Varin, Cristiano

    2016-01-01

    An additive modeling approach is employed to provide a statistical description of hourly variation in concentrations of NOx measured in proximity of the Venice "Marco Polo" International Airport, Italy. Differently from several previous studies on airport emissions based on daily time series, the paper analyzes hourly data because variations of NOx concentrations during the day are informative about the prevailing emission source. The statistical analysis is carried out using a one-year time series. Confounder effects due to seasonality, meteorology and airport traffic volume are accounted for by suitable covariates. Four different model specifications of increasing complexity are considered. The model with the aircraft source expressed as the NOx emitted near the airport is found to have the best predictive quality. Although the aircraft source is statistically significant, the comparison of model-based predictions suggests that the relative impact of aircraft emissions to ambient NOx concentrations is limited and the road traffic is the likely dominant source near the sampling point.

  10. Statistically qualified neuro-analytic failure detection method and system

    DOEpatents

    Vilim, Richard B.; Garcia, Humberto E.; Chen, Frederick W.

    2002-03-02

    An apparatus and method for monitoring a process involve development and application of a statistically qualified neuro-analytic (SQNA) model to accurately and reliably identify process change. The development of the SQNA model is accomplished in two stages: deterministic model adaption and stochastic model modification of the deterministic model adaptation. Deterministic model adaption involves formulating an analytic model of the process representing known process characteristics, augmenting the analytic model with a neural network that captures unknown process characteristics, and training the resulting neuro-analytic model by adjusting the neural network weights according to a unique scaled equation error minimization technique. Stochastic model modification involves qualifying any remaining uncertainty in the trained neuro-analytic model by formulating a likelihood function, given an error propagation equation, for computing the probability that the neuro-analytic model generates measured process output. Preferably, the developed SQNA model is validated using known sequential probability ratio tests and applied to the process as an on-line monitoring system. Illustrative of the method and apparatus, the method is applied to a peristaltic pump system.

  11. Systematic variational method for statistical nonlinear state and parameter estimation

    NASA Astrophysics Data System (ADS)

    Ye, Jingxin; Rey, Daniel; Kadakia, Nirag; Eldridge, Michael; Morone, Uriel I.; Rozdeba, Paul; Abarbanel, Henry D. I.; Quinn, John C.

    2015-11-01

    In statistical data assimilation one evaluates the conditional expected values, conditioned on measurements, of interesting quantities on the path of a model through observation and prediction windows. This often requires working with very high dimensional integrals in the discrete time descriptions of the observations and model dynamics, which become functional integrals in the continuous-time limit. Two familiar methods for performing these integrals include (1) Monte Carlo calculations and (2) variational approximations using the method of Laplace plus perturbative corrections to the dominant contributions. We attend here to aspects of the Laplace approximation and develop an annealing method for locating the variational path satisfying the Euler-Lagrange equations that comprises the major contribution to the integrals. This begins with the identification of the minimum action path starting with a situation where the model dynamics is totally unresolved in state space, and the consistent minimum of the variational problem is known. We then proceed to slowly increase the model resolution, seeking to remain in the basin of the minimum action path, until a path that gives the dominant contribution to the integral is identified. After a discussion of some general issues, we give examples of the assimilation process for some simple, instructive models from the geophysical literature. Then we explore a slightly richer model of the same type with two distinct time scales. This is followed by a model characterizing the biophysics of individual neurons.

  12. Solid form additives and method of forming same

    SciTech Connect

    Schuettenberg, A.D.; Gragson, J.T.

    1987-01-27

    This patent describes a solid form additive comprising: a normally liquid fuel additive selected from carburetor detergent additives, antiknock additives, deposit-control additives, and mixtures thereof, suitable for use in fuel comprising gasoline for internal combustion engines; and a structural agent for containing the fuel additive and for providing dimensional stability to the solid form additive, the structural agent being soluble and dispersible in the fuel; wherein the fuel additive comprises between about 25% and about 75% by weight of the solid form additive; and wherein the solid form additive is a pellet having structural agent and fuel additive essentially homogeneously dispersed throughout the solid form additive; and wherein the pellet is coated with a sealing agent.

  13. Study of complex networks using statistical physics methods

    NASA Astrophysics Data System (ADS)

    Chen, Yiping

    The goal of this thesis is to study the behaviors of complex networks in several aspects using methods from statistical physics. Networks are structures that consist of nodes and links. By changing the way links connect to nodes, different complex network structures can be constructed such as Erdḧs-Renyi (ER) networks and scale-free (SF) networks. Complex networks have wide relevance to many real world problems, including the spread of disease in human society, message routing in the Internet, etc. In this thesis analytical and simulation results are obtained regarding optimal paths in disordered networks, fragmentation of social networks, and improved strategies for immunization against diseases. In the study of disordered systems, of particular current interest is the scaling behavior of the optimal path length ℓopt from strong disorder to weak disorder state for different weight distributions P(w). Here we derive analytically a new criterion. Using this criterion we find that for all P(w) that possess a strong-weak disorder crossover, the distributions p(ℓ) of the optimal path lengths display the same universal behavior. Fragmentation in social networks is also studied using methods from percolation theory. Recently, a new measure of fragmentation F has been developed in social network studies. For each removal of a subset of links or nodes, F is defined as the ratio between the number of pairs of nodes that are not connected in the fragmented network after removal, and the total number of pairs in the original fully connected network. We study the statistical behavior of F using both analytical and numerical methods and relate it to the traditional measure of fragmentation, the relative size of the largest cluster, Pinfinity, used in percolation theory. Finally, we tried to find a better immunization strategy. It is widely accepted that the most efficient immunization strategies are based on "targeted" strategies. Here we propose a novel "equal graph

  14. Reexamination of Statistical Methods for Comparative Anatomy: Examples of Its Application and Comparisons with Other Parametric and Nonparametric Statistics

    PubMed Central

    Aversi-Ferreira, Roqueline A. G. M. F.; Nishijo, Hisao; Aversi-Ferreira, Tales Alexandre

    2015-01-01

    Various statistical methods have been published for comparative anatomy. However, few studies compared parametric and nonparametric statistical methods. Moreover, some previous studies using statistical method for comparative anatomy (SMCA) proposed the formula for comparison of groups of anatomical structures (multiple structures) among different species. The present paper described the usage of SMCA and compared the results by SMCA with those by parametric test (t-test) and nonparametric analyses (cladistics) of anatomical data. In conclusion, the SMCA can offer a more exact and precise way to compare single and multiple anatomical structures across different species, which requires analyses of nominal features in comparative anatomy. PMID:26413553

  15. Reexamination of Statistical Methods for Comparative Anatomy: Examples of Its Application and Comparisons with Other Parametric and Nonparametric Statistics.

    PubMed

    Aversi-Ferreira, Roqueline A G M F; Nishijo, Hisao; Aversi-Ferreira, Tales Alexandre

    2015-01-01

    Various statistical methods have been published for comparative anatomy. However, few studies compared parametric and nonparametric statistical methods. Moreover, some previous studies using statistical method for comparative anatomy (SMCA) proposed the formula for comparison of groups of anatomical structures (multiple structures) among different species. The present paper described the usage of SMCA and compared the results by SMCA with those by parametric test (t-test) and nonparametric analyses (cladistics) of anatomical data. In conclusion, the SMCA can offer a more exact and precise way to compare single and multiple anatomical structures across different species, which requires analyses of nominal features in comparative anatomy.

  16. A review of statistical methods for prediction of proteolytic cleavage.

    PubMed

    duVerle, David A; Mamitsuka, Hiroshi

    2012-05-01

    A fundamental component of systems biology, proteolytic cleavage is involved in nearly all aspects of cellular activities: from gene regulation to cell lifecycle regulation. Current sequencing technologies have made it possible to compile large amount of cleavage data and brought greater understanding of the underlying protein interactions. However, the practical impossibility to exhaustively retrieve substrate sequences through experimentation alone has long highlighted the need for efficient computational prediction methods. Such methods must be able to quickly mark substrate candidates and putative cleavage sites for further analysis. Available methods and expected reliability depend heavily on the type and complexity of proteolytic action, as well as the availability of well-labelled experimental data sets: factors varying greatly across enzyme families. For this review, we chose to give a quick overview of the general issues and challenges in cleavage prediction methods followed by a more in-depth presentation of major techniques and implementations, with a focus on two particular families of cysteine proteases: caspases and calpains. Through their respective differences in proteolytic specificity (high for caspases, broader for calpains) and data availability (much lower for calpains), we aimed to illustrate the strengths and limitations of techniques ranging from position-based matrices and decision trees to more flexible machine-learning methods such as hidden Markov models and Support Vector Machines. In addition to a technical overview for each family of algorithms, we tried to provide elements of evaluation and performance comparison across methods.

  17. System Synthesis in Preliminary Aircraft Design using Statistical Methods

    NASA Technical Reports Server (NTRS)

    DeLaurentis, Daniel; Mavris, Dimitri N.; Schrage, Daniel P.

    1996-01-01

    This paper documents an approach to conceptual and preliminary aircraft design in which system synthesis is achieved using statistical methods, specifically design of experiments (DOE) and response surface methodology (RSM). These methods are employed in order to more efficiently search the design space for optimum configurations. In particular, a methodology incorporating three uses of these techniques is presented. First, response surface equations are formed which represent aerodynamic analyses, in the form of regression polynomials, which are more sophisticated than generally available in early design stages. Next, a regression equation for an overall evaluation criterion is constructed for the purpose of constrained optimization at the system level. This optimization, though achieved in a innovative way, is still traditional in that it is a point design solution. The methodology put forward here remedies this by introducing uncertainty into the problem, resulting a solutions which are probabilistic in nature. DOE/RSM is used for the third time in this setting. The process is demonstrated through a detailed aero-propulsion optimization of a high speed civil transport. Fundamental goals of the methodology, then, are to introduce higher fidelity disciplinary analyses to the conceptual aircraft synthesis and provide a roadmap for transitioning from point solutions to probabalistic designs (and eventually robust ones).

  18. Statistical methods for mapping quantitative trait loci from a dense set of markers.

    PubMed Central

    Dupuis, J; Siegmund, D

    1999-01-01

    Lander and Botstein introduced statistical methods for searching an entire genome for quantitative trait loci (QTL) in experimental organisms, with emphasis on a backcross design and QTL having only additive effects. We extend their results to intercross and other designs, and we compare the power of the resulting test as a function of the magnitude of the additive and dominance effects, the sample size and intermarker distances. We also compare three methods for constructing confidence regions for a QTL: likelihood regions, Bayesian credible sets, and support regions. We show that with an appropriate evaluation of the coverage probability a support region is approximately a confidence region, and we provide a theroretical explanation of the empirical observation that the size of the support region is proportional to the sample size, not the square root of the sample size, as one might expect from standard statistical theory. PMID:9872974

  19. Fuzzy Filtering Method for Color Videos Corrupted by Additive Noise

    PubMed Central

    Ponomaryov, Volodymyr I.; Montenegro-Monroy, Hector; Nino-de-Rivera, Luis

    2014-01-01

    A novel method for the denoising of color videos corrupted by additive noise is presented in this paper. The proposed technique consists of three principal filtering steps: spatial, spatiotemporal, and spatial postprocessing. In contrast to other state-of-the-art algorithms, during the first spatial step, the eight gradient values in different directions for pixels located in the vicinity of a central pixel as well as the R, G, and B channel correlation between the analogous pixels in different color bands are taken into account. These gradient values give the information about the level of contamination then the designed fuzzy rules are used to preserve the image features (textures, edges, sharpness, chromatic properties, etc.). In the second step, two neighboring video frames are processed together. Possible local motions between neighboring frames are estimated using block matching procedure in eight directions to perform interframe filtering. In the final step, the edges and smoothed regions in a current frame are distinguished for final postprocessing filtering. Numerous simulation results confirm that this novel 3D fuzzy method performs better than other state-of-the-art techniques in terms of objective criteria (PSNR, MAE, NCD, and SSIM) as well as subjective perception via the human vision system in the different color videos. PMID:24688428

  20. Methods in probability and statistical inference. Final report, June 15, 1975-June 30, 1979. [Dept. of Statistics, Univ. of Chicago

    SciTech Connect

    Wallace, D L; Perlman, M D

    1980-06-01

    This report describes the research activities of the Department of Statistics, University of Chicago, during the period June 15, 1975 to July 30, 1979. Nine research projects are briefly described on the following subjects: statistical computing and approximation techniques in statistics; numerical computation of first passage distributions; probabilities of large deviations; combining independent tests of significance; small-sample efficiencies of tests and estimates; improved procedures for simultaneous estimation and testing of many correlations; statistical computing and improved regression methods; comparison of several populations; and unbiasedness in multivariate statistics. A description of the statistical consultation activities of the Department that are of interest to DOE, in particular, the scientific interactions between the Department and the scientists at Argonne National Laboratories, is given. A list of publications issued during the term of the contract is included.

  1. Hydrologic extremes - an intercomparison of multiple gridded statistical downscaling methods

    NASA Astrophysics Data System (ADS)

    Werner, Arelia T.; Cannon, Alex J.

    2016-04-01

    Gridded statistical downscaling methods are the main means of preparing climate model data to drive distributed hydrological models. Past work on the validation of climate downscaling methods has focused on temperature and precipitation, with less attention paid to the ultimate outputs from hydrological models. Also, as attention shifts towards projections of extreme events, downscaling comparisons now commonly assess methods in terms of climate extremes, but hydrologic extremes are less well explored. Here, we test the ability of gridded downscaling models to replicate historical properties of climate and hydrologic extremes, as measured in terms of temporal sequencing (i.e. correlation tests) and distributional properties (i.e. tests for equality of probability distributions). Outputs from seven downscaling methods - bias correction constructed analogues (BCCA), double BCCA (DBCCA), BCCA with quantile mapping reordering (BCCAQ), bias correction spatial disaggregation (BCSD), BCSD using minimum/maximum temperature (BCSDX), the climate imprint delta method (CI), and bias corrected CI (BCCI) - are used to drive the Variable Infiltration Capacity (VIC) model over the snow-dominated Peace River basin, British Columbia. Outputs are tested using split-sample validation on 26 climate extremes indices (ClimDEX) and two hydrologic extremes indices (3-day peak flow and 7-day peak flow). To characterize observational uncertainty, four atmospheric reanalyses are used as climate model surrogates and two gridded observational data sets are used as downscaling target data. The skill of the downscaling methods generally depended on reanalysis and gridded observational data set. However, CI failed to reproduce the distribution and BCSD and BCSDX the timing of winter 7-day low-flow events, regardless of reanalysis or observational data set. Overall, DBCCA passed the greatest number of tests for the ClimDEX indices, while BCCAQ, which is designed to more accurately resolve event

  2. Hydrologic extremes - an intercomparison of multiple gridded statistical downscaling methods

    NASA Astrophysics Data System (ADS)

    Werner, A. T.; Cannon, A. J.

    2015-06-01

    Gridded statistical downscaling methods are the main means of preparing climate model data to drive distributed hydrological models. Past work on the validation of climate downscaling methods has focused on temperature and precipitation, with less attention paid to the ultimate outputs from hydrological models. Also, as attention shifts towards projections of extreme events, downscaling comparisons now commonly assess methods in terms of climate extremes, but hydrologic extremes are less well explored. Here, we test the ability of gridded downscaling models to replicate historical properties of climate and hydrologic extremes, as measured in terms of temporal sequencing (i.e., correlation tests) and distributional properties (i.e., tests for equality of probability distributions). Outputs from seven downscaling methods - bias correction constructed analogues (BCCA), double BCCA (DBCCA), BCCA with quantile mapping reordering (BCCAQ), bias correction spatial disaggregation (BCSD), BCSD using minimum/maximum temperature (BCSDX), climate imprint delta method (CI), and bias corrected CI (BCCI) - are used to drive the Variable Infiltration Capacity (VIC) model over the snow-dominated Peace River basin, British Columbia. Outputs are tested using split-sample validation on 26 climate extremes indices (ClimDEX) and two hydrologic extremes indices (3 day peak flow and 7 day peak flow). To characterize observational uncertainty, four atmospheric reanalyses are used as climate model surrogates and two gridded observational datasets are used as downscaling target data. The skill of the downscaling methods generally depended on reanalysis and gridded observational dataset. However, CI failed to reproduce the distribution and BCSD and BCSDX the timing of winter 7 day low flow events, regardless of reanalysis or observational dataset. Overall, DBCCA passed the greatest number of tests for the ClimDEX indices, while BCCAQ, which is designed to more accurately resolve event

  3. Tips and Tricks for Successful Application of Statistical Methods to Biological Data.

    PubMed

    Schlenker, Evelyn

    2016-01-01

    This chapter discusses experimental design and use of statistics to describe characteristics of data (descriptive statistics) and inferential statistics that test the hypothesis posed by the investigator. Inferential statistics, based on probability distributions, depend upon the type and distribution of the data. For data that are continuous, randomly and independently selected, as well as normally distributed more powerful parametric tests such as Student's t test and analysis of variance (ANOVA) can be used. For non-normally distributed or skewed data, transformation of the data (using logarithms) may normalize the data allowing use of parametric tests. Alternatively, with skewed data nonparametric tests can be utilized, some of which rely on data that are ranked prior to statistical analysis. Experimental designs and analyses need to balance between committing type 1 errors (false positives) and type 2 errors (false negatives). For a variety of clinical studies that determine risk or benefit, relative risk ratios (random clinical trials and cohort studies) or odds ratios (case-control studies) are utilized. Although both use 2 × 2 tables, their premise and calculations differ. Finally, special statistical methods are applied to microarray and proteomics data, since the large number of genes or proteins evaluated increase the likelihood of false discoveries. Additional studies in separate samples are used to verify microarray and proteomic data. Examples in this chapter and references are available to help continued investigation of experimental designs and appropriate data analysis.

  4. Developing Students' Thought Processes for Choosing Appropriate Statistical Methods

    ERIC Educational Resources Information Center

    Murray, James; Knowles, Elizabeth

    2014-01-01

    Students often struggle to select appropriate statistical tests when investigating research questions. The authors present a lesson study designed to make students' thought processes visible while considering this choice. The authors taught their students a way to organize knowledge about statistical tests and observed its impact in the classroom…

  5. Equivalence Class Formation: A Method for Teaching Statistical Interactions

    ERIC Educational Resources Information Center

    Fields, Lanny; Travis, Robert; Roy, Deborah; Yadlovker, Eytan; de Aguiar-Rocha, Liliane; Sturmey, Peter

    2009-01-01

    Many students struggle with statistical concepts such as interaction. In an experimental group, participants took a paper-and-pencil test and then were given training to establish equivalent classes containing four different statistical interactions. All participants formed the equivalence classes and showed maintenance when probes contained novel…

  6. Determination of Reference Catalogs for Meridian Observations Using Statistical Method

    NASA Astrophysics Data System (ADS)

    Li, Z. Y.

    2014-09-01

    The meridian observational data are useful for developing high-precision planetary ephemerides of the solar system. These historical data are provided by the jet propulsion laboratory (JPL) or the Institut De Mecanique Celeste Et De Calcul Des Ephemerides (IMCCE). However, we find that the reference systems (realized by the fundamental catalogs FK3 (Third Fundamental Catalogue), FK4 (Fourth Fundamental Catalogue), and FK5 (Fifth Fundamental Catalogue), or Hipparcos), to which the observations are referred, are not given explicitly for some sets of data. The incompleteness of information prevents us from eliminating the systematic effects due to the different fundamental catalogs. The purpose of this paper is to specify clearly the reference catalogs of these observations with the problems in their records by using the JPL DE421 ephemeris. The data for the corresponding planets in the geocentric celestial reference system (GCRS) obtained from the DE421 are transformed to the apparent places with different hypothesis regarding the reference catalogs. Then the validations of the hypothesis are tested by two kinds of statistical quantities which are used to indicate the significance of difference between the original and transformed data series. As a result, this method is proved to be effective for specifying the reference catalogs, and the missed information is determined unambiguously. Finally these meridian data are transformed to the GCRS for further applications in the development of planetary ephemerides.

  7. Method for controlling a laser additive process using intrinsic illumination

    NASA Astrophysics Data System (ADS)

    Tait, Robert; Cai, Guoshuang; Azer, Magdi; Chen, Xiaobin; Liu, Yong; Harding, Kevin

    2015-05-01

    One form of additive manufacturing is to use a laser to generate a melt pool from powdered metal that is sprayed from a nozzle. The laser net-shape machining system builds the part a layer at a time by following a predetermined path. However, because the path may need to take many turns, maintaining a constant melt pool may not be easy. A straight section may require one speed and power while a sharp bend would over melt the metal at the same settings. This paper describes a process monitoring method that uses the intrinsic IR radiation from the melt pool along with a process model configured to establish target values for the parameters associated with the manufacture or repair. This model is based upon known properties of the metal being used as well as the properties of the laser beam. An adaptive control technique is then employed to control process parameters of the machining system based upon the real-time weld pool measurement. Since the system uses the heat radiant from the melt pool, other previously deposited metal does not confuse the system as only the melted material is seen by the camera.

  8. Meta-analysis for Discovering Rare-Variant Associations: Statistical Methods and Software Programs.

    PubMed

    Tang, Zheng-Zheng; Lin, Dan-Yu

    2015-07-02

    There is heightened interest in using next-generation sequencing technologies to identify rare variants that influence complex human diseases and traits. Meta-analysis is essential to this endeavor because large sample sizes are required for detecting associations with rare variants. In this article, we provide a comprehensive overview of statistical methods for meta-analysis of sequencing studies for discovering rare-variant associations. Specifically, we discuss the calculation of relevant summary statistics from participating studies, the construction of gene-level association tests, the choice of transformation for quantitative traits, the use of fixed-effects versus random-effects models, and the removal of shadow association signals through conditional analysis. We also show that meta-analysis based on properly calculated summary statistics is as powerful as joint analysis of individual-participant data. In addition, we demonstrate the performance of different meta-analysis methods by using both simulated and empirical data. We then compare four major software packages for meta-analysis of rare-variant associations-MASS, RAREMETAL, MetaSKAT, and seqMeta-in terms of the underlying statistical methodology, analysis pipeline, and software interface. Finally, we present PreMeta, a software interface that integrates the four meta-analysis packages and allows a consortium to combine otherwise incompatible summary statistics.

  9. Statistical methods in joint modeling of longitudinal and survival data

    NASA Astrophysics Data System (ADS)

    Dempsey, Walter

    Survival studies often generate not only a survival time for each patient but also a sequence of health measurements at annual or semi-annual check-ups while the patient remains alive. Such a sequence of random length accompanied by a survival time is called a survival process. Ordinarily robust health is associated with longer survival, so the two parts of a survival process cannot be assumed independent. The first part of the thesis is concerned with a general technique---reverse alignment---for constructing statistical models for survival processes. A revival model is a regression model in the sense that it incorporates covariate and treatment effects into both the distribution of survival times and the joint distribution of health outcomes. The revival model also determines a conditional survival distribution given the observed history, which describes how the subsequent survival distribution is determined by the observed progression of health outcomes. The second part of the thesis explores the concept of a consistent exchangeable survival process---a joint distribution of survival times in which the risk set evolves as a continuous-time Markov process with homogeneous transition rates. A correspondence with the de Finetti approach of constructing an exchangeable survival process by generating iid survival times conditional on a completely independent hazard measure is shown. Several specific processes are detailed, showing how the number of blocks of tied failure times grows asymptotically with the number of individuals in each case. In particular, we show that the set of Markov survival processes with weakly continuous predictive distributions can be characterized by a two-dimensional family called the harmonic process. The outlined methods are then applied to data, showing how they can be easily extended to handle censoring and inhomogeneity among patients.

  10. Introducing 3D U-statistic method for separating anomaly from background in exploration geochemical data with associated software development

    NASA Astrophysics Data System (ADS)

    Ghannadpour, Seyyed Saeed; Hezarkhani, Ardeshir

    2016-03-01

    The U-statistic method is one of the most important structural methods to separate the anomaly from the background. It considers the location of samples and carries out the statistical analysis of the data without judging from a geochemical point of view and tries to separate subpopulations and determine anomalous areas. In the present study, to use U-statistic method in three-dimensional (3D) condition, U-statistic is applied on the grade of two ideal test examples, by considering sample Z values (elevation). So far, this is the first time that this method has been applied on a 3D condition. To evaluate the performance of 3D U-statistic method and in order to compare U-statistic with one non-structural method, the method of threshold assessment based on median and standard deviation (MSD method) is applied on the two example tests. Results show that the samples indicated by U-statistic method as anomalous are more regular and involve less dispersion than those indicated by the MSD method. So that, according to the location of anomalous samples, denser areas of them can be determined as promising zones. Moreover, results show that at a threshold of U = 0, the total error of misclassification for U-statistic method is much smaller than the total error of criteria of bar {x}+n× s. Finally, 3D model of two test examples for separating anomaly from background using 3D U-statistic method is provided. The source code for a software program, which was developed in the MATLAB programming language in order to perform the calculations of the 3D U-spatial statistic method, is additionally provided. This software is compatible with all the geochemical varieties and can be used in similar exploration projects.

  11. Statistical Signal Processing Methods in Scattering and Imaging

    NASA Astrophysics Data System (ADS)

    Zambrano Nunez, Maytee

    This Ph.D. dissertation project addresses two related topics in wave-based signal processing: 1) Cramer-Rao bound (CRB) analysis of scattering systems formed by pointlike scatterers in one-dimensional (1D) and three-dimensional (3D) spaces. 2) Compressive optical coherent imaging, based on the incorporation of sparsity priors in the reconstructions. The first topic addresses for wave scattering systems in 1D and 3D spaces the information content about scattering parameters, in particular, the targets' positions and strengths, and derived quantities, that is contained in scattering data corresponding to reflective, transmissive, and more general sensing modalities. This part of the dissertation derives the Cramer-Rao bound (CRB) for the estimation of parameters of scalar wave scattering systems formed by point scatterers. The results shed light on the fundamental difference between the approximate Born approximation model for weak scatterers and the more general multiple scattering model, and facilitate the identification of regions in parameter space where multiple scattering facilitates or obstructs the estimation of parameters from scattering data, as well as of sensing configurations giving maximal or minimal information about the parameters. The derived results are illustrated with numerical examples, with particular emphasis on the imaging resolution which we quantify via a relative resolution index borrowed from a previous paper. Additionally, this work investigates fundamental limits of estimation performance for the localization of the targets and the inverse scattering problem. The second topic of the effort describes a novel compressive-sensing-based technique for optical imaging with a coherent single-detector system. This hybrid opto-micro-electromechanical, coherent single-detector imaging system applies the latest developments in the nascent field of compressive sensing to the problem of computational imaging of wavefield intensity from a small number

  12. Reliability and applications of statistical methods based on oligonucleotide frequencies in bacterial and archaeal genomes

    PubMed Central

    Bohlin, Jon; Skjerve, Eystein; Ussery, David W

    2008-01-01

    Background The increasing number of sequenced prokaryotic genomes contains a wealth of genomic data that needs to be effectively analysed. A set of statistical tools exists for such analysis, but their strengths and weaknesses have not been fully explored. The statistical methods we are concerned with here are mainly used to examine similarities between archaeal and bacterial DNA from different genomes. These methods compare observed genomic frequencies of fixed-sized oligonucleotides with expected values, which can be determined by genomic nucleotide content, smaller oligonucleotide frequencies, or be based on specific statistical distributions. Advantages with these statistical methods include measurements of phylogenetic relationship with relatively small pieces of DNA sampled from almost anywhere within genomes, detection of foreign/conserved DNA, and homology searches. Our aim was to explore the reliability and best suited applications for some popular methods, which include relative oligonucleotide frequencies (ROF), di- to hexanucleotide zero'th order Markov methods (ZOM) and 2.order Markov chain Method (MCM). Tests were performed on distant homology searches with large DNA sequences, detection of foreign/conserved DNA, and plasmid-host similarity comparisons. Additionally, the reliability of the methods was tested by comparing both real and random genomic DNA. Results Our findings show that the optimal method is context dependent. ROFs were best suited for distant homology searches, whilst the hexanucleotide ZOM and MCM measures were more reliable measures in terms of phylogeny. The dinucleotide ZOM method produced high correlation values when used to compare real genomes to an artificially constructed random genome with similar %GC, and should therefore be used with care. The tetranucleotide ZOM measure was a good measure to detect horizontally transferred regions, and when used to compare the phylogenetic relationships between plasmids and hosts

  13. Debating Curricular Strategies for Teaching Statistics and Research Methods: What Does the Current Evidence Suggest?

    ERIC Educational Resources Information Center

    Barron, Kenneth E.; Apple, Kevin J.

    2014-01-01

    Coursework in statistics and research methods is a core requirement in most undergraduate psychology programs. However, is there an optimal way to structure and sequence methodology courses to facilitate student learning? For example, should statistics be required before research methods, should research methods be required before statistics, or…

  14. Refining developmental coordination disorder subtyping with multivariate statistical methods

    PubMed Central

    2012-01-01

    Background With a large number of potentially relevant clinical indicators penalization and ensemble learning methods are thought to provide better predictive performance than usual linear predictors. However, little is known about how they perform in clinical studies where few cases are available. We used Random Forests and Partial Least Squares Discriminant Analysis to select the most salient impairments in Developmental Coordination Disorder (DCD) and assess patients similarity. Methods We considered a wide-range testing battery for various neuropsychological and visuo-motor impairments which aimed at characterizing subtypes of DCD in a sample of 63 children. Classifiers were optimized on a training sample, and they were used subsequently to rank the 49 items according to a permuted measure of variable importance. In addition, subtyping consistency was assessed with cluster analysis on the training sample. Clustering fitness and predictive accuracy were evaluated on the validation sample. Results Both classifiers yielded a relevant subset of items impairments that altogether accounted for a sharp discrimination between three DCD subtypes: ideomotor, visual-spatial and constructional, and mixt dyspraxia. The main impairments that were found to characterize the three subtypes were: digital perception, imitations of gestures, digital praxia, lego blocks, visual spatial structuration, visual motor integration, coordination between upper and lower limbs. Classification accuracy was above 90% for all classifiers, and clustering fitness was found to be satisfactory. Conclusions Random Forests and Partial Least Squares Discriminant Analysis are useful tools to extract salient features from a large pool of correlated binary predictors, but also provide a way to assess individuals proximities in a reduced factor space. Less than 15 neuro-visual, neuro-psychomotor and neuro-psychological tests might be required to provide a sensitive and specific diagnostic of DCD on this

  15. Outliers in Statistical Analysis: Basic Methods of Detection and Accommodation.

    ERIC Educational Resources Information Center

    Jacobs, Robert

    Researchers are often faced with the prospect of dealing with observations within a given data set that are unexpected in terms of their great distance from the concentration of observations. For their potential to influence the mean disproportionately, thus affecting many statistical analyses, outlying observations require special care on the…

  16. Accountability Indicators from the Viewpoint of Statistical Method.

    ERIC Educational Resources Information Center

    Jordan, Larry

    Few people seriously regard students as "products" coming off an educational assembly line, but notions about accountability and quality improvement in higher education are pervaded by manufacturing ideas and metaphors. Because numerical indicators of quality are inevitably expressed by trend lines or statistical control chars of some kind, they…

  17. Statistical methods of combining information: Applications to sensor data fusion

    SciTech Connect

    Burr, T.

    1996-12-31

    This paper reviews some statistical approaches to combining information from multiple sources. Promising new approaches will be described, and potential applications to combining not-so-different data sources such as sensor data will be discussed. Experiences with one real data set are described.

  18. Basic Statistical Concepts and Methods for Earth Scientists

    USGS Publications Warehouse

    Olea, Ricardo A.

    2008-01-01

    INTRODUCTION Statistics is the science of collecting, analyzing, interpreting, modeling, and displaying masses of numerical data primarily for the characterization and understanding of incompletely known systems. Over the years, these objectives have lead to a fair amount of analytical work to achieve, substantiate, and guide descriptions and inferences.

  19. Critical Realism and Statistical Methods--A Response to Nash

    ERIC Educational Resources Information Center

    Scott, David

    2007-01-01

    This article offers a defence of critical realism in the face of objections Nash (2005) makes to it in a recent edition of this journal. It is argued that critical and scientific realisms are closely related and that both are opposed to statistical positivism. However, the suggestion is made that scientific realism retains (from statistical…

  20. Using Non-Linear Statistical Methods with Laboratory Kinetic Data

    NASA Technical Reports Server (NTRS)

    Anicich, Vincent

    1997-01-01

    This paper will demonstrate the usefulness of standard non-linear statistical analysis on ICR and SIFT kinetic data. The specific systems used in the demonstration are the isotopic and change transfer reactions in the system of H2O+/D2O, H30+/D2O, and other permutations.

  1. Additives and method for controlling clathrate hydrates in fluid systems

    DOEpatents

    Sloan, Jr., Earle Dendy; Christiansen, Richard Lee; Lederhos, Joseph P.; Long, Jin Ping; Panchalingam, Vaithilingam; Du, Yahe; Sum, Amadeu Kun Wan

    1997-01-01

    Discussed is a process for preventing clathrate hydrate masses from detrimentally impeding the possible flow of a fluid susceptible to clathrate hydrate formation. The process is particularly useful in the natural gas and petroleum production, transportation and processing industry where gas hydrate formation can cause serious problems. Additives preferably contain one or more five member, six member and/or seven member cyclic chemical groupings. Additives include polymers having lactam rings. Additives can also contain polyelectrolytes that are believed to improve conformance of polymer additives through steric hinderance and/or charge repulsion. Also, polymers having an amide on which a C.sub.1 -C.sub.4 group is attached to the nitrogen and/or the carbonyl carbon of the amide may be used alone, or in combination with ring-containing polymers for enhanced effectiveness. Polymers having at least some repeating units representative of polymerizing at least one of an oxazoline, an N-substituted acrylamide and an N-vinyl alkyl amide are preferred.

  2. Additives and method for controlling clathrate hydrates in fluid systems

    DOEpatents

    Sloan, E.D. Jr.; Christiansen, R.L.; Lederhos, J.P.; Long, J.P.; Panchalingam, V.; Du, Y.; Sum, A.K.W.

    1997-06-17

    Discussed is a process for preventing clathrate hydrate masses from detrimentally impeding the possible flow of a fluid susceptible to clathrate hydrate formation. The process is particularly useful in the natural gas and petroleum production, transportation and processing industry where gas hydrate formation can cause serious problems. Additives preferably contain one or more five member, six member and/or seven member cyclic chemical groupings. Additives include polymers having lactam rings. Additives can also contain polyelectrolytes that are believed to improve conformance of polymer additives through steric hindrance and/or charge repulsion. Also, polymers having an amide on which a C{sub 1}-C{sub 4} group is attached to the nitrogen and/or the carbonyl carbon of the amide may be used alone, or in combination with ring-containing polymers for enhanced effectiveness. Polymers having at least some repeating units representative of polymerizing at least one of an oxazoline, an N-substituted acrylamide and an N-vinyl alkyl amide are preferred.

  3. Gasoline and Diesel Fuel Test Methods Additional Resources

    EPA Pesticide Factsheets

    Supporting documents on the Direct Final Rule that allows refiners and laboratories to use more current and improved fuel testing procedures for twelve American Society for Testing and Materials analytical test methods.

  4. Statistical Methods for Rapid Aerothermal Analysis and Design Technology

    NASA Technical Reports Server (NTRS)

    Morgan, Carolyn; DePriest, Douglas; Thompson, Richard (Technical Monitor)

    2002-01-01

    The cost and safety goals for NASA's next generation of reusable launch vehicle (RLV) will require that rapid high-fidelity aerothermodynamic design tools be used early in the design cycle. To meet these requirements, it is desirable to establish statistical models that quantify and improve the accuracy, extend the applicability, and enable combined analyses using existing prediction tools. The research work was focused on establishing the suitable mathematical/statistical models for these purposes. It is anticipated that the resulting models can be incorporated into a software tool to provide rapid, variable-fidelity, aerothermal environments to predict heating along an arbitrary trajectory. This work will support development of an integrated design tool to perform automated thermal protection system (TPS) sizing and material selection.

  5. System and method for high power diode based additive manufacturing

    DOEpatents

    El-Dasher, Bassem S.; Bayramian, Andrew; Demuth, James A.; Farmer, Joseph C.; Torres, Sharon G.

    2016-04-12

    A system is disclosed for performing an Additive Manufacturing (AM) fabrication process on a powdered material forming a substrate. The system may make use of a diode array for generating an optical signal sufficient to melt a powdered material of the substrate. A mask may be used for preventing a first predetermined portion of the optical signal from reaching the substrate, while allowing a second predetermined portion to reach the substrate. At least one processor may be used for controlling an output of the diode array.

  6. Modification of codes NUALGAM and BREMRAD. Volume 3: Statistical considerations of the Monte Carlo method

    NASA Technical Reports Server (NTRS)

    Firstenberg, H.

    1971-01-01

    The statistics are considered of the Monte Carlo method relative to the interpretation of the NUGAM2 and NUGAM3 computer code results. A numerical experiment using the NUGAM2 code is presented and the results are statistically interpreted.

  7. M&M's "The Method," and Other Ideas about Teaching Elementary Statistics.

    ERIC Educational Resources Information Center

    May, E. Lee Jr.

    2000-01-01

    Consists of a collection of observations about the teaching of the first course in elementary probability and statistics offered by many colleges and universities. Highlights the Goldberg Method for solving problems in probability and statistics. (Author/ASK)

  8. Addition and Subtraction. Mathematics-Methods Program Unit.

    ERIC Educational Resources Information Center

    LeBlanc, John F.; And Others

    This unit is 1 of 12 developed for the university classroom portion of the Mathematics-Methods Program (MMP), created by the Indiana University Mathematics Education Development Center (MEDC) as an innovative program for the mathematics training of prospective elementary school teachers (PSTs). Each unit is written in an activity format that…

  9. Impact of mass addition on extreme water level statistics during storms along the coast of the Mediterranean Sea

    NASA Astrophysics Data System (ADS)

    Lionello, Piero; Conte, Dario; Marzo, Luigi; Scarascia, Luca

    2015-04-01

    In the Mediterranean Sea there are two contrasting factors affecting the maximum level that water will reach during a storm in the next decades: the increase of mean sea level and the decrease of storminess. Future reduction of storminess, which is associated with a decreased intensity of the Mediterranean branch on the north hemisphere storm track, will determine a reduction of maxima of wind wave height and storm surge levels. Changes of mean sea level are produced by regional steric effects and by net mass addition. While it is possible to compute the steric effects with regional models, mass addition is ultimately the consequence of a remote cause: the melting of Greenland and Antarctica ice caps. This study considers four indicators of extreme water levels, which, ranked in order of increasing values: the average of the 10 largest annual maxima (wlind10), the largest annual maximum (wlind1), the 5 (rv5) and 50 (rv50) year return level. The analysis is based on a coordinated set of wave and storm surge simulation forced by inputs provided by regional climate model simulations that were carried out in the CIRCE EU-fp7 and cover the period 1951-2050. Accounting for all affecting factors but the mass addition, in about 60% of the Mediterranean coast reduced storminess and steric expansion will compensate each other and produce no significant change of maximum water level statistics. The remaining 40% of the coastline is almost equally divided between significant positive and negative changes. However, if a supplementary sea level increase, representing the effect of water mass addition, is added, the fraction of the coast with significant positive/negative changes increase/decrease quickly. If mass addition would contribute 10cm, there will be no significant negative changes and for any indicator. With a 20cm addition the increase would be significant for wlind10, wlind1, rv5 along more than 75% of the Mediterranean coastline. With a 35cm addition the increase

  10. Applying Statistical Methods To The Proton Radius Puzzle

    NASA Astrophysics Data System (ADS)

    Higinbotham, Douglas

    2016-03-01

    In recent nuclear physics publications, one can find many examples where chi2 and reduced chi2 are the only tools used for the selection of models even though a chi2 difference test is only meaningful for nested models. With this in mind, we reanalyze electron scattering data, being careful to clearly define our selection criteria as well as using a co-variance matrix and confidence levels as per the statistics section of the particle data book. We will show that when applying such techniques to hydrogen elastic scattering data, the nested models often require fewer parameters than typically used and that non-nested models are often rejected inappropriately.

  11. A novel statistical method for behaviour sequence analysis and its application to birdsong.

    PubMed

    Alger, Sarah J; Larget, Bret R; Riters, Lauren V

    2016-06-01

    Complex vocal signals, such as birdsong, contain acoustic elements that differ in both order and duration. These elements may convey socially relevant meaning, both independently and through their interactions, yet statistical methods that combine order and duration data to extract meaning have not, to our knowledge, been fully developed. Here we design novel semi-Markov methods, Bayesian estimation and classification trees to extract order and duration information from behavioural sequences and apply these methods to songs produced by male European starlings, Sturnus vulgaris, in two social contexts in which the function of song differs: a spring (breeding) and autumn (nonbreeding) context. Additionally, previous data indicate that damage to the medial preoptic nucleus (POM), a brain area known to regulate male sexually motivated behaviour, affects structural aspects of starling song such that males in a sexually relevant context (i.e. spring) sing shorter songs than appropriate for this context. We further test the utility of our statistical approach by comparing attributes of song structure in POM-lesioned males to song produced by control spring and autumn males. Spring and autumn songs were statistically separable based on the duration and order of phrase types. Males produced more structurally complex aspects of song in spring than in autumn. Spring song was also longer and more stereotyped than autumn song, both attributes used by females to select mates. Songs produced by POM-lesioned males in some cases fell between measures of spring and autumn songs but differed most from songs produced by autumn males. Overall, these statistical methods can effectively extract biologically meaningful information contained in many behavioural sequences given sufficient sample sizes and replication numbers.

  12. Statistical methods for the analysis of climate extremes

    NASA Astrophysics Data System (ADS)

    Naveau, Philippe; Nogaj, Marta; Ammann, Caspar; Yiou, Pascal; Cooley, Daniel; Jomelli, Vincent

    2005-08-01

    Currently there is an increasing research activity in the area of climate extremes because they represent a key manifestation of non-linear systems and an enormous impact on economic and social human activities. Our understanding of the mean behavior of climate and its 'normal' variability has been improving significantly during the last decades. In comparison, climate extreme events have been hard to study and even harder to predict because they are, by definition, rare and obey different statistical laws than averages. In this context, the motivation for this paper is twofold. Firstly, we recall the basic principles of Extreme Value Theory that is used on a regular basis in finance and hydrology, but it still does not have the same success in climate studies. More precisely, the theoretical distributions of maxima and large peaks are recalled. The parameters of such distributions are estimated with the maximum likelihood estimation procedure that offers the flexibility to take into account explanatory variables in our analysis. Secondly, we detail three case-studies to show that this theory can provide a solid statistical foundation, specially when assessing the uncertainty associated with extreme events in a wide range of applications linked to the study of our climate. To cite this article: P. Naveau et al., C. R. Geoscience 337 (2005).

  13. Comparison and validation of statistical methods for predicting power outage durations in the event of hurricanes.

    PubMed

    Nateghi, Roshanak; Guikema, Seth D; Quiring, Steven M

    2011-12-01

    This article compares statistical methods for modeling power outage durations during hurricanes and examines the predictive accuracy of these methods. Being able to make accurate predictions of power outage durations is valuable because the information can be used by utility companies to plan their restoration efforts more efficiently. This information can also help inform customers and public agencies of the expected outage times, enabling better collective response planning, and coordination of restoration efforts for other critical infrastructures that depend on electricity. In the long run, outage duration estimates for future storm scenarios may help utilities and public agencies better allocate risk management resources to balance the disruption from hurricanes with the cost of hardening power systems. We compare the out-of-sample predictive accuracy of five distinct statistical models for estimating power outage duration times caused by Hurricane Ivan in 2004. The methods compared include both regression models (accelerated failure time (AFT) and Cox proportional hazard models (Cox PH)) and data mining techniques (regression trees, Bayesian additive regression trees (BART), and multivariate additive regression splines). We then validate our models against two other hurricanes. Our results indicate that BART yields the best prediction accuracy and that it is possible to predict outage durations with reasonable accuracy.

  14. Protein stability: computation, sequence statistics, and new experimental methods

    PubMed Central

    Magliery, Thomas J.

    2015-01-01

    Calculating protein stability and predicting stabilizing mutations remain exceedingly difficult tasks, largely due to the inadequacy of potential functions, the difficulty of modeling entropy and the unfolded state, and challenges of sampling, particularly of backbone conformations. Yet, computational design has produced some remarkably stable proteins in recent years, apparently owing to near ideality in structure and sequence features. With caveats, computational prediction of stability can be used to guide mutation, and mutations derived from consensus sequence analysis, especially improved by recent co-variation filters, are very likely to stabilize without sacrificing function. The combination of computational and statistical approaches with library approaches, including new technologies such as deep sequencing and high throughput stability measurements, point to a very exciting near term future for stability engineering, even with difficult computational issues remaining. PMID:26497286

  15. Statistical Methods and Tools for Hanford Staged Feed Tank Sampling

    SciTech Connect

    Fountain, Matthew S.; Brigantic, Robert T.; Peterson, Reid A.

    2013-10-01

    This report summarizes work conducted by Pacific Northwest National Laboratory to technically evaluate the current approach to staged feed sampling of high-level waste (HLW) sludge to meet waste acceptance criteria (WAC) for transfer from tank farms to the Hanford Waste Treatment and Immobilization Plant (WTP). The current sampling and analysis approach is detailed in the document titled Initial Data Quality Objectives for WTP Feed Acceptance Criteria, 24590-WTP-RPT-MGT-11-014, Revision 0 (Arakali et al. 2011). The goal of this current work is to evaluate and provide recommendations to support a defensible, technical and statistical basis for the staged feed sampling approach that meets WAC data quality objectives (DQOs).

  16. PNS and statistical experiments simulation in subcritical systems using Monte-Carlo method on example of Yalina-Thermal assembly

    NASA Astrophysics Data System (ADS)

    Sadovich, Sergey; Talamo, A.; Burnos, V.; Kiyavitskaya, H.; Fokov, Yu.

    2014-06-01

    In subcritical systems driven by an external neutron source, the experimental methods based on pulsed neutron source and statistical techniques play an important role for reactivity measurement. Simulation of these methods is very time-consumed procedure. For simulations in Monte-Carlo programs several improvements for neutronic calculations have been made. This paper introduces a new method for simulation PNS and statistical measurements. In this method all events occurred in the detector during simulation are stored in a file using PTRAC feature in the MCNP. After that with a special code (or post-processing) PNS and statistical methods can be simulated. Additionally different shapes of neutron pulses and its lengths as well as dead time of detectors can be included into simulation. The methods described above were tested on subcritical assembly Yalina-Thermal, located in Joint Institute for Power and Nuclear Research SOSNY, Minsk, Belarus. A good agreement between experimental and simulated results was shown.

  17. Monitoring Method of Cutting Force by Using Additional Spindle Sensors

    NASA Astrophysics Data System (ADS)

    Sarhan, Ahmed Aly Diaa; Matsubara, Atsushi; Sugihara, Motoyuki; Saraie, Hidenori; Ibaraki, Soichi; Kakino, Yoshiaki

    This paper describes a monitoring method of cutting forces for end milling process by using displacement sensors. Four eddy-current displacement sensors are installed on the spindle housing of a machining center so that they can detect the radial motion of the rotating spindle. Thermocouples are also attached to the spindle structure in order to examine the thermal effect in the displacement sensing. The change in the spindle stiffness due to the spindle temperature and the speed is investigated as well. Finally, the estimation performance of cutting forces using the spindle displacement sensors is experimentally investigated by machining tests on carbon steel in end milling operations under different cutting conditions. It is found that the monitoring errors are attributable to the thermal displacement of the spindle, the time lag of the sensing system, and the modeling error of the spindle stiffness. It is also shown that the root mean square errors between estimated and measured amplitudes of cutting forces are reduced to be less than 20N with proper selection of the linear stiffness.

  18. Statistical energy analysis response prediction methods for structural systems

    NASA Technical Reports Server (NTRS)

    Davis, R. F.

    1979-01-01

    The results of an effort to document methods for accomplishing response predictions for commonly encountered aerospace structural configurations is presented. Application of these methods to specified aerospace structure to provide sample analyses is included. An applications manual, with the structural analyses appended as example problems is given. Comparisons of the response predictions with measured data are provided for three of the example problems.

  19. Statistical methods for conducting agreement (comparison of clinical tests) and precision (repeatability or reproducibility) studies in optometry and ophthalmology.

    PubMed

    McAlinden, Colm; Khadka, Jyoti; Pesudovs, Konrad

    2011-07-01

    The ever-expanding choice of ocular metrology and imaging equipment has driven research into the validity of their measurements. Consequently, studies of the agreement between two instruments or clinical tests have proliferated in the ophthalmic literature. It is important that researchers apply the appropriate statistical tests in agreement studies. Correlation coefficients are hazardous and should be avoided. The 'limits of agreement' method originally proposed by Altman and Bland in 1983 is the statistical procedure of choice. Its step-by-step use and practical considerations in relation to optometry and ophthalmology are detailed in addition to sample size considerations and statistical approaches to precision (repeatability or reproducibility) estimates.

  20. Students' Attitudes toward Statistics across the Disciplines: A Mixed-Methods Approach

    ERIC Educational Resources Information Center

    Griffith, James D.; Adams, Lea T.; Gu, Lucy L.; Hart, Christian L.; Nichols-Whitehead, Penney

    2012-01-01

    Students' attitudes toward statistics were investigated using a mixed-methods approach including a discovery-oriented qualitative methodology among 684 undergraduate students across business, criminal justice, and psychology majors where at least one course in statistics was required. Students were asked about their attitudes toward statistics and…

  1. Figaro: a novel statistical method for vector sequence removal

    PubMed Central

    White, James Robert; Roberts, Michael; Yorke, James A.; Pop, Mihai

    2009-01-01

    Motivation Sequences produced by automated Sanger sequencing machines frequently contain fragments of the cloning vector on their ends. Software tools currently available for identifying and removing the vector sequence require knowledge of the vector sequence, specific splice sites and any adapter sequences used in the experiment—information often omitted from public databases. Furthermore, the clipping coordinates themselves are missing or incorrectly reported. As an example, within the ~1.24 billion shotgun sequences deposited in the NCBI Trace Archive, as many as ~735 million (~60%) lack vector clipping information. Correct clipping information is essential to scientists attempting to validate, improve and even finish the increasingly large number of genomes released at a ‘draft’ quality level. Results We present here Figaro, a novel software tool for identifying and removing the vector from raw sequence data without prior knowledge of the vector sequence. The vector sequence is automatically inferred by analyzing the frequency of occurrence of short oligo-nucleotides using Poisson statistics. We show that Figaro achieves 99.98% sensitivity when tested on ~1.5 million shotgun reads from Drosophila pseudoobscura. We further explore the impact of accurate vector trimming on the quality of whole-genome assemblies by re-assembling two bacterial genomes from shotgun sequences deposited in the Trace Archive. Designed as a module in large computational pipelines, Figaro is fast, lightweight and flexible. Availability Figaro is released under an open-source license through the AMOS package (http://amos.sourceforge.net/Figaro). PMID:18202027

  2. Comparison of Statistical Methods for Detector Testing Programs

    SciTech Connect

    Rennie, John Alan; Abhold, Mark

    2016-10-14

    A typical goal for any detector testing program is to ascertain not only the performance of the detector systems under test, but also the confidence that systems accepted using that testing program’s acceptance criteria will exceed a minimum acceptable performance (which is usually expressed as the minimum acceptable success probability, p). A similar problem often arises in statistics, where we would like to ascertain the fraction, p, of a population of items that possess a property that may take one of two possible values. Typically, the problem is approached by drawing a fixed sample of size n, with the number of items out of n that possess the desired property, x, being termed successes. The sample mean gives an estimate of the population mean p ≈ x/n, although usually it is desirable to accompany such an estimate with a statement concerning the range within which p may fall and the confidence associated with that range. Procedures for establishing such ranges and confidence limits are described in detail by Clopper, Brown, and Agresti for two-sided symmetric confidence intervals.

  3. Statistical methods for analyzing Drosophila germline mutation rates.

    PubMed

    Fu, Yun-Xin

    2013-08-01

    Most studies of mutation rates implicitly assume that they remain constant throughout development of the germline. However, researchers recently used a novel statistical framework to reveal that mutation rates differ dramatically during sperm development in Drosophila melanogaster. Here a general framework is described for the inference of germline mutation patterns, generated from either mutation screening experiments or DNA sequence polymorphism data, that enables analysis of more than two mutations per family. The inference is made more rigorous and flexible by providing a better approximation of the probabilities of patterns of mutations and an improved coalescent algorithm within a single host with realistic assumptions. The properties of the inference framework, both the estimation and the hypothesis testing, were investigated by simulation. The refined inference framework is shown to provide (1) nearly unbiased maximum-likelihood estimates of mutation rates and (2) robust hypothesis testing using the standard asymptotic distribution of the likelihood-ratio tests. It is readily applicable to data sets in which multiple mutations in the same family are common.

  4. Instrumental and statistical methods for the comparison of class evidence

    NASA Astrophysics Data System (ADS)

    Liszewski, Elisa Anne

    Trace evidence is a major field within forensic science. Association of trace evidence samples can be problematic due to sample heterogeneity and a lack of quantitative criteria for comparing spectra or chromatograms. The aim of this study is to evaluate different types of instrumentation for their ability to discriminate among samples of various types of trace evidence. Chemometric analysis, including techniques such as Agglomerative Hierarchical Clustering, Principal Components Analysis, and Discriminant Analysis, was employed to evaluate instrumental data. First, automotive clear coats were analyzed by using microspectrophotometry to collect UV absorption data. In total, 71 samples were analyzed with classification accuracy of 91.61%. An external validation was performed, resulting in a prediction accuracy of 81.11%. Next, fiber dyes were analyzed using UV-Visible microspectrophotometry. While several physical characteristics of cotton fiber can be identified and compared, fiber color is considered to be an excellent source of variation, and thus was examined in this study. Twelve dyes were employed, some being visually indistinguishable. Several different analyses and comparisons were done, including an inter-laboratory comparison and external validations. Lastly, common plastic samples and other polymers were analyzed using pyrolysis-gas chromatography/mass spectrometry, and their pyrolysis products were then analyzed using multivariate statistics. The classification accuracy varied dependent upon the number of classes chosen, but the plastics were grouped based on composition. The polymers were used as an external validation and misclassifications occurred with chlorinated samples all being placed into the category containing PVC.

  5. Data Analysis & Statistical Methods for Command File Errors

    NASA Technical Reports Server (NTRS)

    Meshkat, Leila; Waggoner, Bruce; Bryant, Larry

    2014-01-01

    This paper explains current work on modeling for managing the risk of command file errors. It is focused on analyzing actual data from a JPL spaceflight mission to build models for evaluating and predicting error rates as a function of several key variables. We constructed a rich dataset by considering the number of errors, the number of files radiated, including the number commands and blocks in each file, as well as subjective estimates of workload and operational novelty. We have assessed these data using different curve fitting and distribution fitting techniques, such as multiple regression analysis, and maximum likelihood estimation to see how much of the variability in the error rates can be explained with these. We have also used goodness of fit testing strategies and principal component analysis to further assess our data. Finally, we constructed a model of expected error rates based on the what these statistics bore out as critical drivers to the error rate. This model allows project management to evaluate the error rate against a theoretically expected rate as well as anticipate future error rates.

  6. Statistical Methods for Predicting Malaria Incidences Using Data from Sudan

    PubMed Central

    Awadalla, Khidir E.

    2017-01-01

    Malaria is the leading cause of illness and death in Sudan. The entire population is at risk of malaria epidemics with a very high burden on government and population. The usefulness of forecasting methods in predicting the number of future incidences is needed to motivate the development of a system that can predict future incidences. The objective of this paper is to develop applicable and understood time series models and to find out what method can provide better performance to predict future incidences level. We used monthly incidence data collected from five states in Sudan with unstable malaria transmission. We test four methods of the forecast: (1) autoregressive integrated moving average (ARIMA); (2) exponential smoothing; (3) transformation model; and (4) moving average. The result showed that transformation method performed significantly better than the other methods for Gadaref, Gazira, North Kordofan, and Northern, while the moving average model performed significantly better for Khartoum. Future research should combine a number of different and dissimilar methods of time series to improve forecast accuracy with the ultimate aim of developing a simple and useful model for producing reasonably reliable forecasts of the malaria incidence in the study area. PMID:28367352

  7. Compensation and additivity of anthropogenic mortality: life-history effects and review of methods.

    PubMed

    Péron, Guillaume

    2013-03-01

    Demographic compensation, the increase in average individual performance following a perturbation that reduces population size, and, its opposite, demographic overadditivity (or superadditivity) are central processes in both population ecology and wildlife management. A continuum of population responses to changes in cause-specific mortality exists, of which additivity and complete compensation constitute particular points. The position of a population on that continuum influences its ability to sustain exploitation and predation. Here I describe a method for quantifying where a population is on the continuum. Based on variance-covariance formulae, I describe a simple metric for the rate of compensation-additivity. I synthesize the results from 10 wildlife capture-recapture monitoring programmes from the literature and online databases, reviewing current statistical methods and the treatment of common sources of bias. These results are used to test hypotheses regarding the effects of life-history strategy, population density, average cause-specific mortality and age class on the rate of compensation-additivity. This comparative analysis highlights that long-lived species compensate less than short-lived species and that populations below their carrying capacity compensate less than those above.

  8. Statistical methods and neural network approaches for classification of data from multiple sources

    NASA Technical Reports Server (NTRS)

    Benediktsson, Jon Atli; Swain, Philip H.

    1990-01-01

    Statistical methods for classification of data from multiple data sources are investigated and compared to neural network models. A problem with using conventional multivariate statistical approaches for classification of data of multiple types is in general that a multivariate distribution cannot be assumed for the classes in the data sources. Another common problem with statistical classification methods is that the data sources are not equally reliable. This means that the data sources need to be weighted according to their reliability but most statistical classification methods do not have a mechanism for this. This research focuses on statistical methods which can overcome these problems: a method of statistical multisource analysis and consensus theory. Reliability measures for weighting the data sources in these methods are suggested and investigated. Secondly, this research focuses on neural network models. The neural networks are distribution free since no prior knowledge of the statistical distribution of the data is needed. This is an obvious advantage over most statistical classification methods. The neural networks also automatically take care of the problem involving how much weight each data source should have. On the other hand, their training process is iterative and can take a very long time. Methods to speed up the training procedure are introduced and investigated. Experimental results of classification using both neural network models and statistical methods are given, and the approaches are compared based on these results.

  9. A Systematic Comparison of Linear Regression–Based Statistical Methods to Assess Exposome-Health Associations

    PubMed Central

    Agier, Lydiane; Portengen, Lützen; Chadeau-Hyam, Marc; Basagaña, Xavier; Giorgis-Allemand, Lise; Siroux, Valérie; Robinson, Oliver; Vlaanderen, Jelle; González, Juan R.; Nieuwenhuijsen, Mark J.; Vineis, Paolo; Vrijheid, Martine; Slama, Rémy; Vermeulen, Roel

    2016-01-01

    Background: The exposome constitutes a promising framework to improve understanding of the effects of environmental exposures on health by explicitly considering multiple testing and avoiding selective reporting. However, exposome studies are challenged by the simultaneous consideration of many correlated exposures. Objectives: We compared the performances of linear regression–based statistical methods in assessing exposome-health associations. Methods: In a simulation study, we generated 237 exposure covariates with a realistic correlation structure and with a health outcome linearly related to 0 to 25 of these covariates. Statistical methods were compared primarily in terms of false discovery proportion (FDP) and sensitivity. Results: On average over all simulation settings, the elastic net and sparse partial least-squares regression showed a sensitivity of 76% and an FDP of 44%; Graphical Unit Evolutionary Stochastic Search (GUESS) and the deletion/substitution/addition (DSA) algorithm revealed a sensitivity of 81% and an FDP of 34%. The environment-wide association study (EWAS) underperformed these methods in terms of FDP (average FDP, 86%) despite a higher sensitivity. Performances decreased considerably when assuming an exposome exposure matrix with high levels of correlation between covariates. Conclusions: Correlation between exposures is a challenge for exposome research, and the statistical methods investigated in this study were limited in their ability to efficiently differentiate true predictors from correlated covariates in a realistic exposome context. Although GUESS and DSA provided a marginally better balance between sensitivity and FDP, they did not outperform the other multivariate methods across all scenarios and properties examined, and computational complexity and flexibility should also be considered when choosing between these methods. Citation: Agier L, Portengen L, Chadeau-Hyam M, Basagaña X, Giorgis-Allemand L, Siroux V, Robinson O

  10. Advanced Numerical Methods for Computing Statistical Quantities of Interest

    DTIC Science & Technology

    2014-07-10

    coefficients , forcing terms, and initial conditions was analyzed. The input data were assumed to depend on a finite number of random variables . Unlike...89, 2012, 1269-1280. We considered the Musiela equation of forward rates; this is a hyperbolic stochastic partial differential equation . A weak...ZHANG AND M. GUNZBURGER, Error analysis of stochastic collocation method for parabolic partial differential equations with random input data; SIAM Journal

  11. Exploring the use of statistical process control methods to assess course changes

    NASA Astrophysics Data System (ADS)

    Vollstedt, Ann-Marie

    This dissertation pertains to the field of Engineering Education. The Department of Mechanical Engineering at the University of Nevada, Reno (UNR) is hosting this dissertation under a special agreement. This study was motivated by the desire to find an improved, quantitative measure of student quality that is both convenient to use and easy to evaluate. While traditional statistical analysis tools such as ANOVA (analysis of variance) are useful, they are somewhat time consuming and are subject to error because they are based on grades, which are influenced by numerous variables, independent of student ability and effort (e.g. inflation and curving). Additionally, grades are currently the only measure of quality in most engineering courses even though most faculty agree that grades do not accurately reflect student quality. Based on a literature search, in this study, quality was defined as content knowledge, cognitive level, self efficacy, and critical thinking. Nineteen treatments were applied to a pair of freshmen classes in an effort in increase the qualities. The qualities were measured via quiz grades, essays, surveys, and online critical thinking tests. Results from the quality tests were adjusted and filtered prior to analysis. All test results were subjected to Chauvenet's criterion in order to detect and remove outlying data. In addition to removing outliers from data sets, it was felt that individual course grades needed adjustment to accommodate for the large portion of the grade that was defined by group work. A new method was developed to adjust grades within each group based on the residual of the individual grades within the group and the portion of the course grade defined by group work. It was found that the grade adjustment method agreed 78% of the time with the manual ii grade changes instructors made in 2009, and also increased the correlation between group grades and individual grades. Using these adjusted grades, Statistical Process Control

  12. Intelligent Condition Diagnosis Method Based on Adaptive Statistic Test Filter and Diagnostic Bayesian Network

    PubMed Central

    Li, Ke; Zhang, Qiuju; Wang, Kun; Chen, Peng; Wang, Huaqing

    2016-01-01

    A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF) and Diagnostic Bayesian Network (DBN) is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal) and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO). To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA) is proposed to evaluate the sensitiveness of symptom parameters (SPs) for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN) theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method. PMID:26761006

  13. Intelligent Condition Diagnosis Method Based on Adaptive Statistic Test Filter and Diagnostic Bayesian Network.

    PubMed

    Li, Ke; Zhang, Qiuju; Wang, Kun; Chen, Peng; Wang, Huaqing

    2016-01-08

    A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF) and Diagnostic Bayesian Network (DBN) is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal) and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO). To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA) is proposed to evaluate the sensitiveness of symptom parameters (SPs) for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN) theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method.

  14. Comparison of classical statistical methods and artificial neural network in traffic noise prediction

    SciTech Connect

    Nedic, Vladimir; Despotovic, Danijela; Cvetanovic, Slobodan; Despotovic, Milan; Babic, Sasa

    2014-11-15

    Traffic is the main source of noise in urban environments and significantly affects human mental and physical health and labor productivity. Therefore it is very important to model the noise produced by various vehicles. Techniques for traffic noise prediction are mainly based on regression analysis, which generally is not good enough to describe the trends of noise. In this paper the application of artificial neural networks (ANNs) for the prediction of traffic noise is presented. As input variables of the neural network, the proposed structure of the traffic flow and the average speed of the traffic flow are chosen. The output variable of the network is the equivalent noise level in the given time period L{sub eq}. Based on these parameters, the network is modeled, trained and tested through a comparative analysis of the calculated values and measured levels of traffic noise using the originally developed user friendly software package. It is shown that the artificial neural networks can be a useful tool for the prediction of noise with sufficient accuracy. In addition, the measured values were also used to calculate equivalent noise level by means of classical methods, and comparative analysis is given. The results clearly show that ANN approach is superior in traffic noise level prediction to any other statistical method. - Highlights: • We proposed an ANN model for prediction of traffic noise. • We developed originally designed user friendly software package. • The results are compared with classical statistical methods. • The results are much better predictive capabilities of ANN model.

  15. Segmentation of Brain MRI Using SOM-FCM-Based Method and 3D Statistical Descriptors

    PubMed Central

    Ortiz, Andrés; Palacio, Antonio A.; Górriz, Juan M.; Ramírez, Javier; Salas-González, Diego

    2013-01-01

    Current medical imaging systems provide excellent spatial resolution, high tissue contrast, and up to 65535 intensity levels. Thus, image processing techniques which aim to exploit the information contained in the images are necessary for using these images in computer-aided diagnosis (CAD) systems. Image segmentation may be defined as the process of parcelling the image to delimit different neuroanatomical tissues present on the brain. In this paper we propose a segmentation technique using 3D statistical features extracted from the volume image. In addition, the presented method is based on unsupervised vector quantization and fuzzy clustering techniques and does not use any a priori information. The resulting fuzzy segmentation method addresses the problem of partial volume effect (PVE) and has been assessed using real brain images from the Internet Brain Image Repository (IBSR). PMID:23762192

  16. Statistical inference methods for two crossing survival curves: a comparison of methods.

    PubMed

    Li, Huimin; Han, Dong; Hou, Yawen; Chen, Huilin; Chen, Zheng

    2015-01-01

    A common problem that is encountered in medical applications is the overall homogeneity of survival distributions when two survival curves cross each other. A survey demonstrated that under this condition, which was an obvious violation of the assumption of proportional hazard rates, the log-rank test was still used in 70% of studies. Several statistical methods have been proposed to solve this problem. However, in many applications, it is difficult to specify the types of survival differences and choose an appropriate method prior to analysis. Thus, we conducted an extensive series of Monte Carlo simulations to investigate the power and type I error rate of these procedures under various patterns of crossing survival curves with different censoring rates and distribution parameters. Our objective was to evaluate the strengths and weaknesses of tests in different situations and for various censoring rates and to recommend an appropriate test that will not fail for a wide range of applications. Simulation studies demonstrated that adaptive Neyman's smooth tests and the two-stage procedure offer higher power and greater stability than other methods when the survival distributions cross at early, middle or late times. Even for proportional hazards, both methods maintain acceptable power compared with the log-rank test. In terms of the type I error rate, Renyi and Cramér-von Mises tests are relatively conservative, whereas the statistics of the Lin-Xu test exhibit apparent inflation as the censoring rate increases. Other tests produce results close to the nominal 0.05 level. In conclusion, adaptive Neyman's smooth tests and the two-stage procedure are found to be the most stable and feasible approaches for a variety of situations and censoring rates. Therefore, they are applicable to a wider spectrum of alternatives compared with other tests.

  17. New Developments in the Embedded Statistical Coupling Method: Atomistic/Continuum Crack Propagation

    NASA Technical Reports Server (NTRS)

    Saether, E.; Yamakov, V.; Glaessgen, E.

    2008-01-01

    A concurrent multiscale modeling methodology that embeds a molecular dynamics (MD) region within a finite element (FEM) domain has been enhanced. The concurrent MD-FEM coupling methodology uses statistical averaging of the deformation of the atomistic MD domain to provide interface displacement boundary conditions to the surrounding continuum FEM region, which, in turn, generates interface reaction forces that are applied as piecewise constant traction boundary conditions to the MD domain. The enhancement is based on the addition of molecular dynamics-based cohesive zone model (CZM) elements near the MD-FEM interface. The CZM elements are a continuum interpretation of the traction-displacement relationships taken from MD simulations using Cohesive Zone Volume Elements (CZVE). The addition of CZM elements to the concurrent MD-FEM analysis provides a consistent set of atomistically-based cohesive properties within the finite element region near the growing crack. Another set of CZVEs are then used to extract revised CZM relationships from the enhanced embedded statistical coupling method (ESCM) simulation of an edge crack under uniaxial loading.

  18. When civil registration is inadequate: interim methods for generating vital statistics.

    PubMed

    AbouZahr, Carla; Rampatige, Rasika; Lopez, Alan; deSavigny, Don

    2012-04-01

    Comprehensive guidelines and tools to help countries rapidly improve their vital statistics systems, based on international best practice are now available. For many countries, however, attainment of timely, accurate statistics on births and deaths and causes of death will require years of strategic and prioritized investment, with technical assistance from WHO, the United Nations, and academia. In the meantime, however, countries will need accurate and unbiased data in order to measure progress with their health programs and broader development goals, such as the MDGs and the growing crisis of non-communicable diseases. This article has introduced some interim strategies that can yield adequate vital statistics and cause of death data as countries work to strengthen their civil registration systems. These methods mirror the skills, practices and advantages of complete and functioning civil registration and vital statistics systems, but for a sample of the population. They are based on the principle of rigorous and continuous data collection for a defined and manageable part of the population. Doing "smaller, representative" populations well rather than "larger populations poorly" will reduce the biases that would otherwise occur from missing data, incorrect application of data management procedures, poor data quality checking and lack of medical certification of causes of death. A critical component of this strategy is to routinely apply verbal autopsy methods to collect essential cause of death data. When properly applied, VA can yield population-based cause of death data of comparable quality to what is typically collected in hospitals in developing countries. Moreover, with the availability of automated methods to diagnose causes of death, it is now possible to obtain accurate cause of death data routinely, cheaply and quickly in resource-poor settings. The long-term goal of strengthening civil registration and vital statistics systems is to ensure that every

  19. Letter Exchanges on Statistics and Research Methods: Writing, Responding, and Learning.

    ERIC Educational Resources Information Center

    Dunn, Dana S.

    2000-01-01

    Discusses a letter exchange exercise for teaching statistics and research methods. Each student writes a letter to a peer in another course section on a topic in statistics or research methods, writes a response letter, and writes another letter clarifying their ideas. (CMK)

  20. Relationship between Students' Scores on Research Methods and Statistics, and Undergraduate Project Scores

    ERIC Educational Resources Information Center

    Ossai, Peter Agbadobi Uloku

    2016-01-01

    This study examined the relationship between students' scores on Research Methods and statistics, and undergraduate project at the final year. The purpose was to find out whether students matched knowledge of research with project-writing skill. The study adopted an expost facto correlational design. Scores on Research Methods and Statistics for…

  1. Best Practices in Teaching Statistics and Research Methods in the Behavioral Sciences [with CD-ROM

    ERIC Educational Resources Information Center

    Dunn, Dana S., Ed.; Smith, Randolph A., Ed.; Beins, Barney, Ed.

    2007-01-01

    This book provides a showcase for "best practices" in teaching statistics and research methods in two- and four-year colleges and universities. A helpful resource for teaching introductory, intermediate, and advanced statistics and/or methods, the book features coverage of: (1) ways to integrate these courses; (2) how to promote ethical conduct;…

  2. APA's Learning Objectives for Research Methods and Statistics in Practice: A Multimethod Analysis

    ERIC Educational Resources Information Center

    Tomcho, Thomas J.; Rice, Diana; Foels, Rob; Folmsbee, Leah; Vladescu, Jason; Lissman, Rachel; Matulewicz, Ryan; Bopp, Kara

    2009-01-01

    Research methods and statistics courses constitute a core undergraduate psychology requirement. We analyzed course syllabi and faculty self-reported coverage of both research methods and statistics course learning objectives to assess the concordance with APA's learning objectives (American Psychological Association, 2007). We obtained a sample of…

  3. Statistical methods for the forensic analysis of striated tool marks

    SciTech Connect

    Hoeksema, Amy Beth

    2013-01-01

    In forensics, fingerprints can be used to uniquely identify suspects in a crime. Similarly, a tool mark left at a crime scene can be used to identify the tool that was used. However, the current practice of identifying matching tool marks involves visual inspection of marks by forensic experts which can be a very subjective process. As a result, declared matches are often successfully challenged in court, so law enforcement agencies are particularly interested in encouraging research in more objective approaches. Our analysis is based on comparisons of profilometry data, essentially depth contours of a tool mark surface taken along a linear path. In current practice, for stronger support of a match or non-match, multiple marks are made in the lab under the same conditions by the suspect tool. We propose the use of a likelihood ratio test to analyze the difference between a sample of comparisons of lab tool marks to a field tool mark, against a sample of comparisons of two lab tool marks. Chumbley et al. (2010) point out that the angle of incidence between the tool and the marked surface can have a substantial impact on the tool mark and on the effectiveness of both manual and algorithmic matching procedures. To better address this problem, we describe how the analysis can be enhanced to model the effect of tool angle and allow for angle estimation for a tool mark left at a crime scene. With sufficient development, such methods may lead to more defensible forensic analyses.

  4. A REVIEW OF STATISTICAL METHODS FOR THE METEOROLOGICAL ADJUSTMENT OF TROPOSPHERIC OZONE

    EPA Science Inventory

    A variety of statistical methods for meteorological adjustment of ozone have been proposed in the literature over the last decade for purposes of forecasting, estimating ozone time trends, or investigating underlying mechanisms from an empirical perspective. The methods can be...

  5. A Tool Preference Choice Method for RNA Secondary Structure Prediction by SVM with Statistical Tests

    PubMed Central

    Hor, Chiou-Yi; Yang, Chang-Biau; Chang, Chia-Hung; Tseng, Chiou-Ting; Chen, Hung-Hsin

    2013-01-01

    The Prediction of RNA secondary structures has drawn much attention from both biologists and computer scientists. Many useful tools have been developed for this purpose. These tools have their individual strengths and weaknesses. As a result, based on support vector machines (SVM), we propose a tool choice method which integrates three prediction tools: pknotsRG, RNAStructure, and NUPACK. Our method first extracts features from the target RNA sequence, and adopts two information-theoretic feature selection methods for feature ranking. We propose a method to combine feature selection and classifier fusion in an incremental manner. Our test data set contains 720 RNA sequences, where 225 pseudoknotted RNA sequences are obtained from PseudoBase, and 495 nested RNA sequences are obtained from RNA SSTRAND. The method serves as a preprocessing way in analyzing RNA sequences before the RNA secondary structure prediction tools are employed. In addition, the performance of various configurations is subject to statistical tests to examine their significance. The best base-pair accuracy achieved is 75.5%, which is obtained by the proposed incremental method, and is significantly higher than 68.8%, which is associated with the best predictor, pknotsRG. PMID:23641141

  6. Methods for estimating selected low-flow statistics and development of annual flow-duration statistics for Ohio

    USGS Publications Warehouse

    Koltun, G.F.; Kula, Stephanie P.

    2013-01-01

    This report presents the results of a study to develop methods for estimating selected low-flow statistics and for determining annual flow-duration statistics for Ohio streams. Regression techniques were used to develop equations for estimating 10-year recurrence-interval (10-percent annual-nonexceedance probability) low-flow yields, in cubic feet per second per square mile, with averaging periods of 1, 7, 30, and 90-day(s), and for estimating the yield corresponding to the long-term 80-percent duration flow. These equations, which estimate low-flow yields as a function of a streamflow-variability index, are based on previously published low-flow statistics for 79 long-term continuous-record streamgages with at least 10 years of data collected through water year 1997. When applied to the calibration dataset, average absolute percent errors for the regression equations ranged from 15.8 to 42.0 percent. The regression results have been incorporated into the U.S. Geological Survey (USGS) StreamStats application for Ohio (http://water.usgs.gov/osw/streamstats/ohio.html) in the form of a yield grid to facilitate estimation of the corresponding streamflow statistics in cubic feet per second. Logistic-regression equations also were developed and incorporated into the USGS StreamStats application for Ohio for selected low-flow statistics to help identify occurrences of zero-valued statistics. Quantiles of daily and 7-day mean streamflows were determined for annual and annual-seasonal (September–November) periods for each complete climatic year of streamflow-gaging station record for 110 selected streamflow-gaging stations with 20 or more years of record. The quantiles determined for each climatic year were the 99-, 98-, 95-, 90-, 80-, 75-, 70-, 60-, 50-, 40-, 30-, 25-, 20-, 10-, 5-, 2-, and 1-percent exceedance streamflows. Selected exceedance percentiles of the annual-exceedance percentiles were subsequently computed and tabulated to help facilitate consideration of the

  7. Evaluation of the response of a questionnaire study by using the GIS and standard statistical methods.

    PubMed

    Slachtová, H; Machová, T; Tomásková, H; Michalík, J

    2003-06-01

    This study is a part of a larger project Nr. NJ 6139-3 funded by the Grant Agency of the Czech Ministry of Health. The aim of the paper was to analyse the response rate using standard statistical methods and the Geographical Information System (GIS); to indicate differences in the response by sex, age, education, and employment; to determine the breakpoint for the collection of questionnaires according to which we can estimate the total response rate; to indicate whether the study sample was representative enough to generalize the project results. The additional aim of the paper was to collect those background literary sources dealing with the response rate as a methodological paradigm. The statistical and GIS analysis were based on comparison of the total population data (Census 2001), the study sample and the sample of the completed questionnaires data in the 23 districts of the city of Ostrava. The information from the data collection was derived from the date of receipt for each questionnaire. The literature sources were obtained from the Internet--in total 228 papers from the period since 1986 to the present have been checked. The main results of this study are: the GIS analysis was confirmed in all stages by standard statistical methods--it can therefore be used as a valid tool for quick orientation in data and for the comparison of a study sample with the general population; we did not find significant differences in the course of the collection of the questionnaires between sex, age, education, and the employment of respondents; it can be seen that the breakpoint according to which we can estimate the total response rate, is the 10th day after the questionnaires are distributed by post (75% of the questionnaires collected); our sample is representative enough from the geographical point of view. More detailed information about the whole project and results already published or presented are available on the following web site: www.zuova.cz/projekty/ses/php.

  8. Performance of the Tariff Method: validation of a simple additive algorithm for analysis of verbal autopsies

    PubMed Central

    2011-01-01

    Background Verbal autopsies provide valuable information for studying mortality patterns in populations that lack reliable vital registration data. Methods for transforming verbal autopsy results into meaningful information for health workers and policymakers, however, are often costly or complicated to use. We present a simple additive algorithm, the Tariff Method (termed Tariff), which can be used for assigning individual cause of death and for determining cause-specific mortality fractions (CSMFs) from verbal autopsy data. Methods Tariff calculates a score, or "tariff," for each cause, for each sign/symptom, across a pool of validated verbal autopsy data. The tariffs are summed for a given response pattern in a verbal autopsy, and this sum (score) provides the basis for predicting the cause of death in a dataset. We implemented this algorithm and evaluated the method's predictive ability, both in terms of chance-corrected concordance at the individual cause assignment level and in terms of CSMF accuracy at the population level. The analysis was conducted separately for adult, child, and neonatal verbal autopsies across 500 pairs of train-test validation verbal autopsy data. Results Tariff is capable of outperforming physician-certified verbal autopsy in most cases. In terms of chance-corrected concordance, the method achieves 44.5% in adults, 39% in children, and 23.9% in neonates. CSMF accuracy was 0.745 in adults, 0.709 in children, and 0.679 in neonates. Conclusions Verbal autopsies can be an efficient means of obtaining cause of death data, and Tariff provides an intuitive, reliable method for generating individual cause assignment and CSMFs. The method is transparent and flexible and can be readily implemented by users without training in statistics or computer science. PMID:21816107

  9. Using the Bootstrap Method for a Statistical Significance Test of Differences between Summary Histograms

    NASA Technical Reports Server (NTRS)

    Xu, Kuan-Man

    2006-01-01

    A new method is proposed to compare statistical differences between summary histograms, which are the histograms summed over a large ensemble of individual histograms. It consists of choosing a distance statistic for measuring the difference between summary histograms and using a bootstrap procedure to calculate the statistical significance level. Bootstrapping is an approach to statistical inference that makes few assumptions about the underlying probability distribution that describes the data. Three distance statistics are compared in this study. They are the Euclidean distance, the Jeffries-Matusita distance and the Kuiper distance. The data used in testing the bootstrap method are satellite measurements of cloud systems called cloud objects. Each cloud object is defined as a contiguous region/patch composed of individual footprints or fields of view. A histogram of measured values over footprints is generated for each parameter of each cloud object and then summary histograms are accumulated over all individual histograms in a given cloud-object size category. The results of statistical hypothesis tests using all three distances as test statistics are generally similar, indicating the validity of the proposed method. The Euclidean distance is determined to be most suitable after comparing the statistical tests of several parameters with distinct probability distributions among three cloud-object size categories. Impacts on the statistical significance levels resulting from differences in the total lengths of satellite footprint data between two size categories are also discussed.

  10. Strategies for Enhancing the Learning of Ecological Research Methods and Statistics by Tertiary Environmental Science Students

    ERIC Educational Resources Information Center

    Panizzon, D. L.; Boulton, A. J.

    2004-01-01

    To undertake rigorous research in biology and ecology, students must be able to pose testable hypotheses, design decisive studies, and analyse results using suitable statistics. Yet, few biology students excel in topics involving statistics and most attempt to evade optional courses in research methods. Over the last few years, we have developed…

  11. A Statistical Method of Evaluating the Pronunciation Proficiency/Intelligibility of English Presentations by Japanese Speakers

    ERIC Educational Resources Information Center

    Kibishi, Hiroshi; Hirabayashi, Kuniaki; Nakagawa, Seiichi

    2015-01-01

    In this paper, we propose a statistical evaluation method of pronunciation proficiency and intelligibility for presentations made in English by native Japanese speakers. We statistically analyzed the actual utterances of speakers to find combinations of acoustic and linguistic features with high correlation between the scores estimated by the…

  12. 76 FR 5319 - Regulation of Fuel and Fuel Additives: Alternative Test Method for Olefins in Gasoline

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-01-31

    ... AGENCY 40 CFR Part 80 RIN 2060-AP17 Regulation of Fuel and Fuel Additives: Alternative Test Method for... correlated to the fuel parameter's respective EPA designated test method. These alternative test methods are... sections 114(a) and 301(a) of the CAA. Regulation of Fuel and Fuel Additives: Alternative Test Method...

  13. Reanalysis of morphine consumption from two randomized controlled trials of gabapentin using longitudinal statistical methods

    PubMed Central

    Zhang, Shiyuan; Paul, James; Nantha-Aree, Manyat; Buckley, Norman; Shahzad, Uswa; Cheng, Ji; DeBeer, Justin; Winemaker, Mitchell; Wismer, David; Punthakee, Dinshaw; Avram, Victoria; Thabane, Lehana

    2015-01-01

    Background Postoperative pain management in total joint replacement surgery remains ineffective in up to 50% of patients and has an overwhelming impact in terms of patient well-being and health care burden. We present here an empirical analysis of two randomized controlled trials assessing whether addition of gabapentin to a multimodal perioperative analgesia regimen can reduce morphine consumption or improve analgesia for patients following total joint arthroplasty (the MOBILE trials). Methods Morphine consumption, measured for four time periods in patients undergoing total hip or total knee arthroplasty, was analyzed using a linear mixed-effects model to provide a longitudinal estimate of the treatment effect. Repeated-measures analysis of variance and generalized estimating equations were used in a sensitivity analysis to compare the robustness of the methods. Results There was no statistically significant difference in morphine consumption between the treatment group and a control group (mean effect size estimate 1.0, 95% confidence interval −4.7, 6.7, P=0.73). The results remained robust across different longitudinal methods. Conclusion The results of the current reanalysis of morphine consumption align with those of the MOBILE trials. Gabapentin did not significantly reduce morphine consumption in patients undergoing major replacement surgeries. The results remain consistent across longitudinal methods. More work in the area of postoperative pain is required to provide adequate management for this patient population. PMID:25709496

  14. Hybrid statistics-simulations based method for atom-counting from ADF STEM images.

    PubMed

    De Wael, Annelies; De Backer, Annick; Jones, Lewys; Nellist, Peter D; Van Aert, Sandra

    2017-01-25

    A hybrid statistics-simulations based method for atom-counting from annular dark field scanning transmission electron microscopy (ADF STEM) images of monotype crystalline nanostructures is presented. Different atom-counting methods already exist for model-like systems. However, the increasing relevance of radiation damage in the study of nanostructures demands a method that allows atom-counting from low dose images with a low signal-to-noise ratio. Therefore, the hybrid method directly includes prior knowledge from image simulations into the existing statistics-based method for atom-counting, and accounts in this manner for possible discrepancies between actual and simulated experimental conditions. It is shown by means of simulations and experiments that this hybrid method outperforms the statistics-based method, especially for low electron doses and small nanoparticles. The analysis of a simulated low dose image of a small nanoparticle suggests that this method allows for far more reliable quantitative analysis of beam-sensitive materials.

  15. Characterization of squamous cell carcinomas of the head and neck using methods of spatial statistics.

    PubMed

    Mattfeldt, T; Fleischer, F

    2014-10-01

    In the present study, 53 cases of squamous cell carcinomas of the head and neck were characterized by a quantitative histological texture analysis based on principles of spatial statistics. A planar tessellation of the epithelial tumour component was generated by a skeletonization algorithm. The size distribution of the virtual cells of this planar tessellation, and the size distribution of the profiles of the tumour cell nuclei were estimated in terms of area and boundary length. The intensity, the reduced second moment function (K-function) and the pair correlation function of the point process of the centroids of the profiles of the tumour cell nuclei were also estimated. For both purposes, it is necessary to correct for edge effects, which we consider in this paper in some detail. Specifically, the point patterns of the tumour cell nuclei were considered as realizations of a point process, where the points exist only in the epithelial tumour component (the permitted phase) and not in the stroma (the forbidden phase). The methods allow to characterize each individual tumour by a series of summary statistics. The total set of cases was then partitioned into two groups: 19 cases without lymph node metastases (pN0), and 34 nodal positive cases (pN1 or pN2). Statistical analysis showed no significant differences between the intensities, the mean K-functions and the mean pair correlation functions of the tumour cell nucleus profiles of the two groups. However, there were some significant differences between the sizes of the virtual cells and of the nucleus profiles of the nodal negative cases as compared to the nodal positive cases. In a logistic regression analysis, one of the quantitative nuclear size variables (mean nuclear area) was found to be a significant predictor of lymph node metastasis, in addition to tumour stage. The study shows the potential of methods of spatial statistics for objective quantitative grading of squamous cell carcinomas of the head and

  16. Physics-based statistical model and simulation method of RF propagation in urban environments

    DOEpatents

    Pao, Hsueh-Yuan; Dvorak, Steven L.

    2010-09-14

    A physics-based statistical model and simulation/modeling method and system of electromagnetic wave propagation (wireless communication) in urban environments. In particular, the model is a computationally efficient close-formed parametric model of RF propagation in an urban environment which is extracted from a physics-based statistical wireless channel simulation method and system. The simulation divides the complex urban environment into a network of interconnected urban canyon waveguides which can be analyzed individually; calculates spectral coefficients of modal fields in the waveguides excited by the propagation using a database of statistical impedance boundary conditions which incorporates the complexity of building walls in the propagation model; determines statistical parameters of the calculated modal fields; and determines a parametric propagation model based on the statistical parameters of the calculated modal fields from which predictions of communications capability may be made.

  17. Recommended methods for statistical analysis of data containing less-than-detectable measurements

    SciTech Connect

    Atwood, C.L.; Blackwood, L.G.; Harris, G.A.; Loehr, C.A.

    1991-09-01

    This report is a manual for statistical workers dealing with environmental measurements, when some of the measurements are not given exactly but are only reported as less than detectable. For some statistical settings with such data, many methods have been proposed in the literature, while for others few or none have been proposed. This report gives a recommended method in each of the settings considered. The body of the report gives a brief description of each recommended method. Appendix A gives example programs using the statistical package SAS, for those methods that involve nonstandard methods. Appendix B presents the methods that were compared and the reasons for selecting each recommended method, and explains any fine points that might be of interest. 7 refs., 4 figs.

  18. Recommended methods for statistical analysis of data containing less-than-detectable measurements

    SciTech Connect

    Atwood, C.L.; Blackwood, L.G.; Harris, G.A.; Loehr, C.A.

    1990-09-01

    This report is a manual for statistical workers dealing with environmental measurements, when some of the measurements are not given exactly but are only reported as less than detectable. For some statistical settings with such data, many methods have been proposed in the literature, while for others few or none have been proposed. This report gives a recommended method in each of the settings considered. The body of the report gives a brief description of each recommended method. Appendix A gives example programs using the statistical package SAS, for those methods that involve nonstandard methods. Appendix B presents the methods that were compared and the reasons for selecting each recommended method, and explains any fine points that might be of interest. This is an interim version. Future revisions will complete the recommendations. 34 refs., 2 figs., 11 tabs.

  19. Robust phase-shift estimation method for statistical generalized phase-shifting digital holography.

    PubMed

    Yoshikawa, Nobukazu; Shiratori, Takaaki; Kajihara, Kazuki

    2014-06-16

    We propose a robust phase-shift estimation method for statistical generalized phase-shifting digital holography using a slightly off-axis optical configuration. The phase randomness condition in the Fresnel diffraction field of an object can be sufficiently established by the linear phase factor of the oblique incident reference wave. Signed phase-shift values can be estimated with a statistical approach regardless of the statistical properties of the Fresnel diffraction field of the object. We present computer simulations and optical experiments to verify the proposed method.

  20. Probability of identification: a statistical model for the validation of qualitative botanical identification methods.

    PubMed

    LaBudde, Robert A; Harnly, James M

    2012-01-01

    A qualitative botanical identification method (BIM) is an analytical procedure that returns a binary result (1 = Identified, 0 = Not Identified). A BIM may be used by a buyer, manufacturer, or regulator to determine whether a botanical material being tested is the same as the target (desired) material, or whether it contains excessive nontarget (undesirable) material. The report describes the development and validation of studies for a BIM based on the proportion of replicates identified, or probability of identification (POI), as the basic observed statistic. The statistical procedures proposed for data analysis follow closely those of the probability of detection, and harmonize the statistical concepts and parameters between quantitative and qualitative method validation. Use of POI statistics also harmonizes statistical concepts for botanical, microbiological, toxin, and other analyte identification methods that produce binary results. The POI statistical model provides a tool for graphical representation of response curves for qualitative methods, reporting of descriptive statistics, and application of performance requirements. Single collaborator and multicollaborative study examples are given.

  1. Statistical Evaluation and Improvement of Methods for Combining Random and Harmonic Loads

    NASA Technical Reports Server (NTRS)

    Brown, A. M.; McGhee, D. S.

    2003-01-01

    Structures in many environments experience both random and harmonic excitation. A variety of closed-form techniques has been used in the aerospace industry to combine the loads resulting from the two sources. The resulting combined loads are then used to design for both yield/ultimate strength and high- cycle fatigue capability. This Technical Publication examines the cumulative distribution percentiles obtained using each method by integrating the joint probability density function of the sine and random components. A new Microsoft Excel spreadsheet macro that links with the software program Mathematica to calculate the combined value corresponding to any desired percentile is then presented along with a curve tit to this value. Another Excel macro that calculates the combination using Monte Carlo simulation is shown. Unlike the traditional techniques. these methods quantify the calculated load value with a consistent percentile. Using either of the presented methods can be extremely valuable in probabilistic design, which requires a statistical characterization of the loading. Additionally, since the CDF at high probability levels is very flat, the design value is extremely sensitive to the predetermined percentile; therefore, applying the new techniques can substantially lower the design loading without losing any of the identified structural reliability.

  2. Additive Methods for Prediction of Thermochemical Properties. The Laidler Method Revisited. 1. Hydrocarbons

    NASA Astrophysics Data System (ADS)

    Leal, Joa˜O. Paulo

    2006-03-01

    A new parameterization of the Laidler method for estimation of atomization enthalpies and standard enthalpies of formation at 298.15 K for several families of hydrocarbons (alkanes, alkenes, alkynes, polyenes, poly-ynes, alkyl radicals, cycloalkanes, cycloalkenes, benzene derivatives, and polyaromatics) is presented. A total of 200 compounds (164 for liquid phase) are used for the calculation of the parameters. Comparison between the experimental values and those calculated using the group additive scheme led to an average difference of 1.28 kJṡmol-1 for the gas phase enthalpy of formation (excluding the polyaromatic compounds) and of 1.38 kJṡmol-1 for the liquid phase enthalpy of formation. The data base used appears to be essentially error free, but for some compounds (e.g., 2,2,4-trimethyl-pentane, with the highest deviation among all compounds except the polyaromatic ones) the experimental values might need a reevaluation. An Excel worksheet is provided to simplify the calculation of enthalpies of formation and atomization enthalpies based on the Laidler terms defined in this paper.

  3. A statistical method for detecting differentially expressed SNVs based on next-generation RNA-seq data.

    PubMed

    Fu, Rong; Wang, Pei; Ma, Weiping; Taguchi, Ayumu; Wong, Chee-Hong; Zhang, Qing; Gazdar, Adi; Hanash, Samir M; Zhou, Qinghua; Zhong, Hua; Feng, Ziding

    2017-03-01

    In this article, we propose a new statistical method-MutRSeq-for detecting differentially expressed single nucleotide variants (SNVs) based on RNA-seq data. Specifically, we focus on nonsynonymous mutations and employ a hierarchical likelihood approach to jointly model observed mutation events as well as read count measurements from RNA-seq experiments. We then introduce a likelihood ratio-based test statistic, which detects changes not only in overall expression levels, but also in allele-specific expression patterns. In addition, this method can jointly test multiple mutations in one gene/pathway. The simulation studies suggest that the proposed method achieves better power than a few competitors under a range of different settings. In the end, we apply this method to a breast cancer data set and identify genes with nonsynonymous mutations differentially expressed between the triple negative breast cancer tumors and other subtypes of breast cancer tumors.

  4. An Introduction to Survival Analysis: Statistical Methods for Analysis of Clinical Trial Data.

    ERIC Educational Resources Information Center

    Greenhouse, Joel B.; And Others

    1989-01-01

    Introduces statistical methods for evaluating differences in patterns of time to response between two subject groups to determine better therapy. Uses data from hypothetical clinical trial to illustrate two elementary methods for analyzing survival data. Discusses generalization of methods to incorporate covariates. Concludes with general…

  5. Comparison of three statistical downscaling methods for precipitation in the Hérault and Ebro catchments

    NASA Astrophysics Data System (ADS)

    Lassonde, Sylvain; Vrac, Mathieu; Ruelland, Denis; Dezetter, Alain

    2014-05-01

    The aim of the GICC project "REMedHE" (http://www.remedhe.org) is to evaluate and compare the evolution of water supply capacity under climatic and anthropogenic changes by 2050 on two Mediterranean catchments: the Hérault (South of France) and the Ebro (North East of Spain) catchments. Indeed, the Mediterranean region has been identified as a "hot spot" of climate change, especially for precipitation which is expected to globally decrease while water needs should continue to increase. To perform such a study, it is then necessary to simulate future water flows with hydrological models fed by high-resolution precipitation data representative of the future climate. To generate high-resolution climate simulations, three different statistical downscaling approaches have been applied. The first one consists in a deterministic transfer function based on a Generalized Additive Model (GAM). The second method involves a Stochastic Weather Generator (SWG), simulating local values from probability density functions conditioned by large-scale predictors. The third approach belongs to the "Model Output Statistics" (MOS) family, in bias correcting the large-scale distributions with respect to the local-scale ones, through the Cumulative Distribution Function transform CDFt approach. These statistical downscaling models were calibrated and cross-validated using the SAFRAN dataset (for Hérault catchment), a dataset compiled by HydroSciences Montpellier (for Ebro catchment) as local-scale reference and the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis outputs as predictors, over two time periods 1959-1984 and 1985-2010. Cross-validation analysis shows that the inter-annual variability of the yearly sum of precipitation from GAM is close to that from SAFRAN. However, daily variability and occurrence frequency are badly represented by GAM. On the opposite, SWG and one version of CDFt allow both the inter-annual and

  6. Performance comparison of three predictor selection methods for statistical downscaling of daily precipitation

    NASA Astrophysics Data System (ADS)

    Yang, Chunli; Wang, Ninglian; Wang, Shijin; Zhou, Liang

    2016-10-01

    Predictor selection is a critical factor affecting the statistical downscaling of daily precipitation. This study provides a general comparison between uncertainties in downscaled results from three commonly used predictor selection methods (correlation analysis, partial correlation analysis, and stepwise regression analysis). Uncertainty is analyzed by comparing statistical indices, including the mean, variance, and the distribution of monthly mean daily precipitation, wet spell length, and the number of wet days. The downscaled results are produced by the artificial neural network (ANN) statistical downscaling model and 50 years (1961-2010) of observed daily precipitation together with reanalysis predictors. Although results show little difference between downscaling methods, stepwise regression analysis is generally the best method for selecting predictors for the ANN statistical downscaling model of daily precipitation, followed by partial correlation analysis and then correlation analysis.

  7. Development and Evaluation of a Hybrid Dynamical-Statistical Downscaling Method

    NASA Astrophysics Data System (ADS)

    Walton, Daniel Burton

    Regional climate change studies usually rely on downscaling of global climate model (GCM) output in order to resolve important fine-scale features and processes that govern local climate. Previous efforts have used one of two techniques: (1) dynamical downscaling, in which a regional climate model is forced at the boundaries by GCM output, or (2) statistical downscaling, which employs historical empirical relationships to go from coarse to fine resolution. Studies using these methods have been criticized because they either dynamical downscaled only a few GCMs, or used statistical downscaling on an ensemble of GCMs, but missed important dynamical effects in the climate change signal. This study describes the development and evaluation of a hybrid dynamical-statstical downscaling method that utilizes aspects of both dynamical and statistical downscaling to address these concerns. The first step of the hybrid method is to use dynamical downscaling to understand the most important physical processes that contribute to the climate change signal in the region of interest. Then a statistical model is built based on the patterns and relationships identified from dynamical downscaling. This statistical model can be used to downscale an entire ensemble of GCMs quickly and efficiently. The hybrid method is first applied to a domain covering Los Angeles Region to generate projections of temperature change between the 2041-2060 and 1981-2000 periods for 32 CMIP5 GCMs. The hybrid method is also applied to a larger region covering all of California and the adjacent ocean. The hybrid method works well in both areas, primarily because a single feature, the land-sea contrast in the warming, controls the overwhelming majority of the spatial detail. Finally, the dynamically downscaled temperature change patterns are compared to those produced by two commonly-used statistical methods, BCSD and BCCA. Results show that dynamical downscaling recovers important spatial features that the

  8. Teaching Research Methods and Statistics in eLearning Environments: Pedagogy, Practical Examples, and Possible Futures

    PubMed Central

    Rock, Adam J.; Coventry, William L.; Morgan, Methuen I.; Loi, Natasha M.

    2016-01-01

    Generally, academic psychologists are mindful of the fact that, for many students, the study of research methods and statistics is anxiety provoking (Gal et al., 1997). Given the ubiquitous and distributed nature of eLearning systems (Nof et al., 2015), teachers of research methods and statistics need to cultivate an understanding of how to effectively use eLearning tools to inspire psychology students to learn. Consequently, the aim of the present paper is to discuss critically how using eLearning systems might engage psychology students in research methods and statistics. First, we critically appraise definitions of eLearning. Second, we examine numerous important pedagogical principles associated with effectively teaching research methods and statistics using eLearning systems. Subsequently, we provide practical examples of our own eLearning-based class activities designed to engage psychology students to learn statistical concepts such as Factor Analysis and Discriminant Function Analysis. Finally, we discuss general trends in eLearning and possible futures that are pertinent to teachers of research methods and statistics in psychology. PMID:27014147

  9. Teaching Research Methods and Statistics in eLearning Environments: Pedagogy, Practical Examples, and Possible Futures.

    PubMed

    Rock, Adam J; Coventry, William L; Morgan, Methuen I; Loi, Natasha M

    2016-01-01

    Generally, academic psychologists are mindful of the fact that, for many students, the study of research methods and statistics is anxiety provoking (Gal et al., 1997). Given the ubiquitous and distributed nature of eLearning systems (Nof et al., 2015), teachers of research methods and statistics need to cultivate an understanding of how to effectively use eLearning tools to inspire psychology students to learn. Consequently, the aim of the present paper is to discuss critically how using eLearning systems might engage psychology students in research methods and statistics. First, we critically appraise definitions of eLearning. Second, we examine numerous important pedagogical principles associated with effectively teaching research methods and statistics using eLearning systems. Subsequently, we provide practical examples of our own eLearning-based class activities designed to engage psychology students to learn statistical concepts such as Factor Analysis and Discriminant Function Analysis. Finally, we discuss general trends in eLearning and possible futures that are pertinent to teachers of research methods and statistics in psychology.

  10. Methods of learning in statistical education: Design and analysis of a randomized trial

    NASA Astrophysics Data System (ADS)

    Boyd, Felicity Turner

    Background. Recent psychological and technological advances suggest that active learning may enhance understanding and retention of statistical principles. A randomized trial was designed to evaluate the addition of innovative instructional methods within didactic biostatistics courses for public health professionals. Aims. The primary objectives were to evaluate and compare the addition of two active learning methods (cooperative and internet) on students' performance; assess their impact on performance after adjusting for differences in students' learning style; and examine the influence of learning style on trial participation. Methods. Consenting students enrolled in a graduate introductory biostatistics course were randomized to cooperative learning, internet learning, or control after completing a pretest survey. The cooperative learning group participated in eight small group active learning sessions on key statistical concepts, while the internet learning group accessed interactive mini-applications on the same concepts. Controls received no intervention. Students completed evaluations after each session and a post-test survey. Study outcome was performance quantified by examination scores. Intervention effects were analyzed by generalized linear models using intent-to-treat analysis and marginal structural models accounting for reported participation. Results. Of 376 enrolled students, 265 (70%) consented to randomization; 69, 100, and 96 students were randomized to the cooperative, internet, and control groups, respectively. Intent-to-treat analysis showed no differences between study groups; however, 51% of students in the intervention groups had dropped out after the second session. After accounting for reported participation, expected examination scores were 2.6 points higher (of 100 points) after completing one cooperative learning session (95% CI: 0.3, 4.9) and 2.4 points higher after one internet learning session (95% CI: 0.0, 4.7), versus

  11. Genomic similarity and kernel methods I: advancements by building on mathematical and statistical foundations.

    PubMed

    Schaid, Daniel J

    2010-01-01

    Measures of genomic similarity are the basis of many statistical analytic methods. We review the mathematical and statistical basis of similarity methods, particularly based on kernel methods. A kernel function converts information for a pair of subjects to a quantitative value representing either similarity (larger values meaning more similar) or distance (smaller values meaning more similar), with the requirement that it must create a positive semidefinite matrix when applied to all pairs of subjects. This review emphasizes the wide range of statistical methods and software that can be used when similarity is based on kernel methods, such as nonparametric regression, linear mixed models and generalized linear mixed models, hierarchical models, score statistics, and support vector machines. The mathematical rigor for these methods is summarized, as is the mathematical framework for making kernels. This review provides a framework to move from intuitive and heuristic approaches to define genomic similarities to more rigorous methods that can take advantage of powerful statistical modeling and existing software. A companion paper reviews novel approaches to creating kernels that might be useful for genomic analyses, providing insights with examples [1].

  12. Statistical modification analysis of helical planetary gears based on response surface method and Monte Carlo simulation

    NASA Astrophysics Data System (ADS)

    Zhang, Jun; Guo, Fan

    2015-11-01

    Tooth modification technique is widely used in gear industry to improve the meshing performance of gearings. However, few of the present studies on tooth modification considers the influence of inevitable random errors on gear modification effects. In order to investigate the uncertainties of tooth modification amount variations on system's dynamic behaviors of a helical planetary gears, an analytical dynamic model including tooth modification parameters is proposed to carry out a deterministic analysis on the dynamics of a helical planetary gear. The dynamic meshing forces as well as the dynamic transmission errors of the sun-planet 1 gear pair with and without tooth modifications are computed and compared to show the effectiveness of tooth modifications on gear dynamics enhancement. By using response surface method, a fitted regression model for the dynamic transmission error(DTE) fluctuations is established to quantify the relationship between modification amounts and DTE fluctuations. By shifting the inevitable random errors arousing from manufacturing and installing process to tooth modification amount variations, a statistical tooth modification model is developed and a methodology combining Monte Carlo simulation and response surface method is presented for uncertainty analysis of tooth modifications. The uncertainly analysis reveals that the system's dynamic behaviors do not obey the normal distribution rule even though the design variables are normally distributed. In addition, a deterministic modification amount will not definitely achieve an optimal result for both static and dynamic transmission error fluctuation reduction simultaneously.

  13. Evaluation of xenobiotic impact on urban receiving waters by means of statistical methods.

    PubMed

    Musolff, A; Leschik, S; Schafmeister, M-T; Reinstorf, F; Strauch, G; Krieg, R; Schirmer, M

    2010-01-01

    Xenobiotics in urban receiving waters are an emerging problem. A sound knowledge of xenobiotic input, distribution and fate in the aquatic environment is a prerequisite for risk assessments. Methods to assess the impact of xenobiotics on urban receiving waters should address the diverse characteristics of the target compounds and the spatiotemporal variability of concentrations. Here, we present results from a one-year-monitoring program concerning concentrations of pharmaceuticals, additives from personal care products and industrial chemicals in an urban drainage catchment in untreated and treated wastewater, surface water and groundwater. Univariate and multivariate statistical methods were applied to characterize the xenobiotic concentrations. Correlation and principal component analysis revealed a pronounced pattern of xenobiotics in the surface water samples. The concentrations of several xenobiotics were characterized by a negative proportionality to the water temperature. Therefore, seasonal attenuation is assumed to be a major process influencing the measured concentrations. Moreover, dilution of xenobiotics the surface water was found to significantly influence the concentrations. These two processes control more the xenobiotic occurrence in the surface water than the less pronounced concentration pattern in the wastewater sources. For the groundwater samples, we assume that foremost attenuation processes lead to the found differentiation of xenobiotics.

  14. Defining the ecological hydrology of Taiwan Rivers using multivariate statistical methods

    NASA Astrophysics Data System (ADS)

    Chang, Fi-John; Wu, Tzu-Ching; Tsai, Wen-Ping; Herricks, Edwin E.

    2009-09-01

    SummaryThe identification and verification of ecohydrologic flow indicators has found new support as the importance of ecological flow regimes is recognized in modern water resources management, particularly in river restoration and reservoir management. An ecohydrologic indicator system reflecting the unique characteristics of Taiwan's water resources and hydrology has been developed, the Taiwan ecohydrological indicator system (TEIS). A major challenge for the water resources community is using the TEIS to provide environmental flow rules that improve existing water resources management. This paper examines data from the extensive network of flow monitoring stations in Taiwan using TEIS statistics to define and refine environmental flow options in Taiwan. Multivariate statistical methods were used to examine TEIS statistics for 102 stations representing the geographic and land use diversity of Taiwan. The Pearson correlation coefficient showed high multicollinearity between the TEIS statistics. Watersheds were separated into upper and lower-watershed locations. An analysis of variance indicated significant differences between upstream, more natural, and downstream, more developed, locations in the same basin with hydrologic indicator redundancy in flow change and magnitude statistics. Issues of multicollinearity were examined using a Principal Component Analysis (PCA) with the first three components related to general flow and high/low flow statistics, frequency and time statistics, and quantity statistics. These principle components would explain about 85% of the total variation. A major conclusion is that managers must be aware of differences among basins, as well as differences within basins that will require careful selection of management procedures to achieve needed flow regimes.

  15. 40 CFR 80.8 - Sampling methods for gasoline, diesel fuel, fuel additives, and renewable fuels.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... fuel, fuel additives, and renewable fuels. 80.8 Section 80.8 Protection of Environment ENVIRONMENTAL... Provisions § 80.8 Sampling methods for gasoline, diesel fuel, fuel additives, and renewable fuels. The..., blendstocks, fuel additives and renewable fuels for purposes of determining compliance with the...

  16. Statistical studies of animal response data from USF toxicity screening test method

    NASA Technical Reports Server (NTRS)

    Hilado, C. J.; Machado, A. M.

    1978-01-01

    Statistical examination of animal response data obtained using Procedure B of the USF toxicity screening test method indicates that the data deviate only slightly from a normal or Gaussian distribution. This slight departure from normality is not expected to invalidate conclusions based on theoretical statistics. Comparison of times to staggering, convulsions, collapse, and death as endpoints shows that time to death appears to be the most reliable endpoint because it offers the lowest probability of missed observations and premature judgements.

  17. A new statistical method for design and analyses of component tolerance

    NASA Astrophysics Data System (ADS)

    Movahedi, Mohammad Mehdi; Khounsiavash, Mohsen; Otadi, Mahmood; Mosleh, Maryam

    2016-09-01

    Tolerancing conducted by design engineers to meet customers' needs is a prerequisite for producing high-quality products. Engineers use handbooks to conduct tolerancing. While use of statistical methods for tolerancing is not something new, engineers often use known distributions, including the normal distribution. Yet, if the statistical distribution of the given variable is unknown, a new statistical method will be employed to design tolerance. In this paper, we use generalized lambda distribution for design and analyses component tolerance. We use percentile method (PM) to estimate the distribution parameters. The findings indicated that, when the distribution of the component data is unknown, the proposed method can be used to expedite the design of component tolerance. Moreover, in the case of assembled sets, more extensive tolerance for each component with the same target performance can be utilized.

  18. A statistical method (cross-validation) for bone loss region detection after spaceflight

    PubMed Central

    Zhao, Qian; Li, Wenjun; Li, Caixia; Chu, Philip W.; Kornak, John; Lang, Thomas F.

    2010-01-01

    Astronauts experience bone loss after the long spaceflight missions. Identifying specific regions that undergo the greatest losses (e.g. the proximal femur) could reveal information about the processes of bone loss in disuse and disease. Methods for detecting such regions, however, remains an open problem. This paper focuses on statistical methods to detect such regions. We perform statistical parametric mapping to get t-maps of changes in images, and propose a new cross-validation method to select an optimum suprathreshold for forming clusters of pixels. Once these candidate clusters are formed, we use permutation testing of longitudinal labels to derive significant changes. PMID:20632144

  19. Verification of statistical method CORN for modeling of microfuel in the case of high grain concentration

    SciTech Connect

    Chukbar, B. K.

    2015-12-15

    Two methods of modeling a double-heterogeneity fuel are studied: the deterministic positioning and the statistical method CORN of the MCU software package. The effect of distribution of microfuel in a pebble bed on the calculation results is studied. The results of verification of the statistical method CORN for the cases of the microfuel concentration up to 170 cm{sup –3} in a pebble bed are presented. The admissibility of homogenization of the microfuel coating with the graphite matrix is studied. The dependence of the reactivity on the relative location of fuel and graphite spheres in a pebble bed is found.

  20. Differential Expression Analysis for RNA-Seq: An Overview of Statistical Methods and Computational Software

    PubMed Central

    Huang, Huei-Chung; Niu, Yi; Qin, Li-Xuan

    2015-01-01

    Deep sequencing has recently emerged as a powerful alternative to microarrays for the high-throughput profiling of gene expression. In order to account for the discrete nature of RNA sequencing data, new statistical methods and computational tools have been developed for the analysis of differential expression to identify genes that are relevant to a disease such as cancer. In this paper, it is thus timely to provide an overview of these analysis methods and tools. For readers with statistical background, we also review the parameter estimation algorithms and hypothesis testing strategies used in these methods. PMID:26688660

  1. Verification of statistical method CORN for modeling of microfuel in the case of high grain concentration

    NASA Astrophysics Data System (ADS)

    Chukbar, B. K.

    2015-12-01

    Two methods of modeling a double-heterogeneity fuel are studied: the deterministic positioning and the statistical method CORN of the MCU software package. The effect of distribution of microfuel in a pebble bed on the calculation results is studied. The results of verification of the statistical method CORN for the cases of the microfuel concentration up to 170 cm-3 in a pebble bed are presented. The admissibility of homogenization of the microfuel coating with the graphite matrix is studied. The dependence of the reactivity on the relative location of fuel and graphite spheres in a pebble bed is found.

  2. A NEW METHOD TO CORRECT FOR FIBER COLLISIONS IN GALAXY TWO-POINT STATISTICS

    SciTech Connect

    Guo Hong; Zehavi, Idit; Zheng Zheng

    2012-09-10

    In fiber-fed galaxy redshift surveys, the finite size of the fiber plugs prevents two fibers from being placed too close to one another, limiting the ability to study galaxy clustering on all scales. We present a new method for correcting such fiber collision effects in galaxy clustering statistics based on spectroscopic observations. The target galaxy sample is divided into two distinct populations according to the targeting algorithm of fiber placement, one free of fiber collisions and the other consisting of collided galaxies. The clustering statistics are a combination of the contributions from these two populations. Our method makes use of observations in tile overlap regions to measure the contributions from the collided population, and to therefore recover the full clustering statistics. The method is rooted in solid theoretical ground and is tested extensively on mock galaxy catalogs. We demonstrate that our method can well recover the projected and the full three-dimensional (3D) redshift-space two-point correlation functions (2PCFs) on scales both below and above the fiber collision scale, superior to the commonly used nearest neighbor and angular correction methods. We discuss potential systematic effects in our method. The statistical correction accuracy of our method is only limited by sample variance, which scales down with (the square root of) the volume probed. For a sample similar to the final SDSS-III BOSS galaxy sample, the statistical correction error is expected to be at the level of 1% on scales {approx}0.1-30 h {sup -1} Mpc for the 2PCFs. The systematic error only occurs on small scales, caused by imperfect correction of collision multiplets, and its magnitude is expected to be smaller than 5%. Our correction method, which can be generalized to other clustering statistics as well, enables more accurate measurements of full 3D galaxy clustering on all scales with galaxy redshift surveys.

  3. The Effectiveness of Propositional Manipulation as a Lecturing Method in the Statistics Knowledge Domain

    ERIC Educational Resources Information Center

    Leppink, Jimmie; Broers, Nick J.; Imbos, Tjaart; van der Vleuten, Cees P. M.; Berger, Martijn P. F.

    2013-01-01

    The current experiment examined the potential effects of the method of propositional manipulation (MPM) as a lecturing method on motivation to learn and conceptual understanding of statistics. MPM aims to help students develop conceptual understanding by guiding them into self-explanation at two different stages: First, at the stage of…

  4. Statistical Methods Used to Test for Agreement of Medical Instruments Measuring Continuous Variables in Method Comparison Studies: A Systematic Review

    PubMed Central

    Zaki, Rafdzah; Bulgiba, Awang; Ismail, Roshidi; Ismail, Noor Azina

    2012-01-01

    Background Accurate values are a must in medicine. An important parameter in determining the quality of a medical instrument is agreement with a gold standard. Various statistical methods have been used to test for agreement. Some of these methods have been shown to be inappropriate. This can result in misleading conclusions about the validity of an instrument. The Bland-Altman method is the most popular method judging by the many citations of the article proposing this method. However, the number of citations does not necessarily mean that this method has been applied in agreement research. No previous study has been conducted to look into this. This is the first systematic review to identify statistical methods used to test for agreement of medical instruments. The proportion of various statistical methods found in this review will also reflect the proportion of medical instruments that have been validated using those particular methods in current clinical practice. Methodology/Findings Five electronic databases were searched between 2007 and 2009 to look for agreement studies. A total of 3,260 titles were initially identified. Only 412 titles were potentially related, and finally 210 fitted the inclusion criteria. The Bland-Altman method is the most popular method with 178 (85%) studies having used this method, followed by the correlation coefficient (27%) and means comparison (18%). Some of the inappropriate methods highlighted by Altman and Bland since the 1980s are still in use. Conclusions This study finds that the Bland-Altman method is the most popular method used in agreement research. There are still inappropriate applications of statistical methods in some studies. It is important for a clinician or medical researcher to be aware of this issue because misleading conclusions from inappropriate analyses will jeopardize the quality of the evidence, which in turn will influence quality of care given to patients in the future. PMID:22662248

  5. Big data analysis using modern statistical and machine learning methods in medicine.

    PubMed

    Yoo, Changwon; Ramirez, Luis; Liuzzi, Juan

    2014-06-01

    In this article we introduce modern statistical machine learning and bioinformatics approaches that have been used in learning statistical relationships from big data in medicine and behavioral science that typically include clinical, genomic (and proteomic) and environmental variables. Every year, data collected from biomedical and behavioral science is getting larger and more complicated. Thus, in medicine, we also need to be aware of this trend and understand the statistical tools that are available to analyze these datasets. Many statistical analyses that are aimed to analyze such big datasets have been introduced recently. However, given many different types of clinical, genomic, and environmental data, it is rather uncommon to see statistical methods that combine knowledge resulting from those different data types. To this extent, we will introduce big data in terms of clinical data, single nucleotide polymorphism and gene expression studies and their interactions with environment. In this article, we will introduce the concept of well-known regression analyses such as linear and logistic regressions that has been widely used in clinical data analyses and modern statistical models such as Bayesian networks that has been introduced to analyze more complicated data. Also we will discuss how to represent the interaction among clinical, genomic, and environmental data in using modern statistical models. We conclude this article with a promising modern statistical method called Bayesian networks that is suitable in analyzing big data sets that consists with different type of large data from clinical, genomic, and environmental data. Such statistical model form big data will provide us with more comprehensive understanding of human physiology and disease.

  6. Big Data Analysis Using Modern Statistical and Machine Learning Methods in Medicine

    PubMed Central

    Ramirez, Luis; Liuzzi, Juan

    2014-01-01

    In this article we introduce modern statistical machine learning and bioinformatics approaches that have been used in learning statistical relationships from big data in medicine and behavioral science that typically include clinical, genomic (and proteomic) and environmental variables. Every year, data collected from biomedical and behavioral science is getting larger and more complicated. Thus, in medicine, we also need to be aware of this trend and understand the statistical tools that are available to analyze these datasets. Many statistical analyses that are aimed to analyze such big datasets have been introduced recently. However, given many different types of clinical, genomic, and environmental data, it is rather uncommon to see statistical methods that combine knowledge resulting from those different data types. To this extent, we will introduce big data in terms of clinical data, single nucleotide polymorphism and gene expression studies and their interactions with environment. In this article, we will introduce the concept of well-known regression analyses such as linear and logistic regressions that has been widely used in clinical data analyses and modern statistical models such as Bayesian networks that has been introduced to analyze more complicated data. Also we will discuss how to represent the interaction among clinical, genomic, and environmental data in using modern statistical models. We conclude this article with a promising modern statistical method called Bayesian networks that is suitable in analyzing big data sets that consists with different type of large data from clinical, genomic, and environmental data. Such statistical model form big data will provide us with more comprehensive understanding of human physiology and disease. PMID:24987556

  7. Statistical downscaling of daily precipitation over Llobregat river basin in Catalonia (Spain) using three downscaling methods.

    NASA Astrophysics Data System (ADS)

    Ballinas, R.; Versini, P.-A.; Sempere, D.; Escaler, I.

    2009-09-01

    environmental impact studies. Downscaling methods to assess the effect of large-scale circulations on local parameters have. Statistical downscaling methods are based on the view that regional climate can be conditioned by two factors: large-scale climatic state and regional/local features. Local climate information is derived by first developing a statistical model which relates large-scale variables or "predictors" for which GCMs are trustable to regional or local surface "predictands" for which models are less skilful. The main advantage of these methods is that they are computationally inexpensive, and can be applied to outputs from different GCM experiments. Three statistical downscaling methods are applied: Analogue method, Delta Change and Direct Forcing. These methods have been used to determine daily precipitation projections at rain gauge location to study the intensity, frequency and variability of storms in a context of climate change in the Llobregat River Basin in Catalonia, Spain. This work is part of the European project "Water Change" (included in the LIFE + Environment Policy and Governance program). It deals with Medium and long term water resources modelling as a tool for planning and global change adaptation. Two stakeholders involved in the project provided the historical time series: Catalan Water Agency (ACA) and the State Meteorological Agency (AEMET).

  8. Fine Mapping Causal Variants with an Approximate Bayesian Method Using Marginal Test Statistics.

    PubMed

    Chen, Wenan; Larrabee, Beth R; Ovsyannikova, Inna G; Kennedy, Richard B; Haralambieva, Iana H; Poland, Gregory A; Schaid, Daniel J

    2015-07-01

    Two recently developed fine-mapping methods, CAVIAR and PAINTOR, demonstrate better performance over other fine-mapping methods. They also have the advantage of using only the marginal test statistics and the correlation among SNPs. Both methods leverage the fact that the marginal test statistics asymptotically follow a multivariate normal distribution and are likelihood based. However, their relationship with Bayesian fine mapping, such as BIMBAM, is not clear. In this study, we first show that CAVIAR and BIMBAM are actually approximately equivalent to each other. This leads to a fine-mapping method using marginal test statistics in the Bayesian framework, which we call CAVIAR Bayes factor (CAVIARBF). Another advantage of the Bayesian framework is that it can answer both association and fine-mapping questions. We also used simulations to compare CAVIARBF with other methods under different numbers of causal variants. The results showed that both CAVIARBF and BIMBAM have better performance than PAINTOR and other methods. Compared to BIMBAM, CAVIARBF has the advantage of using only marginal test statistics and takes about one-quarter to one-fifth of the running time. We applied different methods on two independent cohorts of the same phenotype. Results showed that CAVIARBF, BIMBAM, and PAINTOR selected the same top 3 SNPs; however, CAVIARBF and BIMBAM had better consistency in selecting the top 10 ranked SNPs between the two cohorts. Software is available at https://bitbucket.org/Wenan/caviarbf.

  9. Statistical methods for detecting genomic alterations through array-based comparative genomic hybridization (CGH).

    PubMed

    Wang, Yuedong; Guo, Sun-Wei

    2004-01-01

    Array-based comparative genomic hybridization (ABCGH) is an emerging high-resolution and high-throughput molecular genetic technique that allows genome-wide screening for chromosome alterations associated with tumorigenesis. Like the cDNA microarrays, ABCGH uses two differentially labeled test and reference DNAs which are cohybridized to cloned genomic fragments immobilized on glass slides. The hybridized DNAs are then detected in two different fluorochromes, and the significant deviation from unity in the ratios of the digitized intensity values is indicative of copy-number differences between the test and reference genomes. Proper statistical analyses need to account for many sources of variation besides genuine differences between the two genomes. In particular, spatial correlations, the variable nature of the ratio variance and non-Normal distribution call for careful statistical modeling. We propose two new statistics, the standard t-statistic and its modification with variances smoothed along the genome, and two tests for each statistic, the standard t-test and a test based on the hybrid adaptive spline (HAS). Simulations indicate that the smoothed t-statistic always improves the performance over the standard t-statistic. The t-tests are more powerful in detecting isolated alterations while those based on HAS are more powerful in detecting a cluster of alterations. We apply the proposed methods to the identification of genomic alterations in endometrium in women with endometriosis.

  10. [Applications of mathematical statistics methods on compatibility researches of traditional Chinese medicines formulae].

    PubMed

    Mai, Lan-Yin; Li, Yi-Xuan; Chen, Yong; Xie, Zhen; Li, Jie; Zhong, Ming-Yu

    2014-05-01

    The compatibility of traditional Chinese medicines (TCMs) formulae containing enormous information, is a complex component system. Applications of mathematical statistics methods on the compatibility researches of traditional Chinese medicines formulae have great significance for promoting the modernization of traditional Chinese medicines and improving clinical efficacies and optimizations of formulae. As a tool for quantitative analysis, data inference and exploring inherent rules of substances, the mathematical statistics method can be used to reveal the working mechanisms of the compatibility of traditional Chinese medicines formulae in qualitatively and quantitatively. By reviewing studies based on the applications of mathematical statistics methods, this paper were summarized from perspective of dosages optimization, efficacies and changes of chemical components as well as the rules of incompatibility and contraindication of formulae, will provide the references for further studying and revealing the working mechanisms and the connotations of traditional Chinese medicines.

  11. Microvariability in AGNs: study of different statistical methods I. Observational Analysis

    NASA Astrophysics Data System (ADS)

    Zibecchi, L.; Andruchow, I.; Cellone, S. A.; Carpintero, D. D.; Romero, G. E.; Combi, J. A.

    2017-01-01

    We present the results of a study of different statistical methods currently used in the literature to analyse the (micro)variability of active galactic nuclei (AGNs) from ground-based optical observations. In particular, we focus on the comparison between the results obtained by applying the so-called C and F statistics, which are based on the ratio of standard deviations and variances, respectively. The motivation for this is that the implementation of these methods leads to different and contradictory results, making the variability classification of the light curves of a certain source dependent on the statistics implemented. For this purpose, we re-analyse the results on an AGN sample observed along several sessions with the 2.15-m `Jorge Sahade' telescope (CASLEO), San Juan, Argentina. For each AGN we constructed the nightly differential light curves. We thus obtained a total of 78 light curves for 39 AGNs, and we then applied the statistical tests mentioned above, in order to re-classify the variability state of these light curves and in an attempt to find the suitable statistical methodology to study photometric (micro)variations. We conclude that, although the C criterion is not proper a statistical test, it could still be a suitable parameter to detect variability and that its application allows to get more reliable variability results, in contrast with the F test.

  12. Forcing the statistical regionalization method WETTREG with large scale models of different resolution: A sensitivity study

    NASA Astrophysics Data System (ADS)

    Spekat, A.; Baumgart, S.; Kreienkamp, F.; Enke, W.

    2010-09-01

    The statistical regionalization method WETTREG is making use of the assumption that future climate changes are linked to changes in large scale atmospheric patterns. The frequency distributions of those patterns and their time-dependency are identified in the output fields of dynamical climate models and applied to force WETTREG. Thus, the magnitude and the time evolution of high-resolution climate signals for time horizons far into the 21st century can be computed. The model results employed to force WETTREG include the GCMS ECHAM5C, HadCM3C and CNRM. Additionally results from the dynamical regional models CLM, DMI, HadRM, RACMO and REMO, nested into one or more of these global models, are used in their pattern-generating capacity to force WETTREG. The study yield insight concerning the forcing-dependent sensitivity of WETTREG as well as the bandwidth of climate change signals. Recent results for the German State of Hesse will be presented in an intercomparison study.

  13. Impact of Statistical Learning Methods on the Predictive Power of Multivariate Normal Tissue Complication Probability Models

    SciTech Connect

    Xu Chengjian; Schaaf, Arjen van der; Schilstra, Cornelis; Langendijk, Johannes A.; Veld, Aart A. van't

    2012-03-15

    Purpose: To study the impact of different statistical learning methods on the prediction performance of multivariate normal tissue complication probability (NTCP) models. Methods and Materials: In this study, three learning methods, stepwise selection, least absolute shrinkage and selection operator (LASSO), and Bayesian model averaging (BMA), were used to build NTCP models of xerostomia following radiotherapy treatment for head and neck cancer. Performance of each learning method was evaluated by a repeated cross-validation scheme in order to obtain a fair comparison among methods. Results: It was found that the LASSO and BMA methods produced models with significantly better predictive power than that of the stepwise selection method. Furthermore, the LASSO method yields an easily interpretable model as the stepwise method does, in contrast to the less intuitive BMA method. Conclusions: The commonly used stepwise selection method, which is simple to execute, may be insufficient for NTCP modeling. The LASSO method is recommended.

  14. A model and variance reduction method for computing statistical outputs of stochastic elliptic partial differential equations

    SciTech Connect

    Vidal-Codina, F.; Nguyen, N.C.; Giles, M.B.; Peraire, J.

    2015-09-15

    We present a model and variance reduction method for the fast and reliable computation of statistical outputs of stochastic elliptic partial differential equations. Our method consists of three main ingredients: (1) the hybridizable discontinuous Galerkin (HDG) discretization of elliptic partial differential equations (PDEs), which allows us to obtain high-order accurate solutions of the governing PDE; (2) the reduced basis method for a new HDG discretization of the underlying PDE to enable real-time solution of the parameterized PDE in the presence of stochastic parameters; and (3) a multilevel variance reduction method that exploits the statistical correlation among the different reduced basis approximations and the high-fidelity HDG discretization to accelerate the convergence of the Monte Carlo simulations. The multilevel variance reduction method provides efficient computation of the statistical outputs by shifting most of the computational burden from the high-fidelity HDG approximation to the reduced basis approximations. Furthermore, we develop a posteriori error estimates for our approximations of the statistical outputs. Based on these error estimates, we propose an algorithm for optimally choosing both the dimensions of the reduced basis approximations and the sizes of Monte Carlo samples to achieve a given error tolerance. We provide numerical examples to demonstrate the performance of the proposed method.

  15. A model and variance reduction method for computing statistical outputs of stochastic elliptic partial differential equations

    NASA Astrophysics Data System (ADS)

    Vidal-Codina, F.; Nguyen, N. C.; Giles, M. B.; Peraire, J.

    2015-09-01

    We present a model and variance reduction method for the fast and reliable computation of statistical outputs of stochastic elliptic partial differential equations. Our method consists of three main ingredients: (1) the hybridizable discontinuous Galerkin (HDG) discretization of elliptic partial differential equations (PDEs), which allows us to obtain high-order accurate solutions of the governing PDE; (2) the reduced basis method for a new HDG discretization of the underlying PDE to enable real-time solution of the parameterized PDE in the presence of stochastic parameters; and (3) a multilevel variance reduction method that exploits the statistical correlation among the different reduced basis approximations and the high-fidelity HDG discretization to accelerate the convergence of the Monte Carlo simulations. The multilevel variance reduction method provides efficient computation of the statistical outputs by shifting most of the computational burden from the high-fidelity HDG approximation to the reduced basis approximations. Furthermore, we develop a posteriori error estimates for our approximations of the statistical outputs. Based on these error estimates, we propose an algorithm for optimally choosing both the dimensions of the reduced basis approximations and the sizes of Monte Carlo samples to achieve a given error tolerance. We provide numerical examples to demonstrate the performance of the proposed method.

  16. Methods for Determining the Statistical Significance of Enrichment or Depletion of Gene Ontology Classifications under Weighted Membership.

    PubMed

    Iacucci, Ernesto; Zingg, Hans H; Perkins, Theodore J

    2012-01-01

    High-throughput molecular biology studies, such as microarray assays of gene expression, two-hybrid experiments for detecting protein interactions, or ChIP-Seq experiments for transcription factor binding, often result in an "interesting" set of genes - say, genes that are co-expressed or bound by the same factor. One way of understanding the biological meaning of such a set is to consider what processes or functions, as defined in an ontology, are over-represented (enriched) or under-represented (depleted) among genes in the set. Usually, the significance of enrichment or depletion scores is based on simple statistical models and on the membership of genes in different classifications. We consider the more general problem of computing p-values for arbitrary integer additive statistics, or weighted membership functions. Such membership functions can be used to represent, for example, prior knowledge on the role of certain genes or classifications, differential importance of different classifications or genes to the experimenter, hierarchical relationships between classifications, or different degrees of interestingness or evidence for specific genes. We describe a generic dynamic programming algorithm that can compute exact p-values for arbitrary integer additive statistics. We also describe several optimizations for important special cases, which can provide orders-of-magnitude speed up in the computations. We apply our methods to datasets describing oxidative phosphorylation and parturition and compare p-values based on computations of several different statistics for measuring enrichment. We find major differences between p-values resulting from these statistics, and that some statistics recover "gold standard" annotations of the data better than others. Our work establishes a theoretical and algorithmic basis for far richer notions of enrichment or depletion of gene sets with respect to gene ontologies than has previously been available.

  17. Statistical study of generalized nonlinear phase step estimation methods in phase-shifting interferometry

    NASA Astrophysics Data System (ADS)

    Langoju, Rajesh; Patil, Abhijit; Rastogi, Pramod

    2007-11-01

    Signal processing methods based on maximum-likelihood theory, discrete chirp Fourier transform, and spectral estimation methods have enabled accurate measurement of phase in phase-shifting interferometry in the presence of nonlinear response of the piezoelectric transducer to the applied voltage. We present the statistical study of these generalized nonlinear phase step estimation methods to identify the best method by deriving the Cramér-Rao bound. We also address important aspects of these methods for implementation in practical applications and compare the performance of the best-identified method with other bench marking algorithms in the presence of harmonics and noise.

  18. Statistical study of generalized nonlinear phase step estimation methods in phase-shifting interferometry

    SciTech Connect

    Langoju, Rajesh; Patil, Abhijit; Rastogi, Pramod

    2007-11-20

    Signal processing methods based on maximum-likelihood theory, discrete chirp Fourier transform, and spectral estimation methods have enabled accurate measurement of phase in phase-shifting interferometry in the presence of nonlinear response of the piezoelectric transducer to the applied voltage. We present the statistical study of these generalized nonlinear phase step estimation methods to identify the best method by deriving the Cramer-Rao bound. We also address important aspects of these methods for implementation in practical applications and compare the performance of the best-identified method with other bench marking algorithms in the presence of harmonics and noise.

  19. Statistical Physics Methods Provide the Exact Solution to a Long-Standing Problem of Genetics.

    PubMed

    Samal, Areejit; Martin, Olivier C

    2015-06-12

    Analytic and computational methods developed within statistical physics have found applications in numerous disciplines. In this Letter, we use such methods to solve a long-standing problem in statistical genetics. The problem, posed by Haldane and Waddington [Genetics 16, 357 (1931)], concerns so-called recombinant inbred lines (RILs) produced by repeated inbreeding. Haldane and Waddington derived the probabilities of RILs when considering two and three genes but the case of four or more genes has remained elusive. Our solution uses two probabilistic frameworks relatively unknown outside of physics: Glauber's formula and self-consistent equations of the Schwinger-Dyson type. Surprisingly, this combination of statistical formalisms unveils the exact probabilities of RILs for any number of genes. Extensions of the framework may have applications in population genetics and beyond.

  20. Statistical Methods for Integrating Multiple Types of High-Throughput Data

    PubMed Central

    Xie, Yang; Ahn, Chul

    2011-01-01

    Large-scale sequencing, copy number, mRNA, and protein data have given great promise to the biomedical research, while posing great challenges to data management and data analysis. Integrating different types of high-throughput data from diverse sources can increase the statistical power of data analysis and provide deeper biological understanding. This chapter uses two biomedical research examples to illustrate why there is an urgent need to develop reliable and robust methods for integrating the heterogeneous data. We then introduce and review some recently developed statistical methods for integrative analysis for both statistical inference and classification purposes. Finally, we present some useful public access databases and program code to facilitate the integrative analysis in practice. PMID:20652519

  1. Statistical Physics Methods Provide the Exact Solution to a Long-Standing Problem of Genetics

    NASA Astrophysics Data System (ADS)

    Samal, Areejit; Martin, Olivier C.

    2015-06-01

    Analytic and computational methods developed within statistical physics have found applications in numerous disciplines. In this Letter, we use such methods to solve a long-standing problem in statistical genetics. The problem, posed by Haldane and Waddington [Genetics 16, 357 (1931)], concerns so-called recombinant inbred lines (RILs) produced by repeated inbreeding. Haldane and Waddington derived the probabilities of RILs when considering two and three genes but the case of four or more genes has remained elusive. Our solution uses two probabilistic frameworks relatively unknown outside of physics: Glauber's formula and self-consistent equations of the Schwinger-Dyson type. Surprisingly, this combination of statistical formalisms unveils the exact probabilities of RILs for any number of genes. Extensions of the framework may have applications in population genetics and beyond.

  2. Neural network approaches versus statistical methods in classification of multisource remote sensing data

    NASA Technical Reports Server (NTRS)

    Benediktsson, Jon A.; Swain, Philip H.; Ersoy, Okan K.

    1990-01-01

    Neural network learning procedures and statistical classificaiton methods are applied and compared empirically in classification of multisource remote sensing and geographic data. Statistical multisource classification by means of a method based on Bayesian classification theory is also investigated and modified. The modifications permit control of the influence of the data sources involved in the classification process. Reliability measures are introduced to rank the quality of the data sources. The data sources are then weighted according to these rankings in the statistical multisource classification. Four data sources are used in experiments: Landsat MSS data and three forms of topographic data (elevation, slope, and aspect). Experimental results show that two different approaches have unique advantages and disadvantages in this classification application.

  3. Rotational self-diffusion in suspensions of charged particles: simulations and revised Beenakker-Mazur and pairwise additivity methods

    NASA Astrophysics Data System (ADS)

    Makuch, Karol; Heinen, Marco; Abade, Gustavo Coelho; Nägele, Gerhard

    To the present day, the Beenakker-Mazur (BM) method is the most comprehensive statistical physics approach to the calculation of short-time transport properties of colloidal suspensions. A revised version of the BM method with an improved treatment of hydrodynamic interactions is presented and evaluated regarding the rotational short-time self-diffusion coefficient, $D^r$ , of suspensions of charged particles interacting by a hard-sphere plus screened Coulomb (Yukawa) pair potential. To assess the accuracy of the method, elaborate simulations of $D^r$ have been performed, covering a broad range of interaction parameters and particle concentrations. The revised BM method is compared in addition with results by a simplifying pairwise additivity (PA) method in which the hydrodynamic interactions are treated on a two-body level. The static pair correlation functions re- quired as input to both theoretical methods are calculated using the Rogers-Young integral equation scheme. While the revised BM method reproduces the general trends of the simulation results, it systematically and significantly underestimates the rotational diffusion coefficient. The PA method agrees well with the simulation data at lower volume fractions, but at higher concentrations $D^r$ is likewise underestimated. For a fixed value of the pair potential at mean particle distance comparable to the thermal energy, $D^r$ increases strongly with increasing Yukawa potential screening parameter.

  4. Phase determination method in statistical generalized phase-shifting digital holography.

    PubMed

    Yoshikawa, Nobukazu

    2013-03-20

    A simple estimation method of the relative phase shift for generalized phase-shifting digital holography based on a statistical method is proposed. This method consists of a selection procedure of an optimum cost function and a simple root-finding procedure. The value and sign of the relative phase shift are determined using the coefficient and the solution of the optimum cost function. The complex field of an object wave is obtained using the estimated relative phase shift. The proposed method lifts the typical restriction on the range of the phase shift due to the phase ambiguity problem. Computer simulations and optical experiments are performed to verify the proposed method.

  5. A dynamic scanning method based on signal-statistics for scanning electron microscopy.

    PubMed

    Timischl, F

    2014-01-01

    A novel dynamic scanning method for noise reduction in scanning electron microscopy and related applications is presented. The scanning method dynamically adjusts the scanning speed of the electron beam depending on the statistical behavior of the detector signal and gives SEM images with uniform and predefined standard deviation, independent of the signal value itself. In the case of partially saturated images, the proposed method decreases image acquisition time without sacrificing image quality. The effectiveness of the proposed method is shown and compared to the conventional scanning method and median filtering using numerical simulations.

  6. The change and development of statistical methods used in research articles in child development 1930-2010.

    PubMed

    Køppe, Simo; Dammeyer, Jesper

    2014-09-01

    The evolution of developmental psychology has been characterized by the use of different quantitative and qualitative methods and procedures. But how does the use of methods and procedures change over time? This study explores the change and development of statistical methods used in articles published in Child Development from 1930 to 2010. The methods used in every article in the first issue of every volume were categorized into four categories. Until 1980 relatively simple statistical methods were used. During the last 30 years there has been an explosive use of more advanced statistical methods employed. The absence of statistical methods or use of simple methods had been eliminated.

  7. Statistical methods to monitor the West Valley off-gas system

    SciTech Connect

    Eggett, D.L.

    1990-10-01

    The off-gas system for the ceramic melter operated at the West Valley Demonstration Project at West Valley, NY, is monitored during melter operation. A one-at-a-time method of monitoring the parameters of the off-gas system is not statistically sound. Therefore, multivariate statistical methods appropriate for the monitoring of many correlated parameters will be used. Monitoring a large number of parameters increases the probability of a false out-of-control signal. If the parameters being monitored are statistically independent, the control limits can be easily adjusted to obtain the desired probability of a false out-of-control signal. However, a high degree of correlation generally exists among the parameters being monitored in the off-gas system. This makes it very difficult to control the probability of false calls (saying the system is out-of-control when it is in-control or saying the system is in-control when it is actually out-of-control). The interpretation of the individual control charts is difficult in the presence of correlation among the variables. When a high degree of correlation exists, variable reduction techniques can be used to reduce the number of parameters. Principal components have been used as a variable reduction technique. The principal component (PC) scores have desirable statistical properties when the original variables are distributed as multivariate normals. Two statistics derived from the PC scores and used to form multivariate control charts are outlined and their distributional properties reviewed. 2 refs., 2 figs.

  8. Teaching Statistical Research Methods to Graduate Students: Lessons Learned from Three Different Degree Programs

    ERIC Educational Resources Information Center

    Ekmekci, Ozgur; Hancock, Adrienne B.; Swayze, Susan

    2012-01-01

    This paper examines the challenge of teaching statistical research methods in three master's degree programs at a private university based in Washington, DC. We, as three professors teaching at this university, discuss the way we employ innovative approaches to deal with this challenge. We ground our discussion within the theoretical framework of…

  9. Diagnosing Skills of Statistical Hypothesis Testing Using the Rule Space Method

    ERIC Educational Resources Information Center

    Im, Seongah; Yin, Yue

    2009-01-01

    This study illustrated the use of the Rule Space Method to diagnose students' proficiencies in, skills and knowledge of statistical hypothesis testing. Participants included 96 undergraduate and, graduate students, of whom 94 were classified into one or more of the knowledge states identified by, the rule space analysis. Analysis at the level of…

  10. Taguchi statistical design and analysis of cleaning methods for spacecraft materials

    NASA Technical Reports Server (NTRS)

    Lin, Y.; Chung, S.; Kazarians, G. A.; Blosiu, J. O.; Beaudet, R. A.; Quigley, M. S.; Kern, R. G.

    2003-01-01

    In this study, we have extensively tested various cleaning protocols. The variant parameters included the type and concentration of solvent, type of wipe, pretreatment conditions, and various rinsing systems. Taguchi statistical method was used to design and evaluate various cleaning conditions on ten common spacecraft materials.

  11. A REVIEW OF STATISTICAL METHODS FOR THE METEOROLOGICAL ADJUSTMENT OF TROPOSPHERIC OZONE. (R825173)

    EPA Science Inventory

    Abstract

    A variety of statistical methods for meteorological adjustment of ozone have been proposed in the literature over the last decade for purposes of forecasting, estimating ozone time trends, or investigating underlying mechanisms from an empirical perspective. T...

  12. A Mixed-Methods Assessment of Using an Online Commercial Tutoring System to Teach Introductory Statistics

    ERIC Educational Resources Information Center

    Xu, Yonghong Jade; Meyer, Katrina A.; Morgan, Dianne D.

    2009-01-01

    This study used a mixed-methods approach to evaluate a hybrid teaching format that incorporated an online tutoring system, ALEKS, to address students' learning needs in a graduate-level introductory statistics course. Student performance in the hybrid course with ALEKS was found to be no different from that in a course taught in a traditional…

  13. Cooperative Learning in Virtual Environments: The Jigsaw Method in Statistical Courses

    ERIC Educational Resources Information Center

    Vargas-Vargas, Manuel; Mondejar-Jimenez, Jose; Santamaria, Maria-Letica Meseguer; Alfaro-Navarro, Jose-Luis; Fernandez-Aviles, Gema

    2011-01-01

    This document sets out a novel teaching methodology as used in subjects with statistical content, traditionally regarded by students as "difficult". In a virtual learning environment, instructional techniques little used in mathematical courses were employed, such as the Jigsaw cooperative learning method, which had to be adapted to the…

  14. Demonstrating the Effectiveness of an Integrated and Intensive Research Methods and Statistics Course Sequence

    ERIC Educational Resources Information Center

    Pliske, Rebecca M.; Caldwell, Tracy L.; Calin-Jageman, Robert J.; Taylor-Ritzler, Tina

    2015-01-01

    We developed a two-semester series of intensive (six-contact hours per week) behavioral research methods courses with an integrated statistics curriculum. Our approach includes the use of team-based learning, authentic projects, and Excel and SPSS. We assessed the effectiveness of our approach by examining our students' content area scores on the…

  15. Interpreting Statistical Significance Test Results: A Proposed New "What If" Method.

    ERIC Educational Resources Information Center

    Kieffer, Kevin M.; Thompson, Bruce

    As the 1994 publication manual of the American Psychological Association emphasized, "p" values are affected by sample size. As a result, it can be helpful to interpret the results of statistical significant tests in a sample size context by conducting so-called "what if" analyses. However, these methods can be inaccurate…

  16. A statistical method for time-continuous assimilation of remote sounding temperatures

    NASA Technical Reports Server (NTRS)

    Ghil, M.

    1977-01-01

    A time-continuous statistical method is presented for the four-dimensional assimilation of remote sounding temperatures based on radiometric measurements from polar-orbiting satellites. This method is applied to DST-6 data from the NOAA-4 and Nimbus-6 satellites. Experiments are reported in which the state of the atmosphere throughout the test period was determined using a varying amount of satellite data and in which different methods were used for their assimilation. Data from the NOAA-4 satellite only, from Nimbus-6 only, and from both satellites together were used; the methods tested include different variations of the statistical method as well as more traditional methods. The conclusions are that: (1) satellite-derived temperature data can have a modest, but statistically significant positive impact on numerical weather prediction in the two-to-three day range; (2) this impact is highly sensitive to the quantity of data available; and (3) the assimilation method plays a major role in the magnitude of the impact for the same data.

  17. Real-time extraction of plasma equilibrium parameters in KSTAR tokamak using statistical methods

    NASA Astrophysics Data System (ADS)

    Na, Yong-Su; Jeon, Young-Mu; Hong, S. H.; Hwang, Y. S.

    2001-02-01

    To improve inherent shortcomings of statistical methods and apply them to the extraction of plasma equilibrium parameters in a fast timescale for real-time plasma control, new concepts of statistical methods such as principal component analysis-based neural network (NN), functional parametrization (FP)-based NN and double network are introduced by modifying NN and FP. These new methods are benchmarked and compared with the conventional techniques of NN and FP in a simple single-filament system. As a result of their applications to identification of plasma equilibrium parameters in the Korea Superconducting Tokamak Advanced Research tokamak, particularly, the double network concept among them has successfully achieved the improvement of drawbacks in the conventional methods. It is shown that more reliable results from the double network method can be obtained by combining several different statistical treatments as a primary network. Even in the case of nonoptimized methods united as a primary network, quite acceptable results can be achieved in the double network method.

  18. Inter-comparison of statistical downscaling methods for projection of extreme flow indices across Europe

    NASA Astrophysics Data System (ADS)

    Hundecha, Yeshewatesfa; Sunyer, Maria A.; Lawrence, Deborah; Madsen, Henrik; Willems, Patrick; Bürger, Gerd; Kriaučiūnienė, Jurate; Loukas, Athanasios; Martinkova, Marta; Osuch, Marzena; Vasiliades, Lampros; von Christierson, Birgitte; Vormoor, Klaus; Yücel, Ismail

    2016-10-01

    The effect of methods of statistical downscaling of daily precipitation on changes in extreme flow indices under a plausible future climate change scenario was investigated in 11 catchments selected from 9 countries in different parts of Europe. The catchments vary from 67 to 6171 km2 in size and cover different climate zones. 15 regional climate model outputs and 8 different statistical downscaling methods, which are broadly categorized as change factor and bias correction based methods, were used for the comparative analyses. Different hydrological models were implemented in different catchments to simulate daily runoff. A set of flood indices were derived from daily flows and their changes have been evaluated by comparing their values derived from simulations corresponding to the current and future climate. Most of the implemented downscaling methods project an increase in the extreme flow indices in most of the catchments. The catchments where the extremes are expected to increase have a rainfall-dominated flood regime. In these catchments, the downscaling methods also project an increase in the extreme precipitation in the seasons when the extreme flows occur. In catchments where the flooding is mainly caused by spring/summer snowmelt, the downscaling methods project a decrease in the extreme flows in three of the four catchments considered. A major portion of the variability in the projected changes in the extreme flow indices is attributable to the variability of the climate model ensemble, although the statistical downscaling methods contribute 35-60% of the total variance.

  19. An overview of recent developments in genomics and associated statistical methods.

    PubMed

    Bickel, Peter J; Brown, James B; Huang, Haiyan; Li, Qunhua

    2009-11-13

    The landscape of genomics has changed drastically in the last two decades. Increasingly inexpensive sequencing has shifted the primary focus from the acquisition of biological sequences to the study of biological function. Assays have been developed to study many intricacies of biological systems, and publicly available databases have given rise to integrative analyses that combine information from many sources to draw complex conclusions. Such research was the focus of the recent workshop at the Isaac Newton Institute, 'High dimensional statistics in biology'. Many computational methods from modern genomics and related disciplines were presented and discussed. Using, as much as possible, the material from these talks, we give an overview of modern genomics: from the essential assays that make data-generation possible, to the statistical methods that yield meaningful inference. We point to current analytical challenges, where novel methods, or novel applications of extant methods, are presently needed.

  20. Exploratory study on a statistical method to analyse time resolved data obtained during nanomaterial exposure measurements

    NASA Astrophysics Data System (ADS)

    Clerc, F.; Njiki-Menga, G.-H.; Witschger, O.

    2013-04-01

    Most of the measurement strategies that are suggested at the international level to assess workplace exposure to nanomaterials rely on devices measuring, in real time, airborne particles concentrations (according different metrics). Since none of the instruments to measure aerosols can distinguish a particle of interest to the background aerosol, the statistical analysis of time resolved data requires special attention. So far, very few approaches have been used for statistical analysis in the literature. This ranges from simple qualitative analysis of graphs to the implementation of more complex statistical models. To date, there is still no consensus on a particular approach and the current period is always looking for an appropriate and robust method. In this context, this exploratory study investigates a statistical method to analyse time resolved data based on a Bayesian probabilistic approach. To investigate and illustrate the use of the this statistical method, particle number concentration data from a workplace study that investigated the potential for exposure via inhalation from cleanout operations by sandpapering of a reactor producing nanocomposite thin films have been used. In this workplace study, the background issue has been addressed through the near-field and far-field approaches and several size integrated and time resolved devices have been used. The analysis of the results presented here focuses only on data obtained with two handheld condensation particle counters. While one was measuring at the source of the released particles, the other one was measuring in parallel far-field. The Bayesian probabilistic approach allows a probabilistic modelling of data series, and the observed task is modelled in the form of probability distributions. The probability distributions issuing from time resolved data obtained at the source can be compared with the probability distributions issuing from the time resolved data obtained far-field, leading in a

  1. A Statistical Method of Identifying Interactions in Neuron–Glia Systems Based on Functional Multicell Ca2+ Imaging

    PubMed Central

    Nakae, Ken; Ikegaya, Yuji; Ishikawa, Tomoe; Oba, Shigeyuki; Urakubo, Hidetoshi; Koyama, Masanori; Ishii, Shin

    2014-01-01

    Crosstalk between neurons and glia may constitute a significant part of information processing in the brain. We present a novel method of statistically identifying interactions in a neuron–glia network. We attempted to identify neuron–glia interactions from neuronal and glial activities via maximum-a-posteriori (MAP)-based parameter estimation by developing a generalized linear model (GLM) of a neuron–glia network. The interactions in our interest included functional connectivity and response functions. We evaluated the cross-validated likelihood of GLMs that resulted from the addition or removal of connections to confirm the existence of specific neuron-to-glia or glia-to-neuron connections. We only accepted addition or removal when the modification improved the cross-validated likelihood. We applied the method to a high-throughput, multicellular in vitro Ca2+ imaging dataset obtained from the CA3 region of a rat hippocampus, and then evaluated the reliability of connectivity estimates using a statistical test based on a surrogate method. Our findings based on the estimated connectivity were in good agreement with currently available physiological knowledge, suggesting our method can elucidate undiscovered functions of neuron–glia systems. PMID:25393874

  2. Fold change rank ordering statistics: a new method for detecting differentially expressed genes

    PubMed Central

    2014-01-01

    Background Different methods have been proposed for analyzing differentially expressed (DE) genes in microarray data. Methods based on statistical tests that incorporate expression level variability are used more commonly than those based on fold change (FC). However, FC based results are more reproducible and biologically relevant. Results We propose a new method based on fold change rank ordering statistics (FCROS). We exploit the variation in calculated FC levels using combinatorial pairs of biological conditions in the datasets. A statistic is associated with the ranks of the FC values for each gene, and the resulting probability is used to identify the DE genes within an error level. The FCROS method is deterministic, requires a low computational runtime and also solves the problem of multiple tests which usually arises with microarray datasets. Conclusion We compared the performance of FCROS with those of other methods using synthetic and real microarray datasets. We found that FCROS is well suited for DE gene identification from noisy datasets when compared with existing FC based methods. PMID:24423217

  3. Detection method of nonlinearity errors by statistical signal analysis in heterodyne Michelson interferometer.

    PubMed

    Hu, Juju; Hu, Haijiang; Ji, Yinghua

    2010-03-15

    Periodic nonlinearity that ranges from tens of nanometers to a few nanometers in heterodyne interferometer limits its use in high accuracy measurement. A novel method is studied to detect the nonlinearity errors based on the electrical subdivision and the analysis method of statistical signal in heterodyne Michelson interferometer. Under the movement of micropositioning platform with the uniform velocity, the method can detect the nonlinearity errors by using the regression analysis and Jackknife estimation. Based on the analysis of the simulations, the method can estimate the influence of nonlinearity errors and other noises for the dimensions measurement in heterodyne Michelson interferometer.

  4. [A method for the medical image registration based on the statistics samples averaging distribution theory].

    PubMed

    Xu, Peng; Yao, Dezhong; Luo, Fen

    2005-08-01

    The registration method based on mutual information is currently a popular technique for the medical image registration, but the computation for the mutual information is complex and the registration speed is slow. In engineering process, a subsampling technique is taken to accelerate the registration speed at the cost of registration accuracy. In this paper a new method based on statistics sample theory is developed, which has both a higher speed and a higher accuracy as compared with the normal subsampling method, and the simulation results confirm the validity of the new method.

  5. [Statistical tests in medical research: traditional methods vs. multivariate NPC permutation tests].

    PubMed

    Arboretti, Rosa; Bordignon, Paolo; Corain, Livio; Palermo, Giuseppe; Pesarin, Fortunato; Salmaso, Luigi

    2015-01-01

    Statistical tests in medical research: traditional methods vs. multivariate npc permutation tests.Within medical research, a useful statistical tool is based on hypotheses testing in terms of the so-called null, that is the treatment has no effect, and alternative hypotheses, that is the treatment has some effects. By controlling the risks of wrong decisions, empirical data are used in order to possibly reject the null hypotheses in favour of the alternative, so that demonstrating the efficacy of a treatment of interest. The multivariate permutation tests, based on the nonparametric combination - NPC method, provide an innovative, robust and effective hypotheses testing solution to many real problems that are commonly encountered in medical research when multiple end-points are observed. This paper discusses the various approaches to hypothesis testing and the main advantages of NPC tests, which consist in the fact that they require much less stringent assumptions than traditional statistical tests. Moreover, the related results may be extended to the reference population even in case of selection-bias, that is non-random sampling. In this work, we review and discuss some basic testing procedures along with the theoretical and practical relevance of NPC tests showing their effectiveness in medical research. Within the non-parametric methods, NPC tests represent the current "frontier" of statistical research, but already widely available in the practice of analysis of clinical data.

  6. NDE of additively manufactured components with embedded defects (reference standards) using conventional and advanced ultrasonic methods

    NASA Astrophysics Data System (ADS)

    Koester, L.; Roberts, R. A.; Barnard, D. J.; Chakrapani, S.; Singh, S.; Hogan, R.; Bond, L. J.

    2017-02-01

    Additive manufacturing provides a unique opportunity to embed defects of known size and shape to produce reference samples for inspection and quality control purposes. This paper reports defect detectability studies with cylindrical additively manufactured cobalt-chromium alloy specimens which contain defects of known sizes and distributions. The specimens were characterized using immersion, synthetic aperture focusing (SAFT), phased array, and nonlinear ultrasonic techniques. Results include detectability, signal to noise ratios, and comparison of results between the methods and what is believed to be the first determination of a non-linearity (beta) parameter for an additively manufactured material. The results indicate that additive manufacturing provides a valuable method to produce reference samples, though additional work is required to validate the shape and morphology of the defects specified.

  7. Identification of robust statistical downscaling methods based on a comprehensive suite of performance metrics for South Korea

    NASA Astrophysics Data System (ADS)

    Eum, H. I.; Cannon, A. J.

    2015-12-01

    Climate models are a key provider to investigate impacts of projected future climate conditions on regional hydrologic systems. However, there is a considerable mismatch of spatial resolution between GCMs and regional applications, in particular a region characterized by complex terrain such as Korean peninsula. Therefore, a downscaling procedure is an essential to assess regional impacts of climate change. Numerous statistical downscaling methods have been used mainly due to the computational efficiency and simplicity. In this study, four statistical downscaling methods [Bias-Correction/Spatial Disaggregation (BCSD), Bias-Correction/Constructed Analogue (BCCA), Multivariate Adaptive Constructed Analogs (MACA), and Bias-Correction/Climate Imprint (BCCI)] are applied to downscale the latest Climate Forecast System Reanalysis data to stations for precipitation, maximum temperature, and minimum temperature over South Korea. By split sampling scheme, all methods are calibrated with observational station data for 19 years from 1973 to 1991 are and tested for the recent 19 years from 1992 to 2010. To assess skill of the downscaling methods, we construct a comprehensive suite of performance metrics that measure an ability of reproducing temporal correlation, distribution, spatial correlation, and extreme events. In addition, we employ Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to identify robust statistical downscaling methods based on the performance metrics for each season. The results show that downscaling skill is considerably affected by the skill of CFSR and all methods lead to large improvements in representing all performance metrics. According to seasonal performance metrics evaluated, when TOPSIS is applied, MACA is identified as the most reliable and robust method for all variables and seasons. Note that such result is derived from CFSR output which is recognized as near perfect climate data in climate studies. Therefore, the

  8. 76 FR 65382 - Regulation of Fuel and Fuel Additives: Alternative Test Method for Olefins in Gasoline

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-10-21

    ... AGENCY 40 CFR Part 80 RIN 2060-AP17 Regulation of Fuel and Fuel Additives: Alternative Test Method for... alternative test method for olefin content in gasoline. This final rule will provide flexibility to the... environmental benefits achieved from our fuels programs. ] DATES: This rule is effective November 21,...

  9. A new mathematical evaluation of smoking problem based of algebraic statistical method.

    PubMed

    Mohammed, Maysaa J; Rakhimov, Isamiddin S; Shitan, Mahendran; Ibrahim, Rabha W; Mohammed, Nadia F

    2016-01-01

    Smoking problem is considered as one of the hot topics for many years. In spite of overpowering facts about the dangers, smoking is still a bad habit widely spread and socially accepted. Many people start smoking during their gymnasium period. The discovery of the dangers of smoking gave a warning sign of danger for individuals. There are different statistical methods used to analyze the dangers of smoking. In this study, we apply an algebraic statistical method to analyze and classify real data using Markov basis for the independent model on the contingency table. Results show that the Markov basis based classification is able to distinguish different date elements. Moreover, we check our proposed method via information theory by utilizing the Shannon formula to illustrate which one of these alternative tables is the best in term of independent.

  10. Feature-based and statistical methods for analyzing the Deepwater Horizon oil spill with AVIRIS imagery

    USGS Publications Warehouse

    Rand, R.S.; Clark, R.N.; Livo, K.E.

    2011-01-01

    The Deepwater Horizon oil spill covered a very large geographical area in the Gulf of Mexico creating potentially serious environmental impacts on both marine life and the coastal shorelines. Knowing the oil's areal extent and thickness as well as denoting different categories of the oil's physical state is important for assessing these impacts. High spectral resolution data in hyperspectral imagery (HSI) sensors such as Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) provide a valuable source of information that can be used for analysis by semi-automatic methods for tracking an oil spill's areal extent, oil thickness, and oil categories. However, the spectral behavior of oil in water is inherently a highly non-linear and variable phenomenon that changes depending on oil thickness and oil/water ratios. For certain oil thicknesses there are well-defined absorption features, whereas for very thin films sometimes there are almost no observable features. Feature-based imaging spectroscopy methods are particularly effective at classifying materials that exhibit specific well-defined spectral absorption features. Statistical methods are effective at classifying materials with spectra that exhibit a considerable amount of variability and that do not necessarily exhibit well-defined spectral absorption features. This study investigates feature-based and statistical methods for analyzing oil spills using hyperspectral imagery. The appropriate use of each approach is investigated and a combined feature-based and statistical method is proposed. ?? 2011 SPIE.

  11. Novel method and experimental validation of statistical calibration via Gaussianization in hot-wire anemometry

    NASA Astrophysics Data System (ADS)

    Gluzman, Igal; Cohen, Jacob; Oshman, Yaakov

    2016-11-01

    We introduce a statistical method based on Gaussianization to estimate the nonlinear calibration curve of a hot-wire probe, that relates the input flow velocity to the output (measured) voltage. The method uses as input a measured sequence of voltage samples, corresponding to different unknown flow velocities in the desired operational range, and only two measured voltages along with their known (calibrated) flow velocities. The novel method is validated against standard calibration methods using data acquired by hot-wire probes using wind-tunnel experiments. We demonstrate our new calibration technique by placing the hot-wire probe at certain region downstream of a cube-shaped body in a free stream of air flow. For testing our calibration method we rely on flow statistics that exist, among others, in a certain region of a turbulent wake formed downstream of the cube-shaped body. The specific properties are: first, the velocity signal in the wake should be as close to Gaussian as possible. Second, the signal should cover the desired velocity range that should be calibrated. The appropriate region to place our probe is determined via computation of the first four statistical moments of the measured signals in different regions of the wake.

  12. Automated counting of morphologically normal red blood cells by using digital holographic microscopy and statistical methods

    NASA Astrophysics Data System (ADS)

    Moon, Inkyu; Yi, Faliu

    2015-09-01

    In this paper we overview a method to automatically count morphologically normal red blood cells (RBCs) by using off-axis digital holographic microscopy and statistical methods. Three kinds of RBC are used as training and testing data. All of the RBC phase images are obtained with digital holographic microscopy (DHM) that is robust to transparent or semitransparent biological cells. For the determination of morphologically normal RBCs, the RBC's phase images are first segmented with marker-controlled watershed transform algorithm. Multiple features are extracted from the segmented cells. Moreover, the statistical method of Hotelling's T-square test is conducted to show that the 3D features from 3D imaging method can improve the discrimination performance for counting of normal shapes of RBCs. Finally, the classifier is designed by using statistical Bayesian algorithm and the misclassification rates are measured with leave-one-out technique. Experimental results show the feasibility of the classification method for calculating the percentage of each typical normal RBC shape.

  13. A Statistical Approach for the Concurrent Coupling of Molecular Dynamics and Finite Element Methods

    NASA Technical Reports Server (NTRS)

    Saether, E.; Yamakov, V.; Glaessgen, E.

    2007-01-01

    Molecular dynamics (MD) methods are opening new opportunities for simulating the fundamental processes of material behavior at the atomistic level. However, increasing the size of the MD domain quickly presents intractable computational demands. A robust approach to surmount this computational limitation has been to unite continuum modeling procedures such as the finite element method (FEM) with MD analyses thereby reducing the region of atomic scale refinement. The challenging problem is to seamlessly connect the two inherently different simulation techniques at their interface. In the present work, a new approach to MD-FEM coupling is developed based on a restatement of the typical boundary value problem used to define a coupled domain. The method uses statistical averaging of the atomistic MD domain to provide displacement interface boundary conditions to the surrounding continuum FEM region, which, in return, generates interface reaction forces applied as piecewise constant traction boundary conditions to the MD domain. The two systems are computationally disconnected and communicate only through a continuous update of their boundary conditions. With the use of statistical averages of the atomistic quantities to couple the two computational schemes, the developed approach is referred to as an embedded statistical coupling method (ESCM) as opposed to a direct coupling method where interface atoms and FEM nodes are individually related. The methodology is inherently applicable to three-dimensional domains, avoids discretization of the continuum model down to atomic scales, and permits arbitrary temperatures to be applied.

  14. Water quality assessment and source identification of Daliao River Basin using multivariate statistical methods.

    PubMed

    Zhang, Yuan; Guo, Fen; Meng, Wei; Wang, Xi-Qin

    2009-05-01

    Multivariate statistical methods, such as cluster analysis (CA), discriminant analysis (DA) and principal component analysis (PCA), were used to analyze the water quality dataset including 13 parameters at 18 sites of the Daliao River Basin from 2003-2005 (8424 observations) to obtain temporal and spatial variations and to identify potential pollution sources. Using Hierarchical CA it is classified 12 months into three periods (first, second and third period) and the 18 sampling sites into three groups (groups A, B and C). Six significant parameters (temperature, pH, DO, BOD(5), volatile phenol and E. coli) were identified by DA for distinguishing temporal or spatial groups, with close to 84.5% correct assignment for temporal variation analysis, while five parameters (DO, NH(4)(+)-N, Hg, volatile phenol and E. coli) were discovered to correctly assign about 73.61% for the spatial variation analysis. PCA is useful in identifying five latent pollution sources for group B and C (oxygen consuming organic pollution, toxic organic pollution, heavy metal pollution, fecal pollution and oil pollution). During the first period, sites received more oxygen consuming organic pollution, toxic organic pollution and heavy metal pollution than those in the other two periods. For group B, sites were mainly affected by oxygen consuming organic pollution and toxic organic pollution during the first period. The level of pollution in the second period was between the other two periods. For group C, sites were mainly affected by oil pollution during the first period and oxygen consuming organic pollution during the third period. Furthermore, source identification of each period for group B and group C provided useful information about seasonal pollution. Sites were mainly affected by fecal pollution in the third period for group B, indicating the character of non-point source pollution. In addition, all the sites were also affected by physical-chemistry pollution. In the second and third

  15. [Confidence interval or p-value--similarities and differences between two important methods of statistical inference of quantitative studies].

    PubMed

    Harari, Gil

    2014-01-01

    Statistic significance, also known as p-value, and CI (Confidence Interval) are common statistics measures and are essential for the statistical analysis of studies in medicine and life sciences. These measures provide complementary information about the statistical probability and conclusions regarding the clinical significance of study findings. This article is intended to describe the methodologies, compare between the methods, assert their suitability for the different needs of study results analysis and to explain situations in which each method should be used.

  16. Quantification and Statistical Analysis Methods for Vessel Wall Components from Stained Images with Masson's Trichrome

    PubMed Central

    Hernández-Morera, Pablo; Castaño-González, Irene; Travieso-González, Carlos M.; Mompeó-Corredera, Blanca; Ortega-Santana, Francisco

    2016-01-01

    Purpose To develop a digital image processing method to quantify structural components (smooth muscle fibers and extracellular matrix) in the vessel wall stained with Masson’s trichrome, and a statistical method suitable for small sample sizes to analyze the results previously obtained. Methods The quantification method comprises two stages. The pre-processing stage improves tissue image appearance and the vessel wall area is delimited. In the feature extraction stage, the vessel wall components are segmented by grouping pixels with a similar color. The area of each component is calculated by normalizing the number of pixels of each group by the vessel wall area. Statistical analyses are implemented by permutation tests, based on resampling without replacement from the set of the observed data to obtain a sampling distribution of an estimator. The implementation can be parallelized on a multicore machine to reduce execution time. Results The methods have been tested on 48 vessel wall samples of the internal saphenous vein stained with Masson’s trichrome. The results show that the segmented areas are consistent with the perception of a team of doctors and demonstrate good correlation between the expert judgments and the measured parameters for evaluating vessel wall changes. Conclusion The proposed methodology offers a powerful tool to quantify some components of the vessel wall. It is more objective, sensitive and accurate than the biochemical and qualitative methods traditionally used. The permutation tests are suitable statistical techniques to analyze the numerical measurements obtained when the underlying assumptions of the other statistical techniques are not met. PMID:26761643

  17. Salmonella serosurveillance: different statistical methods to categorise pig herds based on serological data.

    PubMed

    Cortiñas Abrahantes, J; Bollaerts, K; Aerts, M; Ogunsanya, V; Van der Stede, Y

    2009-05-01

    This study proposes three different statistical methods that can be applied in order to categorise pig herds into two groups (high seroreactors vs. low seroreactors) based on serological test results for Salmonella-specific antibodies in pigs. All proposed statistical methods were restricted to allocate about 10% of the herds into the group defined by each of the statistical approaches as high seroreactors. Previously, semi-parametric quantile regression has been used for this purpose, and here we compare it with two other alternatives: a naive method (based on the mean values) and another based on activity region finder methodology in combination with random forest regression models. The serological response values (the sample-to-positive ratio (S/P ratio)) of 13 649 pigs from 314 Belgian pig herds were used for this comparison. Nearly 14% of these herds were assigned to the high-seroreactor-herd group by at least one of these three methods. The corrected level of agreement was calculated together with the pair-wise agreement among all three methods in order to classify herds as high- or low-level seroreactors, resulting in an agreement level greater than 92%. The results obtained from a fourth method, which is adopted by the Belgian Federal Agency for the Safety of the Food Chain (FASFC), were also compared to the previous three methods. The methods were compared in terms of their agreement as well as their advantages and disadvantages. Recommendations for each applied method are presented in relation to the objectives and the requisite policy for classifying pig herds based on serological data.

  18. Proposal for a biometrics of the cortical surface: a statistical method for relative surface distance metrics

    NASA Astrophysics Data System (ADS)

    Bookstein, Fred L.

    1995-08-01

    Recent advances in computational geometry have greatly extended the range of neuroanatomical questions that can be approached by rigorous quantitative methods. One of the major current challenges in this area is to describe the variability of human cortical surface form and its implications for individual differences in neurophysiological functioning. Existing techniques for representation of stochastically invaginated surfaces do not conduce to the necessary parametric statistical summaries. In this paper, following a hint from David Van Essen and Heather Drury, I sketch a statistical method customized for the constraints of this complex data type. Cortical surface form is represented by its Riemannian metric tensor and averaged according to parameters of a smooth averaged surface. Sulci are represented by integral trajectories of the smaller principal strains of this metric, and their statistics follow the statistics of that relative metric. The diagrams visualizing this tensor analysis look like alligator leather but summarize all aspects of cortical surface form in between the principal sulci, the reliable ones; no flattening is required.

  19. Data Mining Methods Applied to Flight Operations Quality Assurance Data: A Comparison to Standard Statistical Methods

    NASA Technical Reports Server (NTRS)

    Stolzer, Alan J.; Halford, Carl

    2007-01-01

    In a previous study, multiple regression techniques were applied to Flight Operations Quality Assurance-derived data to develop parsimonious model(s) for fuel consumption on the Boeing 757 airplane. The present study examined several data mining algorithms, including neural networks, on the fuel consumption problem and compared them to the multiple regression results obtained earlier. Using regression methods, parsimonious models were obtained that explained approximately 85% of the variation in fuel flow. In general data mining methods were more effective in predicting fuel consumption. Classification and Regression Tree methods reported correlation coefficients of .91 to .92, and General Linear Models and Multilayer Perceptron neural networks reported correlation coefficients of about .99. These data mining models show great promise for use in further examining large FOQA databases for operational and safety improvements.

  20. A new method to test shear wave splitting: Improving statistical assessment of splitting parameters

    NASA Astrophysics Data System (ADS)

    Corbalan Castejon, Ana

    Shear wave splitting has proved to be a very useful technique to probe for seismic anisotropy in the earth's interior, and measurements of seismic anisotropy are perhaps the best way to constrain the strain history of the lithosphere and asthenosphere. However, existent methods of shear wave splitting analysis do not estimate uncertainty correctly, and do not allow for careful statistical modeling of anisotropy and uncertainty in complex scenarios. Consequently, the interpretation of shear wave splitting measurements has an undesirable subjective component. This study illustrates a new method to characterize shear wave splitting and the associated uncertainty based on the cross-convolution method [Menke and Levin, 2003]. This new method has been tested on synthetic data and benchmarked with data from the Pasadena, California seismic station (PAS). Synthetic tests show that the method can successfully obtain the splitting parameters from observed split shear waves. PAS results are very reasonable and consistent with previous studies [Liu et al., 1995; Ozalaybey and Savage, 1995; Polet and Kanamori, 2002]. As presented, the Menke and Levin [2003] method does not explicitly model the errors. Our method works on noisy data without any particular need for processing, it fully accounts for correlation structures on the noise, and it models the errors with a proper bootstrapping approach. Hence, the method presented here casts the analysis of shear wave splitting into a more formal statistical context, allowing for formal hypothesis testing and more nuanced interpretation of seismic anisotropy results.

  1. Effect of the absolute statistic on gene-sampling gene-set analysis methods.

    PubMed

    Nam, Dougu

    2015-03-02

    Gene-set enrichment analysis and its modified versions have commonly been used for identifying altered functions or pathways in disease from microarray data. In particular, the simple gene-sampling gene-set analysis methods have been heavily used for datasets with only a few sample replicates. The biggest problem with this approach is the highly inflated false-positive rate. In this paper, the effect of absolute gene statistic on gene-sampling gene-set analysis methods is systematically investigated. Thus far, the absolute gene statistic has merely been regarded as a supplementary method for capturing the bidirectional changes in each gene set. Here, it is shown that incorporating the absolute gene statistic in gene-sampling gene-set analysis substantially reduces the false-positive rate and improves the overall discriminatory ability. Its effect was investigated by power, false-positive rate, and receiver operating curve for a number of simulated and real datasets. The performances of gene-set analysis methods in one-tailed (genome-wide association study) and two-tailed (gene expression data) tests were also compared and discussed.

  2. [Adequate application of quantitative and qualitative statistic analytic methods in acupuncture clinical trials].

    PubMed

    Tan, Ming T; Liu, Jian-ping; Lao, Lixing

    2012-08-01

    Recently, proper use of the statistical methods in traditional Chinese medicine (TCM) randomized controlled trials (RCTs) has received increased attention. Statistical inference based on hypothesis testing is the foundation of clinical trials and evidence-based medicine. In this article, the authors described the methodological differences between literature published in Chinese and Western journals in the design and analysis of acupuncture RCTs and the application of basic statistical principles. In China, qualitative analysis method has been widely used in acupuncture and TCM clinical trials, while the between-group quantitative analysis methods on clinical symptom scores are commonly used in the West. The evidence for and against these analytical differences were discussed based on the data of RCTs assessing acupuncture for pain relief. The authors concluded that although both methods have their unique advantages, quantitative analysis should be used as the primary analysis while qualitative analysis can be a secondary criterion for analysis. The purpose of this paper is to inspire further discussion of such special issues in clinical research design and thus contribute to the increased scientific rigor of TCM research.

  3. A new approach to NMR chemical shift additivity parameters using simultaneous linear equation method.

    PubMed

    Shahab, Yosif A; Khalil, Rabah A

    2006-10-01

    A new approach to NMR chemical shift additivity parameters using simultaneous linear equation method has been introduced. Three general nitrogen-15 NMR chemical shift additivity parameters with physical significance for aliphatic amines in methanol and cyclohexane and their hydrochlorides in methanol have been derived. A characteristic feature of these additivity parameters is the individual equation can be applied to both open-chain and rigid systems. The factors that influence the (15)N chemical shift of these substances have been determined. A new method for evaluating conformational equilibria at nitrogen in these compounds using the derived additivity parameters has been developed. Conformational analyses of these substances have been worked out. In general, the results indicate that there are four factors affecting the (15)N chemical shift of aliphatic amines; paramagnetic term (p-character), lone pair-proton interactions, proton-proton interactions, symmetry of alkyl substituents and molecular association.

  4. Trends in Citations to Books on Epidemiological and Statistical Methods in the Biomedical Literature

    PubMed Central

    Porta, Miquel; Vandenbroucke, Jan P.; Ioannidis, John P. A.; Sanz, Sergio; Fernandez, Esteve; Bhopal, Raj; Morabia, Alfredo; Victora, Cesar; Lopez, Tomàs

    2013-01-01

    Background There are no analyses of citations to books on epidemiological and statistical methods in the biomedical literature. Such analyses may shed light on how concepts and methods changed while biomedical research evolved. Our aim was to analyze the number and time trends of citations received from biomedical articles by books on epidemiological and statistical methods, and related disciplines. Methods and Findings The data source was the Web of Science. The study books were published between 1957 and 2010. The first year of publication of the citing articles was 1945. We identified 125 books that received at least 25 citations. Books first published in 1980–1989 had the highest total and median number of citations per year. Nine of the 10 most cited texts focused on statistical methods. Hosmer & Lemeshow's Applied logistic regression received the highest number of citations and highest average annual rate. It was followed by books by Fleiss, Armitage, et al., Rothman, et al., and Kalbfleisch and Prentice. Fifth in citations per year was Sackett, et al., Evidence-based medicine. The rise of multivariate methods, clinical epidemiology, or nutritional epidemiology was reflected in the citation trends. Educational textbooks, practice-oriented books, books on epidemiological substantive knowledge, and on theory and health policies were much less cited. None of the 25 top-cited books had the theoretical or sociopolitical scope of works by Cochrane, McKeown, Rose, or Morris. Conclusions Books were mainly cited to reference methods. Books first published in the 1980s continue to be most influential. Older books on theory and policies were rooted in societal and general medical concerns, while the most modern books are almost purely on methods. PMID:23667447

  5. Statistical analysis using the Bayesian nonparametric method for irradiation embrittlement of reactor pressure vessels

    NASA Astrophysics Data System (ADS)

    Takamizawa, Hisashi; Itoh, Hiroto; Nishiyama, Yutaka

    2016-10-01

    In order to understand neutron irradiation embrittlement in high fluence regions, statistical analysis using the Bayesian nonparametric (BNP) method was performed for the Japanese surveillance and material test reactor irradiation database. The BNP method is essentially expressed as an infinite summation of normal distributions, with input data being subdivided into clusters with identical statistical parameters, such as mean and standard deviation, for each cluster to estimate shifts in ductile-to-brittle transition temperature (DBTT). The clusters typically depend on chemical compositions, irradiation conditions, and the irradiation embrittlement. Specific variables contributing to the irradiation embrittlement include the content of Cu, Ni, P, Si, and Mn in the pressure vessel steels, neutron flux, neutron fluence, and irradiation temperatures. It was found that the measured shifts of DBTT correlated well with the calculated ones. Data associated with the same materials were subdivided into the same clusters even if neutron fluences were increased.

  6. A review of statistical methods for data sets with multiple censoring points

    SciTech Connect

    Gilbert, R.O.

    1995-07-06

    This report reviews and summarizes recent literature on statistical methods for analyzing data sets that are censored by multiple censoring points. This report is organized as follows. Following the introductory comments in Section 2, a brief discussion of detection limits is given in Section 3. Sections 4 and 5 focus on data analysis methods for estimating parameters and testing hypotheses, respectively, when data sets are left censored with multiple censoring points. A list of publications that deal with a variety of other applications for censored data sets is provided in Section 6. Recommendations on future research for developing new or improved tools for statistically analyzing multiple left-censored data sets are provided in Section 7. The list of references is in Section 8.

  7. Autonomous Correction of Sensor Data Applied to Building Technologies Utilizing Statistical Processing Methods

    SciTech Connect

    Castello, Charles C; New, Joshua Ryan

    2012-01-01

    Autonomous detection and correction of potentially missing or corrupt sensor data is a essential concern in building technologies since data availability and correctness is necessary to develop accurate software models for instrumented experiments. Therefore, this paper aims to address this problem by using statistical processing methods including: (1) least squares; (2) maximum likelihood estimation; (3) segmentation averaging; and (4) threshold based techniques. Application of these validation schemes are applied to a subset of data collected from Oak Ridge National Laboratory s (ORNL) ZEBRAlliance research project, which is comprised of four single-family homes in Oak Ridge, TN outfitted with a total of 1,218 sensors. The focus of this paper is on three different types of sensor data: (1) temperature; (2) humidity; and (3) energy consumption. Simulations illustrate the threshold based statistical processing method performed best in predicting temperature, humidity, and energy data.

  8. Recent developments in statistical methods for detecting genetic loci affecting phenotypic variability.

    PubMed

    Rönnegård, Lars; Valdar, William

    2012-07-24

    A number of recent works have introduced statistical methods for detecting genetic loci that affect phenotypic variability, which we refer to as variability-controlling quantitative trait loci (vQTL). These are genetic variants whose allelic state predicts how much phenotype values will vary about their expected means. Such loci are of great potential interest in both human and non-human genetic studies, one reason being that a detected vQTL could represent a previously undetected interaction with other genes or environmental factors. The simultaneous publication of these new methods in different journals has in many cases precluded opportunity for comparison. We survey some of these methods, the respective trade-offs they imply, and the connections between them. The methods fall into three main groups: classical non-parametric, fully parametric, and semi-parametric two-stage approximations. Choosing between alternatives involves balancing the need for robustness, flexibility, and speed. For each method, we identify important assumptions and limitations, including those of practical importance, such as their scope for including covariates and random effects. We show in simulations that both parametric methods and their semi-parametric approximations can give elevated false positive rates when they ignore mean-variance relationships intrinsic to the data generation process. We conclude that choice of method depends on the trait distribution, the need to include non-genetic covariates, and the population size and structure, coupled with a critical evaluation of how these fit with the assumptions of the statistical model.

  9. Two-Time Green's Functions and the Spectral Density Method in Nonextensive Classical Statistical Mechanics

    NASA Astrophysics Data System (ADS)

    Cavallo, A.; Cosenza, F.; de Cesare, L.

    2001-12-01

    The two-time retarded and advanced Green's function technique is formulated in nonextensive classical statistical mechanics within the optimal Lagrange multiplier framework. The main spectral properties are presented and a spectral decomposition for the spectral density is obtained. Finally, the nonextensive version of the spectral density method is given and its effectiveness is tested by exploring the equilibrium properties of a classical ferromagnetic spin chain.

  10. Graph-Theoretic Statistical Methods for Detecting and Localizing Distributional Change in Multivariate Data

    DTIC Science & Technology

    2015-06-01

    THEORETIC STATISTICAL METHODS FOR DETECTING AND LOCALIZING DISTRIBUTIONAL CHANGE IN MULTIVARIATE DATA by Matthew A. Hawks June 2015...existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this...DISTRIBUTIONAL CHANGE IN MULTIVARIATE DATA 5. FUNDING NUMBERS 6. AUTHOR(S) Hawks, Matthew A. 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES

  11. Statistical Methods for Estimation of Direct and Differential Kinematics of the Vocal Tract

    PubMed Central

    Lammert, Adam; Goldstein, Louis; Narayanan, Shrikanth; Iskarous, Khalil

    2012-01-01

    We present and evaluate two statistical methods for estimating kinematic relationships of the speech production system: Artificial Neural Networks and Locally-Weighted Regression. The work is motivated by the need to characterize this motor system, with particular focus on estimating differential aspects of kinematics. Kinematic analysis will facilitate progress in a variety of areas, including the nature of speech production goals, articulatory redundancy and, relatedly, acoustic-to-articulatory inversion. Statistical methods must be used to estimate these relationships from data since they are infeasible to express in closed form. Statistical models are optimized and evaluated – using a heldout data validation procedure – on two sets of synthetic speech data. The theoretical and practical advantages of both methods are also discussed. It is shown that both direct and differential kinematics can be estimated with high accuracy, even for complex, nonlinear relationships. Locally-Weighted Regression displays the best overall performance, which may be due to practical advantages in its training procedure. Moreover, accurate estimation can be achieved using only a modest amount of training data, as judged by convergence of performance. The algorithms are also applied to real-time MRI data, and the results are generally consistent with those obtained from synthetic data. PMID:24052685

  12. Low dose dynamic CT myocardial perfusion imaging using a statistical iterative reconstruction method

    SciTech Connect

    Tao, Yinghua; Chen, Guang-Hong; Hacker, Timothy A.; Raval, Amish N.; Van Lysel, Michael S.; Speidel, Michael A.

    2014-07-15

    Purpose: Dynamic CT myocardial perfusion imaging has the potential to provide both functional and anatomical information regarding coronary artery stenosis. However, radiation dose can be potentially high due to repeated scanning of the same region. The purpose of this study is to investigate the use of statistical iterative reconstruction to improve parametric maps of myocardial perfusion derived from a low tube current dynamic CT acquisition. Methods: Four pigs underwent high (500 mA) and low (25 mA) dose dynamic CT myocardial perfusion scans with and without coronary occlusion. To delineate the affected myocardial territory, an N-13 ammonia PET perfusion scan was performed for each animal in each occlusion state. Filtered backprojection (FBP) reconstruction was first applied to all CT data sets. Then, a statistical iterative reconstruction (SIR) method was applied to data sets acquired at low dose. Image voxel noise was matched between the low dose SIR and high dose FBP reconstructions. CT perfusion maps were compared among the low dose FBP, low dose SIR and high dose FBP reconstructions. Numerical simulations of a dynamic CT scan at high and low dose (20:1 ratio) were performed to quantitatively evaluate SIR and FBP performance in terms of flow map accuracy, precision, dose efficiency, and spatial resolution. Results: Forin vivo studies, the 500 mA FBP maps gave −88.4%, −96.0%, −76.7%, and −65.8% flow change in the occluded anterior region compared to the open-coronary scans (four animals). The percent changes in the 25 mA SIR maps were in good agreement, measuring −94.7%, −81.6%, −84.0%, and −72.2%. The 25 mA FBP maps gave unreliable flow measurements due to streaks caused by photon starvation (percent changes of +137.4%, +71.0%, −11.8%, and −3.5%). Agreement between 25 mA SIR and 500 mA FBP global flow was −9.7%, 8.8%, −3.1%, and 26.4%. The average variability of flow measurements in a nonoccluded region was 16.3%, 24.1%, and 937

  13. Low dose dynamic CT myocardial perfusion imaging using a statistical iterative reconstruction method

    PubMed Central

    Tao, Yinghua; Chen, Guang-Hong; Hacker, Timothy A.; Raval, Amish N.; Van Lysel, Michael S.; Speidel, Michael A.

    2014-01-01

    Purpose: Dynamic CT myocardial perfusion imaging has the potential to provide both functional and anatomical information regarding coronary artery stenosis. However, radiation dose can be potentially high due to repeated scanning of the same region. The purpose of this study is to investigate the use of statistical iterative reconstruction to improve parametric maps of myocardial perfusion derived from a low tube current dynamic CT acquisition. Methods: Four pigs underwent high (500 mA) and low (25 mA) dose dynamic CT myocardial perfusion scans with and without coronary occlusion. To delineate the affected myocardial territory, an N-13 ammonia PET perfusion scan was performed for each animal in each occlusion state. Filtered backprojection (FBP) reconstruction was first applied to all CT data sets. Then, a statistical iterative reconstruction (SIR) method was applied to data sets acquired at low dose. Image voxel noise was matched between the low dose SIR and high dose FBP reconstructions. CT perfusion maps were compared among the low dose FBP, low dose SIR and high dose FBP reconstructions. Numerical simulations of a dynamic CT scan at high and low dose (20:1 ratio) were performed to quantitatively evaluate SIR and FBP performance in terms of flow map accuracy, precision, dose efficiency, and spatial resolution. Results: Forin vivo studies, the 500 mA FBP maps gave −88.4%, −96.0%, −76.7%, and −65.8% flow change in the occluded anterior region compared to the open-coronary scans (four animals). The percent changes in the 25 mA SIR maps were in good agreement, measuring −94.7%, −81.6%, −84.0%, and −72.2%. The 25 mA FBP maps gave unreliable flow measurements due to streaks caused by photon starvation (percent changes of +137.4%, +71.0%, −11.8%, and −3.5%). Agreement between 25 mA SIR and 500 mA FBP global flow was −9.7%, 8.8%, −3.1%, and 26.4%. The average variability of flow measurements in a nonoccluded region was 16.3%, 24.1%, and 937

  14. Accuracy Evaluation of a Mobile Mapping System with Advanced Statistical Methods

    NASA Astrophysics Data System (ADS)

    Toschi, I.; Rodríguez-Gonzálvez, P.; Remondino, F.; Minto, S.; Orlandini, S.; Fuller, A.

    2015-02-01

    This paper discusses a methodology to evaluate the precision and the accuracy of a commercial Mobile Mapping System (MMS) with advanced statistical methods. So far, the metric potentialities of this emerging mapping technology have been studied in few papers, where generally the assumption that errors follow a normal distribution is made. In fact, this hypothesis should be carefully verified in advance, in order to test how well the Gaussian classic statistics can adapt to datasets that are usually affected by asymmetrical gross errors. The workflow adopted in this study relies on a Gaussian assessment, followed by an outlier filtering process. Finally, non-parametric statistical models are applied, in order to achieve a robust estimation of the error dispersion. Among the different MMSs available on the market, the latest solution provided by RIEGL is here tested, i.e. the VMX-450 Mobile Laser Scanning System. The test-area is the historic city centre of Trento (Italy), selected in order to assess the system performance in dealing with a challenging and historic urban scenario. Reference measures are derived from photogrammetric and Terrestrial Laser Scanning (TLS) surveys. All datasets show a large lack of symmetry that leads to the conclusion that the standard normal parameters are not adequate to assess this type of data. The use of non-normal statistics gives thus a more appropriate description of the data and yields results that meet the quoted a-priori errors.

  15. Overview of the SAMSI year-long program on Statistical, Mathematical and Computational Methods for Astronomy

    NASA Astrophysics Data System (ADS)

    Jogesh Babu, G.

    2017-01-01

    A year-long research (Aug 2016- May 2017) program on `Statistical, Mathematical and Computational Methods for Astronomy (ASTRO)’ is well under way at Statistical and Applied Mathematical Sciences Institute (SAMSI), a National Science Foundation research institute in Research Triangle Park, NC. This program has brought together astronomers, computer scientists, applied mathematicians and statisticians. The main aims of this program are: to foster cross-disciplinary activities; to accelerate the adoption of modern statistical and mathematical tools into modern astronomy; and to develop new tools needed for important astronomical research problems. The program provides multiple avenues for cross-disciplinary interactions, including several workshops, long-term visitors, and regular teleconferences, so participants can continue collaborations, even if they can only spend limited time in residence at SAMSI. The main program is organized around five working groups:i) Uncertainty Quantification and Astrophysical Emulationii) Synoptic Time Domain Surveysiii) Multivariate and Irregularly Sampled Time Seriesiv) Astrophysical Populationsv) Statistics, computation, and modeling in cosmology.A brief description of each of the work under way by these groups will be given. Overlaps among various working groups will also be highlighted. How the wider astronomy community can both participate and benefit from the activities, will be briefly mentioned.

  16. Comparison of prosthetic models produced by traditional and additive manufacturing methods

    PubMed Central

    Park, Jin-Young; Kim, Hae-Young; Kim, Ji-Hwan; Kim, Jae-Hong

    2015-01-01

    PURPOSE The purpose of this study was to verify the clinical-feasibility of additive manufacturing by comparing the accuracy of four different manufacturing methods for metal coping: the conventional lost wax technique (CLWT); subtractive methods with wax blank milling (WBM); and two additive methods, multi jet modeling (MJM), and micro-stereolithography (Micro-SLA). MATERIALS AND METHODS Thirty study models were created using an acrylic model with the maxillary upper right canine, first premolar, and first molar teeth. Based on the scan files from a non-contact blue light scanner (Identica; Medit Co. Ltd., Seoul, Korea), thirty cores were produced using the WBM, MJM, and Micro-SLA methods, respectively, and another thirty frameworks were produced using the CLWT method. To measure the marginal and internal gap, the silicone replica method was adopted, and the silicone images obtained were evaluated using a digital microscope (KH-7700; Hirox, Tokyo, Japan) at 140X magnification. Analyses were performed using two-way analysis of variance (ANOVA) and Tukey post hoc test (α=.05). RESULTS The mean marginal gaps and internal gaps showed significant differences according to tooth type (P<.001 and P<.001, respectively) and manufacturing method (P<.037 and P<.001, respectively). Micro-SLA did not show any significant difference from CLWT regarding mean marginal gap compared to the WBM and MJM methods. CONCLUSION The mean values of gaps resulting from the four different manufacturing methods were within a clinically allowable range, and, thus, the clinical use of additive manufacturing methods is acceptable as an alternative to the traditional lost wax-technique and subtractive manufacturing. PMID:26330976

  17. Evaluation of Statistical Rainfall Disaggregation Methods Using Rain-Gauge Information for West-Central Florida

    SciTech Connect

    Murch, Renee Rokicki; Zhang, Jing; Ross, Mark; Ganguly, Auroop R; Nachabe, Mahmood

    2008-01-01

    Rainfall disaggregation in time can be useful for the simulation of hydrologic systems and the prediction of floods and flash floods. Disaggregation of rainfall to timescales less than 1 h can be especially useful for small urbanized watershed study, and for continuous hydrologic simulations and when Hortonian or saturation-excess runoff dominates. However, the majority of rain gauges in any region record rainfall in daily time steps or, very often, hourly records have extensive missing data. Also, the convective nature of the rainfall can result in significant differences in the measured rainfall at nearby gauges. This study evaluates several statistical approaches for rainfall disaggregation which may be applicable using data from West-Central Florida, specifically from 1 h observations to 15 min records, and proposes new methodologies that have the potential to outperform existing approaches. Four approaches are examined. The first approach is an existing direct scaling method that utilizes observed 15 min rainfall at secondary rain gauges, to disaggregate observed 1 h rainfall at more numerous primary rain gauges. The second approach is an extension of an existing method for continuous rainfall disaggregation through statistical distributional assumptions. The third approach relies on artificial neural networks for the disaggregation process without sorting and the fourth approach extends the neural network methods through statistical preprocessing via new sorting and desorting schemes. The applicability and performance of these methods were evaluated using information from a fairly dense rain gauge network in West-Central Florida. Of the four methods compared, the sorted neural networks and the direct scaling method predicted peak rainfall magnitudes significantly better than the remaining techniques. The study also suggests that desorting algorithms would also be useful to randomly replace the artificial hyetograph within a rainfall period.

  18. The breaking load method - Results and statistical modification from the ASTM interlaboratory test program

    NASA Technical Reports Server (NTRS)

    Colvin, E. L.; Emptage, M. R.

    1992-01-01

    The breaking load test provides quantitative stress corrosion cracking data by determining the residual strength of tension specimens that have been exposed to corrosive environments. Eight laboratories have participated in a cooperative test program under the auspices of ASTM Committee G-1 to evaluate the new test method. All eight laboratories were able to distinguish between three tempers of aluminum alloy 7075. The statistical analysis procedures that were used in the test program do not work well in all situations. An alternative procedure using Box-Cox transformations shows a great deal of promise. An ASTM standard method has been drafted which incorporates the Box-Cox procedure.

  19. Sharpening method of satellite thermal image based on the geographical statistical model

    NASA Astrophysics Data System (ADS)

    Qi, Pengcheng; Hu, Shixiong; Zhang, Haijun; Guo, Guangmeng

    2016-04-01

    To improve the effectiveness of thermal sharpening in mountainous regions, paying more attention to the laws of land surface energy balance, a thermal sharpening method based on the geographical statistical model (GSM) is proposed. Explanatory variables were selected from the processes of land surface energy budget and thermal infrared electromagnetic radiation transmission, then high spatial resolution (57 m) raster layers were generated for these variables through spatially simulating or using other raster data as proxies. Based on this, the local adaptation statistical relationship between brightness temperature (BT) and the explanatory variables, i.e., the GSM, was built at 1026-m resolution using the method of multivariate adaptive regression splines. Finally, the GSM was applied to the high-resolution (57-m) explanatory variables; thus, the high-resolution (57-m) BT image was obtained. This method produced a sharpening result with low error and good visual effect. The method can avoid the blind choice of explanatory variables and remove the dependence on synchronous imagery at visible and near-infrared bands. The influences of the explanatory variable combination, sampling method, and the residual error correction on sharpening results were analyzed deliberately, and their influence mechanisms are reported herein.

  20. Advances in statistical methods to map quantitative trait loci in outbred populations.

    PubMed

    Hoeschele, I; Uimari, P; Grignola, F E; Zhang, Q; Gage, K M

    1997-11-01

    Statistical methods to map quantitative trait loci (QTL) in outbred populations are reviewed, extensions and applications to human and plant genetic data are indicated, and areas for further research are identified. Simple and computationally inexpensive methods include (multiple) linear regression of phenotype on marker genotypes and regression of squared phenotypic differences among relative pairs on estimated proportions of identity-by-descent at a locus. These methods are less suited for genetic parameter estimation in outbred populations but allow the determination of test statistic distributions via simulation or data permutation; however, further inferences including confidence intervals of QTL location require the use of Monte Carlo or bootstrap sampling techniques. A method which is intermediate in computational requirements is residual maximum likelihood (REML) with a covariance matrix of random QTL effects conditional on information from multiple linked markers. Testing for the number of QTLs on a chromosome is difficult in a classical framework. The computationally most demanding methods are maximum likelihood and Bayesian analysis, which take account of the distribution of multilocus marker-QTL genotypes on a pedigree and permit investigators to fit different models of variation at the QTL. The Bayesian analysis includes the number of QTLs on a chromosome as an unknown.

  1. Advances in Statistical Methods to Map Quantitative Trait Loci in Outbred Populations

    PubMed Central

    Hoeschele, I.; Uimari, P.; Grignola, F. E.; Zhang, Q.; Gage, K. M.

    1997-01-01

    Statistical methods to map quantitative trait loci (QTL) in outbred populations are reviewed, extensions and applications to human and plant genetic data are indicated, and areas for further research are identified. Simple and computationally inexpensive methods include (multiple) linear regression of phenotype on marker genotypes and regression of squared phenotypic differences among relative pairs on estimated proportions of identity-by-descent at a locus. These methods are less suited for genetic parameter estimation in outbred populations but allow the determination of test statistic distributions via simulation or data permutation; however, further inferences including confidence intervals of QTL location require the use of Monte Carlo or bootstrap sampling techniques. A method which is intermediate in computational requirements is residual maximum likelihood (REML) with a covariance matrix of random QTL effects conditional on information from multiple linked markers. Testing for the number of QTLs on a chromosome is difficult in a classical framework. The computationally most demanding methods are maximum likelihood and Bayesian analysis, which take account of the distribution of multilocus marker-QTL genotypes on a pedigree and permit investigators to fit different models of variation at the QTL. The Bayesian analysis includes the number of QTLs on a chromosome as an unknown. PMID:9383084

  2. The Capacity Profile: A Method to Classify Additional Care Needs in Children with Neurodevelopmental Disabilities

    ERIC Educational Resources Information Center

    Meester-Delver, Anke; Beelen, Anita; Hennekam, Raoul; Nollet, Frans; Hadders-Algra, Mijna

    2007-01-01

    The aim of this study was to determine the interrater reliability and stability over time of the Capacity Profile (CAP). The CAP is a standardized method for classifying additional care needs indicated by current impairments in five domains of body functions: physical health, neuromusculoskeletal and movement-related, sensory, mental, and voice…

  3. An Embedded Statistical Method for Coupling Molecular Dynamics and Finite Element Analyses

    NASA Technical Reports Server (NTRS)

    Saether, E.; Glaessgen, E.H.; Yamakov, V.

    2008-01-01

    The coupling of molecular dynamics (MD) simulations with finite element methods (FEM) yields computationally efficient models that link fundamental material processes at the atomistic level with continuum field responses at higher length scales. The theoretical challenge involves developing a seamless connection along an interface between two inherently different simulation frameworks. Various specialized methods have been developed to solve particular classes of problems. Many of these methods link the kinematics of individual MD atoms with FEM nodes at their common interface, necessarily requiring that the finite element mesh be refined to atomic resolution. Some of these coupling approaches also require simulations to be carried out at 0 K and restrict modeling to two-dimensional material domains due to difficulties in simulating full three-dimensional material processes. In the present work, a new approach to MD-FEM coupling is developed based on a restatement of the standard boundary value problem used to define a coupled domain. The method replaces a direct linkage of individual MD atoms and finite element (FE) nodes with a statistical averaging of atomistic displacements in local atomic volumes associated with each FE node in an interface region. The FEM and MD computational systems are effectively independent and communicate only through an iterative update of their boundary conditions. With the use of statistical averages of the atomistic quantities to couple the two computational schemes, the developed approach is referred to as an embedded statistical coupling method (ESCM). ESCM provides an enhanced coupling methodology that is inherently applicable to three-dimensional domains, avoids discretization of the continuum model to atomic scale resolution, and permits finite temperature states to be applied.

  4. Direct comparison of two statistical methods for determination of evoked-potential thresholds

    NASA Astrophysics Data System (ADS)

    Langford, Ted L.; Patterson, James H., Jr.

    1994-07-01

    Several statistical procedures have been proposed as objective methods for determining evoked-potential thresholds. Data have been presented to support each of the methods, but there have not been direct comparisons using the same data. The goal of the present study was to evaluate correlation and variance ratio statistics using common data. A secondary goal was to evaluate the utility of a derived potential for determining thresholds. Chronic, bipolar electrodes were stereotaxically implanted in the inferior colliculi of six chinchillas. Evoked potentials were obtained at 0.25, 0.5, 1.0, 2.0, 4.0 and 8.0 kHz using 12-ms tone bursts and 12-ms tone bursts superimposed on 120-ms pedestal tones which were of the same frequency as the bursts, but lower in amplitude by 15 dB. Alternate responses were averaged in blocks of 200 to 4000 depending on the size of the response. Correlations were calculated for the pairs of averages. A response was deemed present if the correlation coefficient reached the 0.05 level of significance in 4000 or fewer averages. Threshold was defined as the mean of the level at which the correlation was significant and a level 5 dB below that at which it was not. Variance ratios were calculated as described by Elberling and Don (1984) using the same data. Averaged tone burst and tone burst-plus pedestal data were differenced and the resulting waveforms subjected to the same statistical analyses described above. All analyses yielded thresholds which were essentially the same as those obtained using behavioral methods. When the difference between stimulus durations is taken into account, however, evoked-potential methods produced lower thresholds than behavioral methods.

  5. Boosting Bayesian parameter inference of stochastic differential equation models with methods from statistical physics

    NASA Astrophysics Data System (ADS)

    Albert, Carlo; Ulzega, Simone; Stoop, Ruedi

    2016-04-01

    Measured time-series of both precipitation and runoff are known to exhibit highly non-trivial statistical properties. For making reliable probabilistic predictions in hydrology, it is therefore desirable to have stochastic models with output distributions that share these properties. When parameters of such models have to be inferred from data, we also need to quantify the associated parametric uncertainty. For non-trivial stochastic models, however, this latter step is typically very demanding, both conceptually and numerically, and always never done in hydrology. Here, we demonstrate that methods developed in statistical physics make a large class of stochastic differential equation (SDE) models amenable to a full-fledged Bayesian parameter inference. For concreteness we demonstrate these methods by means of a simple yet non-trivial toy SDE model. We consider a natural catchment that can be described by a linear reservoir, at the scale of observation. All the neglected processes are assumed to happen at much shorter time-scales and are therefore modeled with a Gaussian white noise term, the standard deviation of which is assumed to scale linearly with the system state (water volume in the catchment). Even for constant input, the outputs of this simple non-linear SDE model show a wealth of desirable statistical properties, such as fat-tailed distributions and long-range correlations. Standard algorithms for Bayesian inference fail, for models of this kind, because their likelihood functions are extremely high-dimensional intractable integrals over all possible model realizations. The use of Kalman filters is illegitimate due to the non-linearity of the model. Particle filters could be used but become increasingly inefficient with growing number of data points. Hamiltonian Monte Carlo algorithms allow us to translate this inference problem to the problem of simulating the dynamics of a statistical mechanics system and give us access to most sophisticated methods

  6. Advanced statistical methods for improved data analysis of NASA astrophysics missions

    NASA Technical Reports Server (NTRS)

    Feigelson, Eric D.

    1992-01-01

    The investigators under this grant studied ways to improve the statistical analysis of astronomical data. They looked at existing techniques, the development of new techniques, and the production and distribution of specialized software to the astronomical community. Abstracts of nine papers that were produced are included, as well as brief descriptions of four software packages. The articles that are abstracted discuss analytical and Monte Carlo comparisons of six different linear least squares fits, a (second) paper on linear regression in astronomy, two reviews of public domain software for the astronomer, subsample and half-sample methods for estimating sampling distributions, a nonparametric estimation of survival functions under dependent competing risks, censoring in astronomical data due to nondetections, an astronomy survival analysis computer package called ASURV, and improving the statistical methodology of astronomical data analysis.

  7. A Modified Time-Delay Addition Method to Extract Resistive Leakage Current of MOSA

    NASA Astrophysics Data System (ADS)

    Khodsuz, Masume; Mirzaie, Mohammad

    2016-12-01

    Metal oxide surge arresters are one of the most important equipment for power system protection against switching and lightning over-voltages. High-energy stresses and environmental features are the main factors which degrade surge arresters. In order to verify surge arresters good condition, their monitoring is necessary. The majority of surge arrester monitoring techniques is based on total leakage current decomposition of their capacitive and resistive components. This paper introduces a new approach based on time-delay addition method to extract the resistive current from the total leakage current without measuring voltage signal. Surge arrester model for calculating leakage current has been performed in ATP-EMTP. In addition, the signal processing has been done using MATLAB software. To show the accuracy of the proposed method, experimental tests have been performed to extract resistive leakage current by the proposed method.

  8. Reducing the matrix effects in chemical analysis: fusion of isotope dilution and standard addition methods

    NASA Astrophysics Data System (ADS)

    Pagliano, Enea; Meija, Juris

    2016-04-01

    The combination of isotope dilution and mass spectrometry has become an ubiquitous tool of chemical analysis. Often perceived as one of the most accurate methods of chemical analysis, it is not without shortcomings. Current isotope dilution equations are not capable of fully addressing one of the key problems encountered in chemical analysis: the possible effect of sample matrix on measured isotope ratios. The method of standard addition does compensate for the effect of sample matrix by making sure that all measured solutions have identical composition. While it is impossible to attain such condition in traditional isotope dilution, we present equations which allow for matrix-matching between all measured solutions by fusion of isotope dilution and standard addition methods.

  9. Calculation of statistic estimates of kinetic parameters from substrate uncompetitive inhibition equation using the median method.

    PubMed

    Valencia, Pedro L; Astudillo-Castro, Carolina; Gajardo, Diego; Flores, Sebastián

    2017-04-01

    We provide initial rate data from enzymatic reaction experiments and tis processing to estimate the kinetic parameters from the substrate uncompetitive inhibition equation using the median method published by Eisenthal and Cornish-Bowden (Cornish-Bowden and Eisenthal, 1974; Eisenthal and Cornish-Bowden, 1974). The method was denominated the direct linear plot and consists in the calculation of the median from a dataset of kinetic parameters Vmax and Km from the Michaelis-Menten equation. In this opportunity we present the procedure to applicate the direct linear plot to the substrate uncompetitive inhibition equation; a three-parameter equation. The median method is characterized for its robustness and its insensibility to outlier. The calculations are presented in an Excel datasheet and a computational algorithm was developed in the free software Python. The kinetic parameters of the substrate uncompetitive inhibition equation Vmax , Km and Ks were calculated using three experimental points from the dataset formed by 13 experimental points. All the 286 combinations were calculated. The dataset of kinetic parameters resulting from this combinatorial was used to calculate the median which corresponds to the statistic estimator of the real kinetic parameters. A comparative statistical analyses between the median method and the least squares was published in Valencia et al. [3].

  10. Statistical method for detecting phase shifts in alpha rhythm from human electroencephalogram data

    NASA Astrophysics Data System (ADS)

    Naruse, Yasushi; Takiyama, Ken; Okada, Masato; Umehara, Hiroaki

    2013-04-01

    We developed a statistical method for detecting discontinuous phase changes (phase shifts) in fluctuating alpha rhythms in the human brain from electroencephalogram (EEG) data obtained in a single trial. This method uses the state space models and the line process technique, which is a Bayesian method for detecting discontinuity in an image. By applying this method to simulated data, we were able to detect the phase and amplitude shifts in a single simulated trial. Further, we demonstrated that this method can detect phase shifts caused by a visual stimulus in the alpha rhythm from experimental EEG data even in a single trial. The results for the experimental data showed that the timings of the phase shifts in the early latency period were similar between many of the trials, and that those in the late latency period were different between the trials. The conventional averaging method can only detect phase shifts that occur at similar timings between many of the trials, and therefore, the phase shifts that occur at differing timings cannot be detected using the conventional method. Consequently, our obtained results indicate the practicality of our method. Thus, we believe that our method will contribute to studies examining the phase dynamics of nonlinear alpha rhythm oscillators.

  11. Evaluation of dissolution profile similarity - Comparison between the f2, the multivariate statistical distance and the f2 bootstrapping methods.

    PubMed

    Paixão, Paulo; Gouveia, Luís F; Silva, Nuno; Morais, José A G

    2017-03-01

    A simulation study is presented, evaluating the performance of the f2, the model-independent multivariate statistical distance and the f2 bootstrap methods in the ability to conclude similarity between two dissolution profiles. Different dissolution profiles, based on the Noyes-Whitney equation and ranging from theoretical f2 values between 100 and 40, were simulated. Variability was introduced in the dissolution model parameters in an increasing order, ranging from a situation complying with the European guidelines requirements for the use of the f2 metric to several situations where the f2 metric could not be used anymore. Results have shown that the f2 is an acceptable metric when used according to the regulatory requirements, but loses its applicability when variability increases. The multivariate statistical distance presented contradictory results in several of the simulation scenarios, which makes it an unreliable metric for dissolution profile comparisons. The bootstrap f2, although conservative in its conclusions is an alternative suitable method. Overall, as variability increases, all of the discussed methods reveal problems that can only be solved by increasing the number of dosage form units used in the comparison, which is usually not practical or feasible. Additionally, experimental corrective measures may be undertaken in order to reduce the overall variability, particularly when it is shown that it is mainly due to the dissolution assessment instead of being intrinsic to the dosage form.

  12. Monitoring Method of Cow Anthrax Based on Gis and Spatial Statistical Analysis

    NASA Astrophysics Data System (ADS)

    Li, Lin; Yang, Yong; Wang, Hongbin; Dong, Jing; Zhao, Yujun; He, Jianbin; Fan, Honggang

    Geographic information system (GIS) is a computer application system, which possesses the ability of manipulating spatial information and has been used in many fields related with the spatial information management. Many methods and models have been established for analyzing animal diseases distribution models and temporal-spatial transmission models. Great benefits have been gained from the application of GIS in animal disease epidemiology. GIS is now a very important tool in animal disease epidemiological research. Spatial analysis function of GIS can be widened and strengthened by using spatial statistical analysis, allowing for the deeper exploration, analysis, manipulation and interpretation of spatial pattern and spatial correlation of the animal disease. In this paper, we analyzed the cow anthrax spatial distribution characteristics in the target district A (due to the secret of epidemic data we call it district A) based on the established GIS of the cow anthrax in this district in combination of spatial statistical analysis and GIS. The Cow anthrax is biogeochemical disease, and its geographical distribution is related closely to the environmental factors of habitats and has some spatial characteristics, and therefore the correct analysis of the spatial distribution of anthrax cow for monitoring and the prevention and control of anthrax has a very important role. However, the application of classic statistical methods in some areas is very difficult because of the pastoral nomadic context. The high mobility of livestock and the lack of enough suitable sampling for the some of the difficulties in monitoring currently make it nearly impossible to apply rigorous random sampling methods. It is thus necessary to develop an alternative sampling method, which could overcome the lack of sampling and meet the requirements for randomness. The GIS computer application software ArcGIS9.1 was used to overcome the lack of data of sampling sites.Using ArcGIS 9.1 and GEODA

  13. InSAR Tropospheric Correction Methods: A Statistical Comparison over Different Regions

    NASA Astrophysics Data System (ADS)

    Bekaert, D. P.; Walters, R. J.; Wright, T. J.; Hooper, A. J.; Parker, D. J.

    2015-12-01

    Observing small magnitude surface displacements through InSAR is highly challenging, and requires advanced correction techniques to reduce noise. In fact, one of the largest obstacles facing the InSAR community is related to tropospheric noise correction. Spatial and temporal variations in temperature, pressure, and relative humidity result in a spatially-variable InSAR tropospheric signal, which masks smaller surface displacements due to tectonic or volcanic deformation. Correction methods applied today include those relying on weather model data, GNSS and/or spectrometer data. Unfortunately, these methods are often limited by the spatial and temporal resolution of the auxiliary data. Alternatively a correction can be estimated from the high-resolution interferometric phase by assuming a linear or a power-law relationship between the phase and topography. For these methods, the challenge lies in separating deformation from tropospheric signals. We will present results of a statistical comparison of the state-of-the-art tropospheric corrections estimated from spectrometer products (MERIS and MODIS), a low and high spatial-resolution weather model (ERA-I and WRF), and both the conventional linear and power-law empirical methods. We evaluate the correction capability over Southern Mexico, Italy, and El Hierro, and investigate the impact of increasing cloud cover on the accuracy of the tropospheric delay estimation. We find that each method has its strengths and weaknesses, and suggest that further developments should aim to combine different correction methods. All the presented methods are included into our new open source software package called TRAIN - Toolbox for Reducing Atmospheric InSAR Noise (Bekaert et al., in review), which is available to the community Bekaert, D., R. Walters, T. Wright, A. Hooper, and D. Parker (in review), Statistical comparison of InSAR tropospheric correction techniques, Remote Sensing of Environment

  14. A six-beam method to measure turbulence statistics using ground-based wind lidars

    NASA Astrophysics Data System (ADS)

    Sathe, A.; Mann, J.; Vasiljevic, N.; Lea, G.

    2014-10-01

    A so-called six-beam method is proposed to measure atmospheric turbulence using a ground-based wind lidar. This method requires measurement of the radial velocity variances at five equally spaced azimuth angles on the base of a scanning cone and one measurement at the center of the scanning circle, i.e.using a vertical beam at the same height. The scanning configuration is optimized to minimize the sum of the random errors in the measurement of the second-order moments of the components (u,v, w) of the wind field. We present this method as an alternative to the so-called velocity azimuth display (VAD) method that is routinely used in commercial wind lidars, and which usually results in significant averaging effects of measured turbulence. In the VAD method, the high frequency radial velocity measurements are used instead of their variances. The measurements are performed using a pulsed lidar (WindScanner), and the derived turbulence statistics (using both methods) such as the u and v variances are compared with those obtained from a reference cup anemometer and a wind vane at 89 m height under different atmospheric stabilities. The measurements show that in comparison to the reference cup anemometer, depending on the atmospheric stability and the wind field component, the six-beam method measures between 85-101% of the reference turbulence, whereas the VAD method measures between 66-87% of the reference turbulence.

  15. A six-beam method to measure turbulence statistics using ground-based wind lidars

    NASA Astrophysics Data System (ADS)

    Sathe, A.; Mann, J.; Vasiljevic, N.; Lea, G.

    2015-02-01

    A so-called six-beam method is proposed to measure atmospheric turbulence using a ground-based wind lidar. This method requires measurement of the radial velocity variances at five equally spaced azimuth angles on the base of a scanning cone and one measurement at the centre of the scanning circle, i.e.using a vertical beam at the same height. The scanning configuration is optimized to minimize the sum of the random errors in the measurement of the second-order moments of the components (u,v, w) of the wind field. We present this method as an alternative to the so-called velocity azimuth display (VAD) method that is routinely used in commercial wind lidars, and which usually results in significant averaging effects of measured turbulence. In the VAD method, the high frequency radial velocity measurements are used instead of their variances. The measurements are performed using a pulsed lidar (WindScanner), and the derived turbulence statistics (using both methods) such as the u and v variances are compared with those obtained from a reference cup anemometer and a wind vane at 89 m height under different atmospheric stabilities. The measurements show that in comparison to the reference cup anemometer, depending on the atmospheric stability and the wind field component, the six-beam method measures between 85 and 101% of the reference turbulence, whereas the VAD method measures between 66 and 87% of the reference turbulence.

  16. Appplication of statistical mechanical methods to the modeling of social networks

    NASA Astrophysics Data System (ADS)

    Strathman, Anthony Robert

    With the recent availability of large-scale social data sets, social networks have become open to quantitative analysis via the methods of statistical physics. We examine the statistical properties of a real large-scale social network, generated from cellular phone call-trace logs. We find this network, like many other social networks to be assortative (r = 0.31) and clustered (i.e., strongly transitive, C = 0.21). We measure fluctuation scaling to identify the presence of internal structure in the network and find that structural inhomogeneity effectively disappears at the scale of a few hundred nodes, though there is no sharp cutoff. We introduce an agent-based model of social behavior, designed to model the formation and dissolution of social ties. The model is a modified Metropolis algorithm containing agents operating under the basic sociological constraints of reciprocity, communication need and transitivity. The model introduces the concept of a social temperature. We go on to show that this simple model reproduces the global statistical network features (incl. assortativity, connected fraction, mean degree, clustering, and mean shortest path length) of the real network data and undergoes two phase transitions, one being from a "gas" to a "liquid" state and the second from a liquid to a glassy state as function of this social temperature.

  17. An Efficient Resampling Method for Assessing Genome-Wide Statistical Significance in Mapping Quantitative Trait Loci

    PubMed Central

    Zou, Fei; Fine, Jason P.; Hu, Jianhua; Lin, D. Y.

    2004-01-01

    Assessing genome-wide statistical significance is an important and difficult problem in multipoint linkage analysis. Due to multiple tests on the same genome, the usual pointwise significance level based on the chi-square approximation is inappropriate. Permutation is widely used to determine genome-wide significance. Theoretical approximations are available for simple experimental crosses. In this article, we propose a resampling procedure to assess the significance of genome-wide QTL mapping for experimental crosses. The proposed method is computationally much less intensive than the permutation procedure (in the order of 102 or higher) and is applicable to complex breeding designs and sophisticated genetic models that cannot be handled by the permutation and theoretical methods. The usefulness of the proposed method is demonstrated through simulation studies and an application to a Drosophila backcross. PMID:15611194

  18. fMRI bold signal analysis using a novel nonparametric statistical method

    NASA Astrophysics Data System (ADS)

    De Mazière, Patrick A.; Van Hulle, Marc M.

    2007-03-01

    We present in this article a novel analytical method that enables the application of nonparametric rank-order statistics to fMRI data analysis, since it takes the omnipresent serial correlations (temporal autocorrelations) properly into account. Comparative simulations, using the common General Linear Model and the permutation test, confirm the validity and usefulness of our approach. Our simulations, which are performed with both synthetic and real fMRI data, show that our method requires significantly less computation time than permutation-based methods, while offering the same order of robustness and returning more information about the evoked response when combined with/compared to the results obtained with the common General Lineal Model approach.

  19. Methods for Measurement and Statistical Analysis of the Frangibility of Strengthened Glass

    NASA Astrophysics Data System (ADS)

    Tang, Zhongzhi; Mauro, Yihong; Gee, Christopher; Duffy, Delena; Meyer, Timothy; Abrams, Matthew; Walker, Kimberly; Mauro, John

    2015-06-01

    Chemically strengthened glass features a surface compression and a balancing central tension (CT) in the interior of the glass. A greater CT is usually associated with a higher level of stored elastic energy in the glass. During a fracture event, release of a greater amount of stored energy can lead to frangibility, i.e., shorter crack branching distances, smaller fragment size, and ejection of small fragments from the glass. In this paper, the frangibility and fragmentation behaviors of a series of chemically strengthened glass samples are studied using two different manual testing methods and an automated tester. Both immediate and delayed fracture events were observed. A statistical method is proposed to determine the probability of frangible fracture for glasses ion exchanged under a specific set of conditions, and analysis is performed to understand the dependence of frangibility probability on sample thickness, CT, and testing method. We also propose a more rigorous set of criteria for qualifying frangibility.

  20. Assessment of earthquake hazard by simultaneous use of the statistical method and the method of fuzzy mathematics

    NASA Astrophysics Data System (ADS)

    Feng, De-Yi; Gu, Jing-Ping; Lin, Ming-Zhou; Xu, Shao-Xie; Yu, Xue-Jun

    1984-11-01

    A probabilistic method and a retrieval method of fuzzy information are simultaneously studied for assessment of earthquake hazard, or earthquake prediction. Statistical indices of regional seismicity in three adjacent time intervals are used to predict an earthquake in the next interval. The indices are earthquake frequency, the maximum magnitude, and a parameter related to the average magnitude (or b-value) and their time derivatives. Applying the probabilistic method, we can estimate a probability for a large earthquake with magnitude larger than a certain threshold occurring in the next time interval in a given region. By using the retrieval method of fuzzy information we can classify time intervals into several classes according to the regional seismic activity in each time interval and then evaluate whether or not the next time interval belongs to seismically hazardous time interval with a large earthquake. Some examples of applying both methods to the North section of the North-South Seismic Zone in China are shown. The results obtained are in good agreement with actual earthquake history. A comparison of the probabilistic method with the method of fuzzy mathematics is made, and it is recommended that earthquake hazard be assessed by simultaneous use of both methods.

  1. Evaluation of aerosol sources at European high altitude background sites with trajectory statistical methods

    NASA Astrophysics Data System (ADS)

    Salvador, P.; Artíñano, B.; Pio, C. A.; Afonso, J.; Puxbaum, H.; Legrand, M.; Hammer, S.; Kaiser, A.

    2009-04-01

    During the last years, the analysis of a great number of back-trajectories from receptor sites has turned out to be a valuable tool to identify sources and sinks areas of atmospheric particulate matter (PM) or to reconstruct their average spatial distribution. A number of works have applied different trajectory statistical methods (TSM), which allow working simultaneously with back-trajectories computed from one or several receptor points and PM concentration values registered there. In spite of these methods have many limitations, they are simple and effective methods to detect the relevant source regions and the air flow regimes which are connected with regional and large-scale air pollution transport. In this study 5-day backward air trajectories arriving over 3 monitoring sites, were utilised and analysed simultaneously with the PM levels and chemical composition values registered there. These sites are located in the centre of Europe and can be classified into natural continental background (Schauinsland-SIL in Germany (1205 m asl), Puy de Dôme-PDD in France (1450 m asl) and Sonnblick-SBO in Austria (3106 m asl)). In the framework of the CARBOSOL European project, weekly aerosol samples were collected with High Volume Samplers (DIGITEL DH77) and PM10 (SIL and PDD) or PM2.5 (SBO) inlets, on quartz fibre filters. Filter samples were treated and analyzed for determining the levels of major organic fractions (OC, EC) and inorganic ions. Additionally, analyses for specific organic compounds were also carried out whenever was possible (Pio et al., 2007). For each day of the sampling period, four trajectories ending at 00:00, 06:00, 12:00 and 18:00 h UTC have been computed by the Norwegian Institute for Air Research NILU (SIL and PDD) and the Central Institute for Meteorology and Geophysics of Austria (SBO) using the FLEXTRA model (Stohl et al., 1995). In all, more than 8000 complete trajectories were available for analysis, each with 40 endpoints. Firstly air mass

  2. Valid statistical inference methods for a case-control study with missing data.

    PubMed

    Tian, Guo-Liang; Zhang, Chi; Jiang, Xuejun

    2016-05-19

    The main objective of this paper is to derive the valid sampling distribution of the observed counts in a case-control study with missing data under the assumption of missing at random by employing the conditional sampling method and the mechanism augmentation method. The proposed sampling distribution, called the case-control sampling distribution, can be used to calculate the standard errors of the maximum likelihood estimates of parameters via the Fisher information matrix and to generate independent samples for constructing small-sample bootstrap confidence intervals. Theoretical comparisons of the new case-control sampling distribution with two existing sampling distributions exhibit a large difference. Simulations are conducted to investigate the influence of the three different sampling distributions on statistical inferences. One finding is that the conclusion by the Wald test for testing independency under the two existing sampling distributions could be completely different (even contradictory) from the Wald test for testing the equality of the success probabilities in control/case groups under the proposed distribution. A real cervical cancer data set is used to illustrate the proposed statistical methods.

  3. A statistical method for lung tumor segmentation uncertainty in PET images based on user inference.

    PubMed

    Zheng, Chaojie; Wang, Xiuying; Feng, Dagan

    2015-01-01

    PET has been widely accepted as an effective imaging modality for lung tumor diagnosis and treatment. However, standard criteria for delineating tumor boundary from PET are yet to develop largely due to relatively low quality of PET images, uncertain tumor boundary definition, and variety of tumor characteristics. In this paper, we propose a statistical solution to segmentation uncertainty on the basis of user inference. We firstly define the uncertainty segmentation band on the basis of segmentation probability map constructed from Random Walks (RW) algorithm; and then based on the extracted features of the user inference, we use Principle Component Analysis (PCA) to formulate the statistical model for labeling the uncertainty band. We validated our method on 10 lung PET-CT phantom studies from the public RIDER collections [1] and 16 clinical PET studies where tumors were manually delineated by two experienced radiologists. The methods were validated using Dice similarity coefficient (DSC) to measure the spatial volume overlap. Our method achieved an average DSC of 0.878 ± 0.078 on phantom studies and 0.835 ± 0.039 on clinical studies.

  4. Statistical Tests of System Linearity Based on the Method of Surrogate Data

    SciTech Connect

    Hunter, N.; Paez, T.; Red-Horse, J.

    1998-11-04

    When dealing with measured data from dynamic systems we often make the tacit assumption that the data are generated by linear dynamics. While some systematic tests for linearity and determinism are available - for example the coherence fimction, the probability density fimction, and the bispectrum - fi,u-ther tests that quanti$ the existence and the degree of nonlinearity are clearly needed. In this paper we demonstrate a statistical test for the nonlinearity exhibited by a dynamic system excited by Gaussian random noise. We perform the usual division of the input and response time series data into blocks as required by the Welch method of spectrum estimation and search for significant relationships between a given input fkequency and response at harmonics of the selected input frequency. We argue that systematic tests based on the recently developed statistical method of surrogate data readily detect significant nonlinear relationships. The paper elucidates the method of surrogate data. Typical results are illustrated for a linear single degree-of-freedom system and for a system with polynomial stiffness nonlinearity.

  5. A statistical method for enhancing the production of succinic acid from Escherichia coli under anaerobic conditions.

    PubMed

    Isar, Jasmine; Agarwal, Lata; Saran, Saurabh; Saxena, Rajendra Kumar

    2006-09-01

    The most influential parameters for succinic acid production obtained through one at a time method were sucrose, tryptone, magnesium carbonate, inoculum size and incubation period. These resulted in the production of 7.0 g L(-1) of succinic acid in 60 h from Escherichia coli W3110 under anaerobic conditions. Based on these results, a statistical method, face centered central composite design (FCCCD) falling under response surface method (RSM) was employed for further enhancing the succinic acid production and to monitor the interactive effect of these parameters, which resulted in a twofold increase in yield (14.3 g L(-1) in 48 h). The analysis of variance (ANOVA) showed the adequacy of the model and the verification experiments confirmed its validity. On subsequent scale-up in a 10-L bioreactor using conditions optimized through RSM, 24.2 g L(-1) of succinic acid was obtained in 30 h. This clearly indicated that the model stood valid even on large-scale. Thus, the statistical optimization strategy led to a 3.5-fold increase in the yield of succinic acid. This is the first report on the use of FCCCD to improve succinic acid production from E. coli.

  6. A review and critique of the statistical methods used to generate reference values in pediatric echocardiography.

    PubMed

    Mawad, Wadi; Drolet, Christian; Dahdah, Nagib; Dallaire, Frederic

    2013-01-01

    Several articles have proposed echocardiographic reference values in normal pediatric subjects, but adequate validation is often lacking and has not been reviewed. The aim of this study was to review published reference values in pediatric two-dimensional and M-mode echocardiography with a specific focus on the adequacy of the statistical and mathematical methods used to normalize echocardiographic measurements. All articles proposing reference values for transthoracic pediatric echocardiography were reviewed. The types of measurements, the methods of normalization, the regression models used, and the methods used to detect potential bias in proposed reference values were abstracted. The detection of residual associations, residual heteroscedasticity, and departures from the normal distribution theory predictions were specifically analyzed. Fifty-two studies met the inclusion criteria. Most authors (87%) used parametric normalization to account for body size, but their approaches were very heterogeneous. Linear regression and indexing were the most common models. Heteroscedasticity was often present but was mentioned in only 27% of studies. The absence of residual heteroscedasticity and residual associations between the normalized measurements and the independent variables were mentioned in only 9% and 22% of the studies, respectively. Only 14% of studies documented that the distribution of the residual values was appropriate for Z score calculation or that the proportion of subjects falling outside the reference range was appropriate. Statistical suitability of the proposed reference ranges was often incompletely documented. This review underlines the great need for better standardization in echocardiographic measurement normalization.

  7. Computing physical properties with quantum Monte Carlo methods with statistical fluctuations independent of system size.

    PubMed

    Assaraf, Roland

    2014-12-01

    We show that the recently proposed correlated sampling without reweighting procedure extends the locality (asymptotic independence of the system size) of a physical property to the statistical fluctuations of its estimator. This makes the approach potentially vastly more efficient for computing space-localized properties in large systems compared with standard correlated methods. A proof is given for a large collection of noninteracting fragments. Calculations on hydrogen chains suggest that this behavior holds not only for systems displaying short-range correlations, but also for systems with long-range correlations.

  8. The Hybrid Synthetic Microdata Platform: A Method for Statistical Disclosure Control

    PubMed Central

    van den Heuvel, Edwin R.; Swertz, Morris A.

    2015-01-01

    Owners of biobanks are in an unfortunate position: on the one hand, they need to protect the privacy of their participants, whereas on the other, their usefulness relies on the disclosure of the data they hold. Existing methods for Statistical Disclosure Control attempt to find a balance between utility and confidentiality, but come at a cost for the analysts of the data. We outline an alternative perspective to the balance between confidentiality and utility. By combining the generation of synthetic data with the automated execution of data analyses, biobank owners can guarantee the privacy of their participants, yet allow the analysts to work in an unrestricted manner. PMID:26035007

  9. Application of statistical method for determination of primary mass composition of cosmic rays using simulated data

    NASA Astrophysics Data System (ADS)

    Kalita, D.; Boruah, K.

    2013-03-01

    In this paper we have studied the reconstruction of primary mass composition based on simulated longitudinal shower development using a statistical method viz. the multiparametric topological analysis (MTA) and show its applicability for the determination of the primary mass composition. In particular, the sensitivity of X max distribution is tested for simulated data using CORSIKA-6990 code assuming a number of uniform and non-uniform mixed compositions of proton(p), oxygen(O) and iron(Fe) nuclei at primary energies 1017 eV and 1018 eV.

  10. A shortcut through the Coulomb gas method for spectral linear statistics on random matrices

    NASA Astrophysics Data System (ADS)

    Deelan Cunden, Fabio; Facchi, Paolo; Vivo, Pierpaolo

    2016-04-01

    In the last decade, spectral linear statistics on large dimensional random matrices have attracted significant attention. Within the physics community, a privileged role has been played by invariant matrix ensembles for which a two-dimensional Coulomb gas analogy is available. We present a critical revision of the Coulomb gas method in random matrix theory (RMT) borrowing language and tools from large deviations theory. This allows us to formalize an equivalent, but more effective and quicker route toward RMT free energy calculations. Moreover, we argue that this more modern viewpoint is likely to shed further light on the interesting issues of weak phase transitions and evaporation phenomena recently observed in RMT.

  11. Comparison of statistical methods for assessment of population genetic diversity by DNA fingerprinting

    SciTech Connect

    Leonard, T.; Roth, A.; Gordon, D.; Wessendarp, T.; Smith, M.K.; Silbiger, R.; Torsella, J.

    1995-12-31

    The advent of newer techniques for genomic characterization, e.g., Random Amplified Polymorphic DNA (RAPD) fingerprinting, has motivated development of a number of statistical approaches for creating hypothesis tests using this genetic information. The authors specific interest is methods for deriving relative genetic diversity measures of feral populations subjected to varying degrees of environmental impacts. Decreased polymorphism and loss of alleles have been documented in stressed populations of some species as assayed by allozyme analysis and, more recently, by DNA fingerprinting. Multilocus fingerprinting techniques (such as RAPDS) differ from allozyme analysis in that they do not explicitly yield information of allelism and heterozygosity. Therefore, in order to infer these parameters, assumptions must be made concerning the relationship of observed data to the underlying DNA architecture. In particular, assessments of population genetic diversity from DNA fingerprint data have employed at least three approaches based on different assumptions about the data. The authors compare different statistics, using a previously presented set of RAPD fingerprints of three populations of brown bullhead catfish. Furthermore, the behavior of these statistics is examined--as the sample sizes of fish/population and polymorphisms/fish are varied. Sample sizes are reduced either randomly or, in the case of polymorphisms (which are electrophoretic bands), systematically pruned using the criteria of high reproducibility between duplicate samples for inclusion of data. Implications for sampling individuals and loci in assessments of population genetic diversities are discussed. Concern about population N value and statistical power is very relevant to field situations where individuals available for sampling may be limited in number.

  12. Vibration-based structural health monitoring using adaptive statistical method under varying environmental condition

    NASA Astrophysics Data System (ADS)

    Jin, Seung-Seop; Jung, Hyung-Jo

    2014-03-01

    It is well known that the dynamic properties of a structure such as natural frequencies depend not only on damage but also on environmental condition (e.g., temperature). The variation in dynamic characteristics of a structure due to environmental condition may mask damage of the structure. Without taking the change of environmental condition into account, false-positive or false-negative damage diagnosis may occur so that structural health monitoring becomes unreliable. In order to address this problem, an approach to construct a regression model based on structural responses considering environmental factors has been usually used by many researchers. The key to success of this approach is the formulation between the input and output variables of the regression model to take into account the environmental variations. However, it is quite challenging to determine proper environmental variables and measurement locations in advance for fully representing the relationship between the structural responses and the environmental variations. One alternative (i.e., novelty detection) is to remove the variations caused by environmental factors from the structural responses by using multivariate statistical analysis (e.g., principal component analysis (PCA), factor analysis, etc.). The success of this method is deeply depending on the accuracy of the description of normal condition. Generally, there is no prior information on normal condition during data acquisition, so that the normal condition is determined by subjective perspective with human-intervention. The proposed method is a novel adaptive multivariate statistical analysis for monitoring of structural damage detection under environmental change. One advantage of this method is the ability of a generative learning to capture the intrinsic characteristics of the normal condition. The proposed method is tested on numerically simulated data for a range of noise in measurement under environmental variation. A comparative

  13. A prediction method for radon in groundwater using GIS and multivariate statistics.

    PubMed

    Skeppström, Kirlna; Olofsson, Bo

    2006-08-31

    Radon (222Rn) in groundwater constitutes a source of natural radioactivity to indoor air. It is difficult to make predictions of radon levels in groundwater due to the heterogeneous distribution of uranium and radium, flow patterns and varying geochemical conditions. High radon concentrations in groundwater are not always associated with high uranium content in the bedrock, since groundwater with a high radon content has been found in regions with low to moderate uranium concentrations in the bedrock. This paper describes a methodology for predicting areas with high concentrations of 222Rn in groundwater on a general scale, within an area of approximately 185x145km2. The methodology is based on multivariate statistical analyses, including principal component analysis and regression analysis, and investigates the factors of geology, land use, topography and uranium (U) content in the bedrock. A statistical variable based method (the RV method) was used to estimate risk values related to different radon concentrations. The method was calibrated and tested on more than 4400 drilled wells in Stockholm County. The results showed that radon concentration was clearly correlated to bedrock type, well altitude and distance from fracture zones. The weighted index (risk value) estimated by the RV method provided a fair prediction of radon potential in groundwater on a general scale. Risk values obtained using the RV method were compared to radon measurements in 12 test areas (on a local scale, each of area 25x25km2) in Stockholm County and a high correlation (r=-0.87) was observed. The study showed that the occurrence and spread of radon in groundwater are guided by multiple factors, which can be used in a radon prediction method on a general scale. However, it does not provide any direct information on the geochemical and flow processes involved.

  14. Methods for estimating selected low-flow frequency statistics and harmonic mean flows for streams in Iowa

    USGS Publications Warehouse

    Eash, David A.; Barnes, Kimberlee K.

    2012-01-01

    -least-squares equations developed for estimating the harmonic-mean-flow statistic for each of the three regions range from 66.4 to 80.4 percent. The regression equations are applicable only to stream sites in Iowa with low flows not significantly affected by regulation, diversion, or urbanization and with basin characteristics within the range of those used to develop the equations. If the equations are used at ungaged sites on regulated streams, or on streams affected by water-supply and agricultural withdrawals, then the estimates will need to be adjusted by the amount of regulation or withdrawal to estimate the actual flow conditions if that is of interest. Caution is advised when applying the equations for basins with characteristics near the applicable limits of the equations and for basins located in karst topography. A test of two drainage-area ratio methods using 31 pairs of streamgages, for the annual 7-day mean low-flow statistic for a recurrence interval of 10 years, indicates a weighted drainage-area ratio method provides better estimates than regional regression equations for an ungaged site on a gaged stream in Iowa when the drainage-area ratio is between 0.5 and 1.4. These regression equations will be implemented within the U.S. Geological Survey StreamStats web-based geographic-information-system tool. StreamStats allows users to click on any ungaged site on a river and compute estimates of the seven selected statistics; in addition, 90-percent prediction intervals and the measured basin characteristics for the ungaged sites also are provided. StreamStats also allows users to click on any streamgage in Iowa and estimates computed for these seven selected statistics are provided for the streamgage.

  15. An Analysis of Research Methods and Statistical Techniques Used by Doctoral Dissertation at the Education Sciences in Turkey

    ERIC Educational Resources Information Center

    Karadag, Engin

    2010-01-01

    To assess research methods and analysis of statistical techniques employed by educational researchers, this study surveyed unpublished doctoral dissertation from 2003 to 2007. Frequently used research methods consisted of experimental research; a survey; a correlational study; and a case study. Descriptive statistics, t-test, ANOVA, factor…

  16. University and Student Segmentation: Multilevel Latent-Class Analysis of Students' Attitudes towards Research Methods and Statistics

    ERIC Educational Resources Information Center

    Mutz, Rudiger; Daniel, Hans-Dieter

    2013-01-01

    Background: It is often claimed that psychology students' attitudes towards research methods and statistics affect course enrolment, persistence, achievement, and course climate. However, the inter-institutional variability has been widely neglected in the research on students' attitudes towards research methods and statistics, but it is important…

  17. Methods of cracking a crude product to produce additional crude products

    DOEpatents

    Mo, Weijian; Roes, Augustinus Wilhelmus Maria; Nair, Vijay

    2009-09-08

    A method for producing a crude product is disclosed. Formation fluid is produced from a subsurface in situ heat treatment process. The formation fluid is separated to produce a liquid stream and a first gas stream. The first gas stream includes olefins. The liquid stream is fractionated to produce one or more crude products. At least one of the crude products has a boiling range distribution from 38.degree. C. and 343.degree. C. as determined by ASTM Method D5307. The crude product having the boiling range distribution from 38.degree. C. and 343.degree. C. is catalytically cracked to produce one or more additional crude products. At least one of the additional crude products is a second gas stream. The second gas stream has a boiling point of at most 38.degree. C. at 0.101 MPa.

  18. Solid-liquid coexistence in small systems: A statistical method to calculate melting temperatures.

    PubMed

    Hong, Qi-Jun; van de Walle, Axel

    2013-09-07

    We propose an efficient and accurate scheme to calculate the melting point (MP) of materials. This method is based on the statistical analysis of small-size coexistence molecular dynamics simulations. It eliminates the risk of metastable superheated solid in the fast-heating method, while also significantly reducing the computer cost relative to the traditional large-scale coexistence method. Using empirical potentials, we validate the method and systematically study the finite-size effect on the calculated MPs. The method converges to the exact result in the limit of large system size. An accuracy within 100 K in MP is usually achieved when simulation contains more than 100 atoms. Density functional theory examples of tantalum, high-pressure sodium, and ionic material NaCl are shown to demonstrate the accuracy and flexibility of the method in its practical applications. The method serves as a promising approach for large-scale automated material screening in which the MP is a design criterion.

  19. The method of manufacture of nylon dental partially removable prosthesis using additive technologies

    NASA Astrophysics Data System (ADS)

    Kashapov, R. N.; Korobkina, A. I.; Platonov, E. V.; Saleeva, G. T.

    2014-12-01

    The article is devoted to the topic of creating new methods of dental prosthesis. The aim of this work is to investigate the possibility of using additive technology to create nylon prosthesis. As a result of experimental studies, was made a sample of nylon partially removable prosthesis using 3D printing has allowed to simplify, accelerate and reduce the coat of manufacturing high-precision nylon dentures.

  20. Hybrid Residual Flexibility/Mass-Additive Method for Structural Dynamic Testing

    NASA Technical Reports Server (NTRS)

    Tinker, M. L.

    2003-01-01

    A large fixture was designed and constructed for modal vibration testing of International Space Station elements. This fixed-base test fixture, which weighs thousands of pounds and is anchored to a massive concrete floor, initially utilized spherical bearings and pendulum mechanisms to simulate Shuttle orbiter boundary constraints for launch of the hardware. Many difficulties were encountered during a checkout test of the common module prototype structure, mainly due to undesirable friction and excessive clearances in the test-article-to-fixture interface bearings. Measured mode shapes and frequencies were not representative of orbiter-constrained modes due to the friction and clearance effects in the bearings. As a result, a major redesign effort for the interface mechanisms was undertaken. The total cost of the fixture design, construction and checkout, and redesign was over $2 million. Because of the problems experienced with fixed-base testing, alternative free-suspension methods were studied, including the residual flexibility and mass-additive approaches. Free-suspension structural dynamics test methods utilize soft elastic bungee cords and overhead frame suspension systems that are less complex and much less expensive than fixed-base systems. The cost of free-suspension fixturing is on the order of tens of thousands of dollars as opposed to millions, for large fixed-base fixturing. In addition, free-suspension test configurations are portable, allowing modal tests to be done at sites without modal test facilities. For example, a mass-additive modal test of the ASTRO-1 Shuttle payload was done at the Kennedy Space Center launch site. In this Technical Memorandum, the mass-additive and residual flexibility test methods are described in detail. A discussion of a hybrid approach that combines the best characteristics of each method follows and is the focus of the study.

  1. [Bootstrap method-based estimation on the confidence interval for additive interaction in cohort studies].

    PubMed

    Pan, Jin-ren; Chen, Kun

    2010-07-01

    Interaction assessment is an important step in epidemiological analysis. When etiological study is carried out, the logarithmic models such as logistic model or Cox proportional hazard model are commonly used to estimate the independent effects of the risk factors. However, estimating interaction between risk factors by the regression coefficient of the product term is on multiplicative scale, and for public-health purposes, it is supposed to be on additive scale or departure from additivity. This paper illustrates with a example of cohort study by fitting Cox proportional hazard model to estimate three measures for additive interaction which presented by Rothman. Adopting the S-Plus application with a built-in Bootstrap function, it is convenient to estimate the confidence interval for additive interaction. Furthermore, this method can avoid the exaggerated estimation by using ORs in a cohort study to gain better precision. When using the complex combination models between additive interaction and multiplicative interaction, it is reasonable to choose the former one when the result is inconsistent.

  2. Estimating soil organic carbon stocks and spatial patterns with statistical and GIS-based methods.

    PubMed

    Zhi, Junjun; Jing, Changwei; Lin, Shengpan; Zhang, Cao; Liu, Qiankun; DeGloria, Stephen D; Wu, Jiaping

    2014-01-01

    Accurately quantifying soil organic carbon (SOC) is considered fundamental to studying soil quality, modeling the global carbon cycle, and assessing global climate change. This study evaluated the uncertainties caused by up-scaling of soil properties from the county scale to the provincial scale and from lower-level classification of Soil Species to Soil Group, using four methods: the mean, median, Soil Profile Statistics (SPS), and pedological professional knowledge based (PKB) methods. For the SPS method, SOC stock is calculated at the county scale by multiplying the mean SOC density value of each soil type in a county by its corresponding area. For the mean or median method, SOC density value of each soil type is calculated using provincial arithmetic mean or median. For the PKB method, SOC density value of each soil type is calculated at the county scale considering soil parent materials and spatial locations of all soil profiles. A newly constructed 1∶50,000 soil survey geographic database of Zhejiang Province, China, was used for evaluation. Results indicated that with soil classification levels up-scaling from Soil Species to Soil Group, the variation of estimated SOC stocks among different soil classification levels was obviously lower than that among different methods. The difference in the estimated SOC stocks among the four methods was lowest at the Soil Species level. The differences in SOC stocks among the mean, median, and PKB methods for different Soil Groups resulted from the differences in the procedure of aggregating soil profile properties to represent the attributes of one soil type. Compared with the other three estimation methods (i.e., the SPS, mean and median methods), the PKB method holds significant promise for characterizing spatial differences in SOC distribution because spatial locations of all soil profiles are considered during the aggregation procedure.

  3. Validating a nondestructive optical method for apportioning colored particulate matter into black carbon and additional components

    PubMed Central

    Yan, Beizhan; Kennedy, Daniel; Miller, Rachel L.; Cowin, James P.; Jung, Kyung-hwa; Perzanowski, Matt; Balletta, Marco; Perera, Federica P.; Kinney, Patrick L.; Chillrud, Steven N.

    2011-01-01

    Exposure of black carbon (BC) is associated with a variety of adverse health outcomes. A number of optical methods for estimating BC on Teflon filters have been adopted but most assume all light absorption is due to BC while other sources of colored particulate matter exist. Recently, a four-wavelength-optical reflectance measurement for distinguishing second hand cigarette smoke (SHS) from soot-BC was developed (Brook et al., 2010; Lawless et al., 2004). However, the method has not been validated for soot-BC nor SHS and little work has been done to look at the methodological issues of the optical reflectance measurements for samples that could have SHS, BC, and other colored particles. We refined this method using a lab-modified integrating sphere with absorption measured continuously from 350 nm to 1000 nm. Furthermore, we characterized the absorption spectrum of additional components of particulate matter (PM) on PM2.5 filters including ammonium sulfate, hematite, goethite, and magnetite. Finally, we validate this method for BC by comparison to other standard methods. Use of synthesized data indicates that it is important to optimize the choice of wavelengths to minimize computational errors as additional components (more than 2) are added to the apportionment model of colored components. We found that substantial errors are introduced when using 4 wavelengths suggested by Lawless et al. to quantify four substances, while an optimized choice of wavelengths can reduce model-derived error from over 10% to less than 2%. For environmental samples, the method was sensitive for estimating airborne levels of BC and SHS, but not mass loadings of iron oxides and sulfate. Duplicate samples collected in NYC show high reproducibility (points consistent with a 1:1 line, R2 = 0.95). BC data measured by this method were consistent with those measured by other optical methods, including Aethalometer and Smoke-stain Reflectometer (SSR); although the SSR looses sensitivity at

  4. Validating a nondestructive optical method for apportioning colored particulate matter into black carbon and additional components.

    PubMed

    Yan, Beizhan; Kennedy, Daniel; Miller, Rachel L; Cowin, James P; Jung, Kyung-Hwa; Perzanowski, Matt; Balletta, Marco; Perera, Federica P; Kinney, Patrick L; Chillrud, Steven N

    2011-12-01

    Exposure of black carbon (BC) is associated with a variety of adverse health outcomes. A number of optical methods for estimating BC on Teflon filters have been adopted but most assume all light absorption is due to BC while other sources of colored particulate matter exist. Recently, a four-wavelength-optical reflectance measurement for distinguishing second hand cigarette smoke (SHS) from soot-BC was developed (Brook et al., 2010; Lawless et al., 2004). However, the method has not been validated for soot-BC nor SHS and little work has been done to look at the methodological issues of the optical reflectance measurements for samples that could have SHS, BC, and other colored particles. We refined this method using a lab-modified integrating sphere with absorption measured continuously from 350 nm to 1000 nm. Furthermore, we characterized the absorption spectrum of additional components of particulate matter (PM) on PM(2.5) filters including ammonium sulfate, hematite, goethite, and magnetite. Finally, we validate this method for BC by comparison to other standard methods. Use of synthesized data indicates that it is important to optimize the choice of wavelengths to minimize computational errors as additional components (more than 2) are added to the apportionment model of colored components. We found that substantial errors are introduced when using 4 wavelengths suggested by Lawless et al. to quantify four substances, while an optimized choice of wavelengths can reduce model-derived error from over 10% to less than 2%. For environmental samples, the method was sensitive for estimating airborne levels of BC and SHS, but not mass loadings of iron oxides and sulfate. Duplicate samples collected in NYC show high reproducibility (points consistent with a 1:1 line, R(2) = 0.95). BC data measured by this method were consistent with those measured by other optical methods, including Aethalometer and Smoke-stain Reflectometer (SSR); although the SSR looses sensitivity at

  5. Validating a nondestructive optical method for apportioning colored particulate matter into black carbon and additional components

    NASA Astrophysics Data System (ADS)

    Yan, Beizhan; Kennedy, Daniel; Miller, Rachel L.; Cowin, James P.; Jung, Kyung-hwa; Perzanowski, Matt; Balletta, Marco; Perera, Federica P.; Kinney, Patrick L.; Chillrud, Steven N.

    2011-12-01

    Exposure of black carbon (BC) is associated with a variety of adverse health outcomes. A number of optical methods for estimating BC on Teflon filters have been adopted but most assume all light absorption is due to BC while other sources of colored particulate matter exist. Recently, a four-wavelength-optical reflectance measurement for distinguishing second hand cigarette smoke (SHS) from soot-BC was developed (Brook et al., 2010; Lawless et al., 2004). However, the method has not been validated for soot-BC nor SHS and little work has been done to look at the methodological issues of the optical reflectance measurements for samples that could have SHS, BC, and other colored particles. We refined this method using a lab-modified integrating sphere with absorption measured continuously from 350 nm to 1000 nm. Furthermore, we characterized the absorption spectrum of additional components of particulate matter (PM) on PM 2.5 filters including ammonium sulfate, hematite, goethite, and magnetite. Finally, we validate this method for BC by comparison to other standard methods. Use of synthesized data indicates that it is important to optimize the choice of wavelengths to minimize computational errors as additional components (more than 2) are added to the apportionment model of colored components. We found that substantial errors are introduced when using 4 wavelengths suggested by Lawless et al. to quantify four substances, while an optimized choice of wavelengths can reduce model-derived error from over 10% to less than 2%. For environmental samples, the method was sensitive for estimating airborne levels of BC and SHS, but not mass loadings of iron oxides and sulfate. Duplicate samples collected in NYC show high reproducibility (points consistent with a 1:1 line, R2 = 0.95). BC data measured by this method were consistent with those measured by other optical methods, including Aethalometer and Smoke-stain Reflectometer (SSR); although the SSR looses sensitivity at

  6. A comparison of dynamical and statistical downscaling methods for regional wave climate projections along French coastlines.

    NASA Astrophysics Data System (ADS)

    Laugel, Amélie; Menendez, Melisa; Benoit, Michel; Mattarolo, Giovanni; Mendez, Fernando

    2013-04-01

    Wave climate forecasting is a major issue for numerous marine and coastal related activities, such as offshore industries, flooding risks assessment and wave energy resource evaluation, among others. Generally, there are two main ways to predict the impacts of the climate change on the wave climate at regional scale: the dynamical and the statistical downscaling of GCM (Global Climate Model). In this study, both methods have been applied on the French coast (Atlantic , English Channel and North Sea shoreline) under three climate change scenarios (A1B, A2, B1) simulated with the GCM ARPEGE-CLIMAT, from Météo-France (AR4, IPCC). The aim of the work is to characterise the wave climatology of the 21st century and compare the statistical and dynamical methods pointing out advantages and disadvantages of each approach. The statistical downscaling method proposed by the Environmental Hydraulics Institute of Cantabria (Spain) has been applied (Menendez et al., 2011). At a particular location, the sea-state climate (Predictand Y) is defined as a function, Y=f(X), of several atmospheric circulation patterns (Predictor X). Assuming these climate associations between predictor and predictand are stationary, the statistical approach has been used to project the future wave conditions with reference to the GCM. The statistical relations between predictor and predictand have been established over 31 years, from 1979 to 2009. The predictor is built as the 3-days-averaged squared sea level pressure gradient from the hourly CFSR database (Climate Forecast System Reanalysis, http://cfs.ncep.noaa.gov/cfsr/). The predictand has been extracted from the 31-years hindcast sea-state database ANEMOC-2 performed with the 3G spectral wave model TOMAWAC (Benoit et al., 1996), developed at EDF R&D LNHE and Saint-Venant Laboratory for Hydraulics and forced by the CFSR 10m wind field. Significant wave height, peak period and mean wave direction have been extracted with an hourly-resolution at

  7. A method of analyzing nonstationary ionic channel current fluctuations in the presence of an additive measurement noise.

    PubMed

    Mino, H

    1993-03-01

    A method of estimating the parameters of nonstationary ionic channel current fluctuations (NST-ICF's) in the presence of an additive measurement noise is proposed. The case is considered in which the sample records of NST-ICT's corrupted by the measurement noise are available for estimation, where the experiment can be repeated many times to calculate the statistics of noisy NST-ICF's. The conventional second-order regression model expressed in terms of the mean and variance of noisy NST-ICF's is derived theoretically, assuming that NST-ICF's are binomially distributed. Since the coefficients of the regression model are explicitly related to not only the parameters of NST-ICF's but also the measurement noise component, the parameters of NST-ICF's that are of interest can be estimated without interference from the additive measurement noise by identifying the regression coefficients. Furthermore, the accuracy of the parameter estimates is theoretically evaluated using the error-covariance matrix of the regression coefficients. The validity and effectiveness of the proposed method are demonstrated in a Monte Carlo simulation in which a fundamental kinetic scheme of Na+ channels is treated as a specific example.

  8. Performance analysis of Wald-statistic based network detection methods for radiation sources

    SciTech Connect

    Sen, Satyabrata; Rao, Nageswara S; Wu, Qishi; Barry, M. L..; Grieme, M.; Brooks, Richard R; Cordone, G.

    2016-01-01

    There have been increasingly large deployments of radiation detection networks that require computationally fast algorithms to produce prompt results over ad-hoc sub-networks of mobile devices, such as smart-phones. These algorithms are in sharp contrast to complex network algorithms that necessitate all measurements to be sent to powerful central servers. In this work, at individual sensors, we employ Wald-statistic based detection algorithms which are computationally very fast, and are implemented as one of three Z-tests and four chi-square tests. At fusion center, we apply the K-out-of-N fusion to combine the sensors hard decisions. We characterize the performance of detection methods by deriving analytical expressions for the distributions of underlying test statistics, and by analyzing the fusion performances in terms of K, N, and the false-alarm rates of individual detectors. We experimentally validate our methods using measurements from indoor and outdoor characterization tests of the Intelligence Radiation Sensors Systems (IRSS) program. In particular, utilizing the outdoor measurements, we construct two important real-life scenarios, boundary surveillance and portal monitoring, and present the results of our algorithms.

  9. Monitoring, fault detection and operation prediction of MSW incinerators using multivariate statistical methods.

    PubMed

    Tavares, Gilberto; Zsigraiová, Zdena; Semiao, Viriato; Carvalho, Maria da Graca

    2011-07-01

    This work proposes the application of two multivariate statistical methods, principal component analysis (PCA) and partial least square (PLS), to a continuous process of a municipal solid waste (MSW) moving grate-type incinerator for process control--monitoring, fault detection and diagnosis--through the extraction of information from historical data. PCA model is built for process monitoring capable of detecting abnormal situations and the original 16-variable process dimension is reduced to eight, the first 4 being able to capture together 86% of the total process variation. PLS model is constructed to predict the generated superheated steam flow rate allowing for control of its set points. The model retained six of the original 13 variables, explaining together 90% of the input variation and almost 98% of the output variation. The proposed methodology is demonstrated by applying those multivariate statistical methods to process data continuously measured in an actual incinerator. Both models exhibited very good performance in fault detection and isolation. In predicting the generated superheated steam flow rate for its set point control the PLS model performed very well with low prediction errors (RMSE of 3.1 and 4.1).

  10. Statistical Downscaling for Rainfall Forecasts Using Modified Constructed Analog Method in Thailand

    PubMed Central

    Anuchaivong, Patchalai; Sukawat, Dusadee

    2017-01-01

    The simulations of rainfall from historical data were created in this study by using statistical downscaling. Statistical downscaling techniques are based on a relationship between the variables that are solved by the General Circulation Models (GCMs) and the observed predictions. The Modified Constructed Analog Method (MCAM) is a technique in downscaling estimation, suitable for rainfall simulation accuracy using weather forecasting. In this research, the MCAM was used to calculate the Euclidean distance to obtain the number of analog days. Afterwards, a linear combination of 30 analog days is created with simulated rainfall data which are determined by the corresponding 5 days from the adjusted weights of the appropriate forecast day. This method is used to forecast the daily rainfall and was received from the Thai Meteorological Department (TMD) from the period during 1979 to 2010 at thirty stations. The experiment involved the use of rainfall forecast data that was combined with the historical data during the rainy season in 2010. The result showed that the MCAM gave the correlation value of 0.8 resulting in a reduced percentage error of 13.66%. The MCAM gave the value of 1094.10 mm which was the closest value to the observed precipitation of 1119.53 mm. PMID:28317010

  11. Methods for estimating selected low-flow frequency statistics for unregulated streams in Kentucky

    USGS Publications Warehouse

    Martin, Gary R.; Arihood, Leslie D.

    2010-01-01

    This report provides estimates of, and presents methods for estimating, selected low-flow frequency statistics for unregulated streams in Kentucky including the 30-day mean low flows for recurrence intervals of 2 and 5 years (30Q2 and 30Q5) and the 7-day mean low flows for recurrence intervals of 5, 10, and 20 years (7Q2, 7Q10, and 7Q20). Estimates of these statistics are provided for 121 U.S. Geological Survey streamflow-gaging stations with data through the 2006 climate year, which is the 12-month period ending March 31 of each year. Data were screened to identify the periods of homogeneous, unregulated flows for use in the analyses. Logistic-regression equations are presented for estimating the annual probability of the selected low-flow frequency statistics being equal to zero. Weighted-least-squares regression equations were developed for estimating the magnitude of the nonzero 30Q2, 30Q5, 7Q2, 7Q10, and 7Q20 low flows. Three low-flow regions were defined for estimating the 7-day low-flow frequency statistics. The explicit explanatory variables in the regression equations include total drainage area and the mapped streamflow-variability index measured from a revised statewide coverage of this characteristic. The percentage of the station low-flow statistics correctly classified as zero or nonzero by use of the logistic-regression equations ranged from 87.5 to 93.8 percent. The average standard errors of prediction of the weighted-least-squares regression equations ranged from 108 to 226 percent. The 30Q2 regression equations have the smallest standard errors of prediction, and the 7Q20 regression equations have the largest standard errors of prediction. The regression equations are applicable only to stream sites with low flows unaffected by regulation from reservoirs and local diversions of flow and to drainage basins in specified ranges of basin characteristics. Caution is advised when applying the equations for basins with characteristics near the

  12. A Preferable Method for the Formation of Vesicles from Lamellar Liquid Crystals Using Chemical Additives.

    PubMed

    Enomoto, Yasutaka; Imai, Yoko; Tajima, Kazuo

    2017-01-01

    We present a method for vesicle formation from lamellar liquid crystals (LCs) using a cationic amphiphilic substance, namely 2-hydroxyethyl di(alkanol)oxyethyl methylammonium methylsulfate (DEAE). Vesicle formation from the DEAE lamellar dispersion occurred via a two-step chemical addition. This method required neither additional mechanical energy nor the use of special solvents. The transition was solubilized using an organic substance (e.g., limonene) in the lamellar DEAE LC, after which, a small amount of inorganic salt was added to the solubilized lamellar LC dispersion with gentle stirring. The viscosity of the DEAE dispersion following salt addition decreased sharply from 10(5) mPa·s to 10(2) mPa·s, and the DEAE dispersion was converted into a high fluidity liquid. Several organic substances were examined as potential solubilizates to initiate the lamellar-vesicle transition. Inorganic salts were also examined as transition triggers using various types of electrolytes; only neutral salts were effective as trigger additives. Dissociation of inorganic salts yielded anions, which inserted between the DEAE bilayer membranes and induced OH(-) ion exchange. In addition, a number of cations simultaneously formed ion pairs with the DEAE counter ions (CH3SO4(-) ions). However, as the amount of solubilized organic substances in the DEAE bilayer membrane decreased over time, the vesicles were transformed into lamellar LCs once again. The DEAE states in each step were measured by monitoring the zeta potential, pH, viscosity, and by examination of scanning electron microscopy and atomic force microscopy images. A possible molecular mechanism for the lamellar-vesicle transition of DEAE was proposed.

  13. Comparison of simple additive weighting (SAW) and composite performance index (CPI) methods in employee remuneration determination

    NASA Astrophysics Data System (ADS)

    Karlitasari, L.; Suhartini, D.; Benny

    2017-01-01

    The process of determining the employee remuneration for PT Sepatu Mas Idaman currently are still using Microsoft Excel-based spreadsheet where in the spreadsheet there is the value of criterias that must be calculated for every employee. This can give the effect of doubt during the assesment process, therefore resulting in the process to take much longer time. The process of employee remuneration determination is conducted by the assesment team based on some criterias that have been predetermined. The criteria used in the assessment process are namely the ability to work, human relations, job responsibility, discipline, creativity, work, achievement of targets, and absence. To ease the determination of employee remuneration to be more efficient and effective, the Simple Additive Weighting (SAW) method is used. SAW method can help in decision making for a certain case, and the calculation that generates the greatest value will be chosen as the best alternative. Other than SAW, also by using another method was the CPI method which is one of the calculating method in decision making based on performance index. Where SAW method was more faster by 89-93% compared to CPI method. Therefore it is expected that this application can be an evaluation material for the need of training and development for employee performances to be more optimal.

  14. Spatial temporal clustering for hotspot using kulldorff scan statistic method (KSS): A case in Riau Province

    NASA Astrophysics Data System (ADS)

    Hudjimartsu, S. A.; Djatna, T.; Ambarwari, A.; Apriliantono

    2017-01-01

    The forest fires in Indonesia occurs frequently in the dry season. Almost all the causes of forest fires are caused by the human activity itself. The impact of forest fires is the loss of biodiversity, pollution hazard and harm the economy of surrounding communities. To prevent fires required the method, one of them with spatial temporal clustering. Spatial temporal clustering formed grouping data so that the results of these groupings can be used as initial information on fire prevention. To analyze the fires, used hotspot data as early indicator of fire spot. Hotspot data consists of spatial and temporal dimensions can be processed using the Spatial Temporal Clustering with Kulldorff Scan Statistic (KSS). The result of this research is to the effectiveness of KSS method to cluster spatial hotspot in a case within Riau Province and produces two types of clusters, most cluster and secondary cluster. This cluster can be used as an early fire warning information.

  15. Lysine requirement of broiler chicks as affected by protein source and method of statistical evaluation.

    PubMed

    Barbour, G; Latshaw, J D; Bishop, B

    1993-09-01

    1. An experiment was designed to test if the lysine requirement, expressed as g lysine/kg CP, was the same for several protein sources. 2. Groundnut meal, groundnut meal adjusted with indispensable amino acids or sesame meal supplied the dietary CP at 180 g/kg diet. Increments of lysine (1.5 g/kg diet) were added to each of these diets. 3. The gain, food intake and food efficiency responses of broiler chicks were analysed using a quadratic equation and a two-slope method. An estimate of lysine requirements was also obtained from a survey of college students. 4. The different methods produced widely different estimates of lysine requirement. 5. The average lysine requirement was estimated at 50.1 g lysine/kg CP for groundnut meal, 61.7 for adjusted groundnut meal and 54.9 for sesame meal. 6. Reasons for the effect of statistical analysis and protein source on lysine requirement are discussed.

  16. Diagnosis of fault gearbox with wavelet packet decomposition and vector statistics method

    NASA Astrophysics Data System (ADS)

    Ren, Xueping; Shao, Wei; Ma, Wensheng

    2008-12-01

    Vibration signals from fault gearbox are usually complex with many different frequencies. As a result, it is difficult to find early symptoms of a potential fault in a gearbox. WPD (Wavelet Packet Decomposition) have been established as the most wide spread tool to disclose transient information in signals and wavelet packet filter is found to be very effective in detection of symptoms from vibration signals of a gearbox with early fatigue tooth crack. The paper presents a method to decompose the fault vibration signals with WPD and analysis the decomposed vectors with statistic algorithm to diagnosis the gearbox fault. The method is considered to be effective with the aim of gearbox fault detection and diagnosis.

  17. Van der Waals interactions: Evaluations by use of a statistical mechanical method

    NASA Astrophysics Data System (ADS)

    Høye, Johan S.

    2011-10-01

    In this work the induced van der Waals interaction between a pair of neutral atoms or molecules is considered by use of a statistical mechanical method. With use of the Schrödinger equation this interaction can be obtained by standard quantum mechanical perturbation theory to second order. However, the latter is restricted to electrostatic interactions between dipole moments. So with radiating dipole-dipole interaction where retardation effects are important for large separations of the particles, other methods are needed, and the resulting induced interaction is the Casimir-Polder interaction usually obtained by field theory. It can also be evaluated, however, by a statistical mechanical method that utilizes the path integral representation. We here show explicitly by use of this method the equivalence of the Casimir-Polder interaction and the van der Waals interaction based upon the Schrödinger equation. The equivalence is to leading order for short separations where retardation effects can be neglected. In recent works [J. S. Høye, Physica A 389, 1380 (2010), 10.1016/j.physa.2009.12.003; Phys. Rev. E 81, 061114 (2010)], 10.1103/PhysRevE.81.061114, the Casimir-Polder or Casimir energy was added as a correction to calculations of systems like the electron clouds of molecules. The equivalence to van der Waals interactions indicates that the added Casimir energy will improve the accuracy of calculated molecular energies. Thus, we give numerical estimates of this energy including analysis and estimates for the uniform electron gas.

  18. Effect of the chlortetracycline addition method on methane production from the anaerobic digestion of swine wastewater.

    PubMed

    Huang, Lu; Wen, Xin; Wang, Yan; Zou, Yongde; Ma, Baohua; Liao, Xindi; Liang, Juanboo; Wu, Yinbao

    2014-10-01

    Effects of antibiotic residues on methane production in anaerobic digestion are commonly studied using the following two antibiotic addition methods: (1) adding manure from animals that consume a diet containing antibiotics, and (2) adding antibiotic-free animal manure spiked with antibiotics. This study used chlortetracycline (CTC) as a model antibiotic to examine the effects of the antibiotic addition method on methane production in anaerobic digestion under two different swine wastewater concentrations (0.55 and 0.22mg CTC/g dry manure). The results showed that CTC degradation rate in which manure was directly added at 0.55mg CTC/g (HSPIKE treatment) was lower than the control values and the rest of the treatment groups. Methane production from the HSPIKE treatment was reduced (p<0.05) by 12% during the whole experimental period and 15% during the first 7days. The treatments had no significant effect on the pH and chemical oxygen demand value of the digesters, and the total nitrogen of the 0.55mg CTC/kg manure collected from mediated swine was significantly higher than the other values. Therefore, different methane production under different antibiotic addition methods might be explained by the microbial activity and the concentrations of antibiotic intermediate products and metabolites. Because the primary entry route of veterinary antibiotics into an anaerobic digester is by contaminated animal manure, the most appropriate method for studying antibiotic residue effects on methane production may be using manure from animals that are given a particular antibiotic, rather than adding the antibiotic directly to the anaerobic digester.

  19. The methods of receiving coal water suspension and its use as the modifying additive in concrete

    NASA Astrophysics Data System (ADS)

    Buyantuyev, S. L.; Urkhanova, L. A.; Lkhasaranov, S. A.; Stebenkova, Y. Y.; Khmelev, A. B.; Kondratenko, A. S.

    2017-01-01

    Results of research of the coal water suspension (CWS) from a cake received in the electrodigit ways in the fluid environment and gas are given in article and also the possibilities of its use as the modifying additive in concrete are considered. Use of a coal cake is perspective as it is a withdrawal of the coal and concentrating enterprises and has extremely low cost. Methods of receiving CWS and possibility of formation of carbon nanomaterials (CNM) are given in their structure. Research and the analysis of a microstructure of a surface of exemplars before electrodigit processing, their element structure, dependence of durability of a cement stone on a look and quantity of an additive of CWS is conducted. For modification of cement the carbon nanomaterials received from the following exemplars of water coal suspensions were used: foams from a cake from a scrubber of the plasma modular reactor, coal water suspension from a cake from electrodigit installation. The product which can find further application for a power engineering as fuel for combustion, and also in structural materials science, in particular, as the modifying additive in concrete allows to receive these methods.

  20. PREFACE: Advanced many-body and statistical methods in mesoscopic systems

    NASA Astrophysics Data System (ADS)

    Anghel, Dragos Victor; Sabin Delion, Doru; Sorin Paraoanu, Gheorghe

    2012-02-01

    It has increasingly been realized in recent times that the borders separating various subfields of physics are largely artificial. This is the case for nanoscale physics, physics of lower-dimensional systems and nuclear physics, where the advanced techniques of many-body theory developed in recent times could provide a unifying framework for these disciplines under the general name of mesoscopic physics. Other fields, such as quantum optics and quantum information, are increasingly using related methods. The 6-day conference 'Advanced many-body and statistical methods in mesoscopic systems' that took place in Constanta, Romania, between 27 June and 2 July 2011 was, we believe, a successful attempt at bridging an impressive list of topical research areas: foundations of quantum physics, equilibrium and non-equilibrium quantum statistics/fractional statistics, quantum transport, phases and phase transitions in mesoscopic systems/superfluidity and superconductivity, quantum electromechanical systems, quantum dissipation, dephasing, noise and decoherence, quantum information, spin systems and their dynamics, fundamental symmetries in mesoscopic systems, phase transitions, exactly solvable methods for mesoscopic systems, various extension of the random phase approximation, open quantum systems, clustering, decay and fission modes and systematic versus random behaviour of nuclear spectra. This event brought together participants from seventeen countries and five continents. Each of the participants brought considerable expertise in his/her field of research and, at the same time, was exposed to the newest results and methods coming from the other, seemingly remote, disciplines. The talks touched on subjects that are at the forefront of topical research areas and we hope that the resulting cross-fertilization of ideas will lead to new, interesting results from which everybody will benefit. We are grateful for the financial and organizational support from IFIN-HH, Ovidius

  1. Statistical methods for the analysis of a screening test for chronic beryllium disease

    SciTech Connect

    Frome, E.L.; Neubert, R.L.; Smith, M.H.; Littlefield, L.G.; Colyer, S.P.

    1994-10-01

    The lymphocyte proliferation test (LPT) is a noninvasive screening procedure used to identify persons who may have chronic beryllium disease. A practical problem in the analysis of LPT well counts is the occurrence of outlying data values (approximately 7% of the time). A log-linear regression model is used to describe the expected well counts for each set of test conditions. The variance of the well counts is proportional to the square of the expected counts, and two resistant regression methods are used to estimate the parameters of interest. The first approach uses least absolute values (LAV) on the log of the well counts to estimate beryllium stimulation indices (SIs) and the coefficient of variation. The second approach uses a resistant regression version of maximum quasi-likelihood estimation. A major advantage of the resistant regression methods is that it is not necessary to identify and delete outliers. These two new methods for the statistical analysis of the LPT data and the outlier rejection method that is currently being used are applied to 173 LPT assays. The authors strongly recommend the LAV method for routine analysis of the LPT.

  2. Statistical Classification of Soft Solder Alloys by Laser-Induced Breakdown Spectroscopy: Review of Methods

    NASA Astrophysics Data System (ADS)

    Zdunek, R.; Nowak, M.; Pliński, E.

    2016-02-01

    This paper reviews machine-learning methods that are nowadays the most frequently used for the supervised classification of spectral signals in laser-induced breakdown spectroscopy (LIBS). We analyze and compare various statistical classification methods, such as linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), partial least-squares discriminant analysis (PLS-DA), soft independent modeling of class analogy (SIMCA), support vector machine (SVM), naive Bayes method, probabilistic neural networks (PNN), and K-nearest neighbor (KNN) method. The theoretical considerations are supported with experiments conducted for real soft-solder-alloy spectra obtained using LIBS. We consider two decision problems: binary and multiclass classification. The former is used to distinguish overheated soft solders from their normal versions. The latter aims to assign a testing sample to a given group of materials. The measurements are obtained for several laser-energy values, projection masks, and numbers of laser shots. Using cross-validation, we evaluate the above classification methods in terms of their usefulness in solving both classification problems.

  3. Computer program for the calculation of grain size statistics by the method of moments

    USGS Publications Warehouse

    Sawyer, Michael B.

    1977-01-01

    A computer program is presented for a Hewlett-Packard Model 9830A desk-top calculator (1) which calculates statistics using weight or point count data from a grain-size analysis. The program uses the method of moments in contrast to the more commonly used but less inclusive graphic method of Folk and Ward (1957). The merits of the program are: (1) it is rapid; (2) it can accept data in either grouped or ungrouped format; (3) it allows direct comparison with grain-size data in the literature that have been calculated by the method of moments; (4) it utilizes all of the original data rather than percentiles from the cumulative curve as in the approximation technique used by the graphic method; (5) it is written in the computer language BASIC, which is easily modified and adapted to a wide variety of computers; and (6) when used in the HP-9830A, it does not require punching of data cards. The method of moments should be used only if the entire sample has been measured and the worker defines the measured grain-size range. (1) Use of brand names in this paper does not imply endorsement of these products by the U.S. Geological Survey.

  4. [Concentration retrieving method of SO2 using differential optical absorption spectroscopy based on statistics].

    PubMed

    Liu, Bin; Sun, Chang-Ku; Zhang, Chi; Zhao, Yu-Mei; Liu, Jun-Ping

    2011-01-01

    A concentration retrieving method using statistics is presented, which is applied in differential optical absorption spectroscopy (DOAS) for measuring the concentration of SO2. The method uses the standard deviation of the differential absorption to represents the gas concentration. Principle component analysis (PCA) method is used to process the differential absorption spectrum. In the method, the basis data for the concentration retrieval of SO2 is the combination of the PCA processing result, the correlation coefficient, and the standard deviation of the differential absorption. The method is applied to a continuous emission monitoring system (CEMS) with optical path length of 0.3 m. Its measuring range for SO2 concentration is 0-5 800 mg x m(-3). The nonlinear calibration and the temperature compensation for the system were executed. The full scale error of the retrieving concentration is less than 0.7% FS. And the measuring result is -4.54 mg x m(-3) when the concentration of SO2 is zero.

  5. The Wavelet Element Method. Part 2; Realization and Additional Features in 2D and 3D

    NASA Technical Reports Server (NTRS)

    Canuto, Claudio; Tabacco, Anita; Urban, Karsten

    1998-01-01

    The Wavelet Element Method (WEM) provides a construction of multiresolution systems and biorthogonal wavelets on fairly general domains. These are split into subdomains that are mapped to a single reference hypercube. Tensor products of scaling functions and wavelets defined on the unit interval are used on the reference domain. By introducing appropriate matching conditions across the interelement boundaries, a globally continuous biorthogonal wavelet basis on the general domain is obtained. This construction does not uniquely define the basis functions but rather leaves some freedom for fulfilling additional features. In this paper we detail the general construction principle of the WEM to the 1D, 2D and 3D cases. We address additional features such as symmetry, vanishing moments and minimal support of the wavelet functions in each particular dimension. The construction is illustrated by using biorthogonal spline wavelets on the interval.

  6. Standard addition method for laser ablation ICPMS using a spinning platform.

    PubMed

    Claverie, Fanny; Malherbe, Julien; Bier, Naomi; Molloy, John L; Long, Stephen E

    2013-04-02

    A method has been developed for the fast and easy determination of Pb, Sr, Ba, Ni, Cu, and Zn, which are of geological and environmental interest, in solid samples by laser ablation inductively coupled plasma mass spectrometry (LA-ICPMS) using a spinning sample platform. The platform, containing a sample and a standard, is spun during the ablation, allowing the quasi-simultaneous ablation of both materials. The aerosols resulting from the ablation of sample and standard were mixed in the ablation cell allowing quantification of analytes by standard additions. The proportion of standard versus sample of the mixing can be increased by performing the ablation further from the axis of rotation. The ablated masses have been determined using a new strategy based on isotope dilution analysis. This spinning laser ablation method has been applied to the Allende meteorite and four powdered standard reference materials (SRMs) fused in lithium borate glasses: two sediments as well as a soil and a rock material. SRM 612 (Trace Elements in Glass) was also analyzed despite having a matrix slightly different from the glass standard obtained by lithium borate fusion. The deviation from the certified values was found to be less than 15% for most of the mass fractions for all the elements and samples studied, with an average precision of 10%. These results demonstrate the validity of the proposed method for the direct and fast analysis of solid samples of different matrixes by standard additions, using a single standard sample.

  7. A network-based method to assess the statistical significance of mild co-regulation effects.

    PubMed

    Horvát, Emőke-Ágnes; Zhang, Jitao David; Uhlmann, Stefan; Sahin, Özgür; Zweig, Katharina Anna

    2013-01-01

    Recent development of high-throughput, multiplexing technology has initiated projects that systematically investigate interactions between two types of components in biological networks, for instance transcription factors and promoter sequences, or microRNAs (miRNAs) and mRNAs. In terms of network biology, such screening approaches primarily attempt to elucidate relations between biological components of two distinct types, which can be represented as edges between nodes in a bipartite graph. However, it is often desirable not only to determine regulatory relationships between nodes of different types, but also to understand the connection patterns of nodes of the same type. Especially interesting is the co-occurrence of two nodes of the same type, i.e., the number of their common neighbours, which current high-throughput screening analysis fails to address. The co-occurrence gives the number of circumstances under which both of the biological components are influenced in the same way. Here we present SICORE, a novel network-based method to detect pairs of nodes with a statistically significant co-occurrence. We first show the stability of the proposed method on artificial data sets: when randomly adding and deleting observations we obtain reliable results even with noise exceeding the expected level in large-scale experiments. Subsequently, we illustrate the viability of the method based on the analysis of a proteomic screening data set to reveal regulatory patterns of human microRNAs targeting proteins in the EGFR-driven cell cycle signalling system. Since statistically significant co-occurrence may indicate functional synergy and the mechanisms underlying canalization, and thus hold promise in drug target identification and therapeutic development, we provide a platform-independent implementation of SICORE with a graphical user interface as a novel tool in the arsenal of high-throughput screening analysis.

  8. Effect of different oxytetracycline addition methods on its degradation behavior in soil.

    PubMed

    Chen, Gui-Xiu; He, Wei-Wei; Wang, Yan; Zou, Yong-De; Liang, Juan-Boo; Liao, Xin-Di; Wu, Yin-Bao

    2014-05-01

    The degradation behavior of veterinary antibiotics in soil is commonly studied using the following methods of adding antibiotics to the soil: (i) adding manure collected from animals fed with a diet containing antibiotics, (ii) adding antibiotic-free animal manure spiked with antibiotics and (iii) directly adding antibiotics. No research simultaneously comparing different antibiotic addition methods was found. Oxytetracycline (OTC) was used as a model antibiotic to compare the effect of the three commonly used antibiotic addition methods on OTC degradation behavior in soil. The three treatment methods have similar trends, though OTC degradation half-lives show the following significant differences (P<0.05): manure from swine fed OTC (treatment A)method to study the degradation and ecotoxicity of antibiotic residues in soil may be to use manure from animals that are given a particular antibiotic, rather than by adding it directly to the soil.

  9. Quantitative imaging biomarkers: a review of statistical methods for computer algorithm comparisons.

    PubMed

    Obuchowski, Nancy A; Reeves, Anthony P; Huang, Erich P; Wang, Xiao-Feng; Buckler, Andrew J; Kim, Hyun J Grace; Barnhart, Huiman X; Jackson, Edward F; Giger, Maryellen L; Pennello, Gene; Toledano, Alicia Y; Kalpathy-Cramer, Jayashree; Apanasovich, Tatiyana V; Kinahan, Paul E; Myers, Kyle J; Goldgof, Dmitry B; Barboriak, Daniel P; Gillies, Robert J; Schwartz, Lawrence H; Sullivan, Daniel C

    2015-02-01

    Quantitative biomarkers from medical images are becoming important tools for clinical diagnosis, staging, monitoring, treatment planning, and development of new therapies. While there is a rich history of the development of quantitative imaging biomarker (QIB) techniques, little attention has been paid to the validation and comparison of the computer algorithms that implement the QIB measurements. In this paper we provide a framework for QIB algorithm comparisons. We first review and compare various study designs, including designs with the true value (e.g. phantoms, digital reference images, and zero-change studies), designs with a reference standard (e.g. studies testing equivalence with a reference standard), and designs without a reference standard (e.g. agreement studies and studies of algorithm precision). The statistical methods for comparing QIB algorithms are then presented for various study types using both aggregate and disaggregate approaches. We propose a series of steps for establishing the performance of a QIB algorithm, identify limitations in the current statistical literature, and suggest future directions for research.

  10. Quantitative Imaging Biomarkers: A Review of Statistical Methods for Computer Algorithm Comparisons

    PubMed Central

    2014-01-01

    Quantitative biomarkers from medical images are becoming important tools for clinical diagnosis, staging, monitoring, treatment planning, and development of new therapies. While there is a rich history of the development of quantitative imaging biomarker (QIB) techniques, little attention has been paid to the validation and comparison of the computer algorithms that implement the QIB measurements. In this paper we provide a framework for QIB algorithm comparisons. We first review and compare various study designs, including designs with the true value (e.g. phantoms, digital reference images, and zero-change studies), designs with a reference standard (e.g. studies testing equivalence with a reference standard), and designs without a reference standard (e.g. agreement studies and studies of algorithm precision). The statistical methods for comparing QIB algorithms are then presented for various study types using both aggregate and disaggregate approaches. We propose a series of steps for establishing the performance of a QIB algorithm, identify limitations in the current statistical literature, and suggest future directions for research. PMID:24919829

  11. Comparison of methods for calculating conditional expectations of sufficient statistics for continuous time Markov chains

    PubMed Central

    2011-01-01

    Background Continuous time Markov chains (CTMCs) is a widely used model for describing the evolution of DNA sequences on the nucleotide, amino acid or codon level. The sufficient statistics for CTMCs are the time spent in a state and the number of changes between any two states. In applications past evolutionary events (exact times and types of changes) are unaccessible and the past must be inferred from DNA sequence data observed in the present. Results We describe and implement three algorithms for computing linear combinations of expected values of the sufficient statistics, conditioned on the end-points of the chain, and compare their performance with respect to accuracy and running time. The first algorithm is based on an eigenvalue decomposition of the rate matrix (EVD), the second on uniformization (UNI), and the third on integrals of matrix exponentials (EXPM). The implementation in R of the algorithms is available at http://www.birc.au.dk/~paula/. Conclusions We use two different models to analyze the accuracy and eight experiments to investigate the speed of the three algorithms. We find that they have similar accuracy and that EXPM is the slowest method. Furthermore we find that UNI is usually faster than EVD. PMID:22142146

  12. Improved Test Planning and Analysis Through the Use of Advanced Statistical Methods

    NASA Technical Reports Server (NTRS)

    Green, Lawrence L.; Maxwell, Katherine A.; Glass, David E.; Vaughn, Wallace L.; Barger, Weston; Cook, Mylan

    2016-01-01

    The goal of this work is, through computational simulations, to provide statistically-based evidence to convince the testing community that a distributed testing approach is superior to a clustered testing approach for most situations. For clustered testing, numerous, repeated test points are acquired at a limited number of test conditions. For distributed testing, only one or a few test points are requested at many different conditions. The statistical techniques of Analysis of Variance (ANOVA), Design of Experiments (DOE) and Response Surface Methods (RSM) are applied to enable distributed test planning, data analysis and test augmentation. The D-Optimal class of DOE is used to plan an optimally efficient single- and multi-factor test. The resulting simulated test data are analyzed via ANOVA and a parametric model is constructed using RSM. Finally, ANOVA can be used to plan a second round of testing to augment the existing data set with new data points. The use of these techniques is demonstrated through several illustrative examples. To date, many thousands of comparisons have been performed and the results strongly support the conclusion that the distributed testing approach outperforms the clustered testing approach.

  13. Statistical method for revealing form-function relations in biological networks

    PubMed Central

    Mugler, Andrew; Grinshpun, Boris; Franks, Riley

    2011-01-01

    Over the past decade, a number of researchers in systems biology have sought to relate the function of biological systems to their network-level descriptions—lists of the most important players and the pairwise interactions between them. Both for large networks (in which statistical analysis is often framed in terms of the abundance of repeated small subgraphs) and for small networks which can be analyzed in greater detail (or even synthesized in vivo and subjected to experiment), revealing the relationship between the topology of small subgraphs and their biological function has been a central goal. We here seek to pose this revelation as a statistical task, illustrated using a particular setup which has been constructed experimentally and for which parameterized models of transcriptional regulation have been studied extensively. The question “how does function follow form” is here mathematized by identifying which topological attributes correlate with the diverse possible information-processing tasks which a transcriptional regulatory network can realize. The resulting method reveals one form-function relationship which had earlier been predicted based on analytic results, and reveals a second for which we can provide an analytic interpretation. Resulting source code is distributed via http://formfunction.sourceforge.net. PMID:21183719

  14. A simple method for the addition of rotenone in Arabidopsis thaliana leaves

    PubMed Central

    Maliandi, María V; Rius, Sebastián P; Busi, María V; Gomez-Casati, Diego F

    2015-01-01

    A simple and reproducible method for the treatment of Arabidopsis thaliana leaves with rotenone is presented. Rosette leaves were incubated with rotenone and Triton X-100 for at least 15 h. Treated leaves showed increased expression of COX19 and BCS1a, 2 genes known to be induced in Arabidopsis cell cultures after rotenone treatment. Moreover, rotenone/Triton X-100 incubated leaves presented an inhibition of oxygen uptake. The simplicity of the procedure shows this methodology is useful for studying the effect of the addition of rotenone to a photosynthetic tissue in situ. PMID:26357865

  15. A simple method for the addition of rotenone in Arabidopsis thaliana leaves.

    PubMed

    Maliandi, María V; Rius, Sebastián P; Busi, María V; Gomez-Casati, Diego F

    2015-01-01

    A simple and reproducible method for the treatment of Arabidopsis thaliana leaves with rotenone is presented. Rosette leaves were incubated with rotenone and Triton X-100 for at least 15 h. Treated leaves showed increased expression of COX19 and BCS1a, 2 genes known to be induced in Arabidopsis cell cultures after rotenone treatment. Moreover, rotenone/Triton X-100 incubated leaves presented an inhibition of oxygen uptake. The simplicity of the procedure shows this methodology is useful for studying the effect of the addition of rotenone to a photosynthetic tissue in situ.

  16. A nonparametric statistical method for image segmentation using information theory and curve evolution.

    PubMed

    Kim, Junmo; Fisher, John W; Yezzi, Anthony; Cetin, Müjdat; Willsky, Alan S

    2005-10-01

    In this paper, we present a new information-theoretic approach to image segmentation. We cast the segmentation problem as the maximization of the mutual information between the region labels and the image pixel intensities, subject to a constraint on the total length of the region boundaries. We assume that the probability densities associated with the image pixel intensities within each region are completely unknown a priori, and we formulate the problem based on nonparametric density estimates. Due to the nonparametric structure, our method does not require the image regions to have a particular type of probability distribution and does not require the extraction and use of a particular statistic. We solve the information-theoretic optimization problem by deriving the associated gradient flows and applying curve evolution techniques. We use level-set methods to implement the resulting evolution. The experimental results based on both synthetic and real images demonstrate that the proposed technique can solve a variety of challenging image segmentation problems. Futhermore, our method, which does not require any training, performs as good as methods based on training.

  17. Computed statistics at streamgages, and methods for estimating low-flow frequency statistics and development of regional regression equations for estimating low-flow frequency statistics at ungaged locations in Missouri

    USGS Publications Warehouse

    Southard, Rodney E.

    2013-01-01

    The weather and precipitation patterns in Missouri vary considerably from year to year. In 2008, the statewide average rainfall was 57.34 inches and in 2012, the statewide average rainfall was 30.64 inches. This variability in precipitation and resulting streamflow in Missouri underlies the necessity for water managers and users to have reliable streamflow statistics and a means to compute select statistics at ungaged locations for a better understanding of water availability. Knowledge of surface-water availability is dependent on the streamflow data that have been collected and analyzed by the U.S. Geological Survey for more than 100 years at approximately 350 streamgages throughout Missouri. The U.S. Geological Survey, in cooperation with the Missouri Department of Natural Resources, computed streamflow statistics at streamgages through the 2010 water year, defined periods of drought and defined methods to estimate streamflow statistics at ungaged locations, and developed regional regression equations to compute selected streamflow statistics at ungaged locations. Streamflow statistics and flow durations were computed for 532 streamgages in Missouri and in neighboring States of Missouri. For streamgages with more than 10 years of record, Kendall’s tau was computed to evaluate for trends in streamflow data. If trends were detected, the variable length method was used to define the period of no trend. Water years were removed from the dataset from the beginning of the record for a streamgage until no trend was detected. Low-flow frequency statistics were then computed for the entire period of record and for the period of no trend if 10 or more years of record were available for each analysis. Three methods are presented for computing selected streamflow statistics at ungaged locations. The first method uses power curve equations developed for 28 selected streams in Missouri and neighboring States that have multiple streamgages on the same streams. Statistical

  18. Goodness-of-fit methods for additive-risk models in tumorigenicity experiments.

    PubMed

    Ghosh, Debashis

    2003-09-01

    In tumorigenicity experiments, a complication is that the time to event is generally not observed, so that the time to tumor is subject to interval censoring. One of the goals in these studies is to properly model the effect of dose on risk. Thus, it is important to have goodness of fit procedures available for assessing the model fit. While several estimation procedures have been developed for current-status data, relatively little work has been done on model-checking techniques. In this article, we propose numerical and graphical methods for the analysis of current-status data using the additive-risk model, primarily focusing on the situation where the monitoring times are dependent. The finite-sample properties of the proposed methodology are examined through numerical studies. The methods are then illustrated with data from a tumorigenicity experiment.

  19. Systems and Methods for Fabricating Objects Including Amorphous Metal Using Techniques Akin to Additive Manufacturing

    NASA Technical Reports Server (NTRS)

    Hofmann, Douglas (Inventor)

    2017-01-01

    Systems and methods in accordance with embodiments of the invention fabricate objects including amorphous metals using techniques akin to additive manufacturing. In one embodiment, a method of fabricating an object that includes an amorphous metal includes: applying a first layer of molten metallic alloy to a surface; cooling the first layer of molten metallic alloy such that it solidifies and thereby forms a first layer including amorphous metal; subsequently applying at least one layer of molten metallic alloy onto a layer including amorphous metal; cooling each subsequently applied layer of molten metallic alloy such that it solidifies and thereby forms a layer including amorphous metal prior to the application of any adjacent layer of molten metallic alloy; where the aggregate of the solidified layers including amorphous metal forms a desired shape in the object to be fabricated; and removing at least the first layer including amorphous metal from the surface.

  20. Evaluation of an Alternative Statistical Method for Analysis of RCRA Groundwater Monitoring Data at the Hanford Site

    SciTech Connect

    Chou, Charissa J.

    2004-06-24

    Statistical methods are required in groundwater monitoring programs to determine if a RCRA-regulated unit affects groundwater quality beneath a site. This report presents the results of the statistical analysis of groundwater monitoring data acquired at B Pond and the 300 Area process trenches during a 2-year trial test period.

  1. Understanding the Negative Graduate Student Perceptions of Required Statistics and Research Methods Courses: Implications for Programs and Faculty

    ERIC Educational Resources Information Center

    Coleman, Charles; Conrad, Cynthia

    2007-01-01

    The authors of this study endeavor to explore the negative opinions and perceptions of graduate students in business and social science programs, regarding their required statistics and research methods courses. The general sense of instructors of such courses is that students dread and resent having to take courses dealing with statistics and…

  2. Statistically Qualified Neuro-Analytic system and Method for Process Monitoring

    SciTech Connect

    Vilim, Richard B.; Garcia, Humberto E.; Chen, Frederick W.

    1998-11-04

    An apparatus and method for monitoring a process involves development and application of a statistically qualified neuro-analytic (SQNA) model to accurately and reliably identify process change. The development of the SQNA model is accomplished in two steps: deterministic model adaption and stochastic model adaptation. Deterministic model adaption involves formulating an analytic model of the process representing known process characteristics,augmenting the analytic model with a neural network that captures unknown process characteristics, and training the resulting neuro-analytic model by adjusting the neural network weights according to a unique scaled equation emor minimization technique. Stochastic model adaptation involves qualifying any remaining uncertainty in the trained neuro-analytic model by formulating a likelihood function, given an error propagation equation, for computing the probability that the neuro-analytic model generates measured process output. Preferably, the developed SQNA model is validated using known sequential probability ratio tests and applied to the process as an on-line monitoring system.

  3. Statistical methods for astronomical data with upper limits. II - Correlation and regression

    NASA Technical Reports Server (NTRS)

    Isobe, T.; Feigelson, E. D.; Nelson, P. I.

    1986-01-01

    Statistical methods for calculating correlations and regressions in bivariate censored data where the dependent variable can have upper or lower limits are presented. Cox's regression and the generalization of Kendall's rank correlation coefficient provide significant levels of correlations, and the EM algorithm, under the assumption of normally distributed errors, and its nonparametric analog using the Kaplan-Meier estimator, give estimates for the slope of a regression line. Monte Carlo simulations demonstrate that survival analysis is reliable in determining correlations between luminosities at different bands. Survival analysis is applied to CO emission in infrared galaxies, X-ray emission in radio galaxies, H-alpha emission in cooling cluster cores, and radio emission in Seyfert galaxies.

  4. Performance analysis of morphological component analysis (MCA) method for mammograms using some statistical features

    NASA Astrophysics Data System (ADS)

    Gardezi, Syed Jamal Safdar; Faye, Ibrahima; Kamel, Nidal; Eltoukhy, Mohamed Meselhy; Hussain, Muhammad

    2014-10-01

    Early detection of breast cancer helps reducing the mortality rates. Mammography is very useful tool in breast cancer detection. But it is very difficult to separate different morphological features in mammographic images. In this study, Morphological Component Analysis (MCA) method is used to extract different morphological aspects of mammographic images by effectively preserving the morphological characteristics of regions. MCA decomposes the mammogram into piecewise smooth part and the texture part using the Local Discrete Cosine Transform (LDCT) and Curvelet Transform via wrapping (CURVwrap). In this study, simple comparison in performance has been done using some statistical features for the original image versus the piecewise smooth part obtained from the MCA decomposition. The results show that MCA suppresses the structural noises and blood vessels from the mammogram and enhances the performance for mass detection.

  5. Investigating Statistical Downscaling Methods and Applications for the NCEP/GEFS Ensemble Precipitation Forecasts

    NASA Astrophysics Data System (ADS)

    Luo, Y.; Zhu, Y.; Hou, D.

    2015-12-01

    Significant discrepancies exist when coarse resolution model precipitation forecast products on standard output grids are verified against high-resolution analyses, remaining a challenge for NWP model guidance products. To enhance the usefulness of the model products, tremendous efforts with various statistical post-processing techniques are being made to reduce those discrepancies and recover small scale features using observations and a long-term reforecast climatology as the baseline. Among them, downscaling ensemble using forecast analogs (Hamill et al., 2006) and multiplicative downscaling using Parameter-elevation Regressions on Independent Slopes Model (PRISM) Mountain Mapper by WPC show promising improvement in skill of forecasts. This work concentrates on these two commonly used statistical downscaling approaches along with the Frequency Matching Method (FMM, Zhu and Luo, 2015) developed at NCEP/EMC. In this work, these three approaches will be investigated when applied to the standard one degree NCEP Global Ensemble Forecast System (GEFS) ensemble precipitation forecasts based on the 5-km high resolution NCEP Climatology-Calibrated Precipitation Analysis (CCPA) and 18 years ensemble control only reforecast data from the latest version of GEFS (GEFS v11.0). We will explore the effectiveness and feasibility of these approaches and to discover their strengths and weaknesses, with a focus mainly on generation of much higher 5km NDGD grid GEFS ensemble precipitation forecasts over the CONUS. This work is also expected to identify factors that influence the performance for each approach, such as the choice of case matching methods, the sample size, weighting function, regime definition, etc. A summary of the investigations and outcomes will be shown. Suggestions for some possible directions to produce such a high resolution ensemble precipitation forecast products in the future will be provided.

  6. Reporting of occupational and environmental research: use and misuse of statistical and epidemiological methods

    PubMed Central

    Rushton, L.

    2000-01-01

    OBJECTIVES—To report some of the most serious omissions and errors which may occur in papers submitted to Occupational and Environmental Medicine, and to give guidelines on the essential components that should be included in papers reporting results from studies of occupational and environmental health.
METHODS—Since 1994 Occupational and Environmental Medicine has used a panel of medical statisticians to review submitted papers which have a substantial statistical content. Although some studies may have genuine errors in their design, execution, and analysis, many of the problems identified during the reviewing process are due to inadequate and incomplete reporting of essential aspects of a study. This paper outlines some of the most important errors and omissions that may occur. Observational studies are often the preferred choice of design in occupational and environmental medicine. Some of the issues relating to design, execution, and analysis which should be considered when reporting three of the most common observational study designs, cross sectional, case-control, and cohort are described. An illustration of good reporting practice is given for each. Various mathematical modelling techniques are often used in the analysis of these studies, the reporting of which causes a major problem to some authors. Suggestions for the presentation of results from modelling are made.
CONCLUSIONS—There is increasing interest in the development and application of formal "good epidemiology practices". These not only consider issues of data quality, study design, and study conduct, but through their structured approach to the documentation of the study procedures, provide the potential for more rigorous reporting of the results in the scientific literature.


Keywords: research reporting; statistical methods; epidemiological methods PMID:10711263

  7. A Method for Simulating Correlated Non-Normal Systems of Statistical Equations.

    ERIC Educational Resources Information Center

    Headrick, Todd C.; Beasley, T. Mark

    Real world data often fail to meet the underlying assumptions of normal statistical theory. Many statistical procedures in the psychological and educational sciences involve models that may include a system of statistical equations with non-normal correlated variables (e.g., factor analysis, structural equation modeling, or other complex…

  8. Statistical downscaling of daily precipitation over Llobregat River Basin in Catalunya, Spain using analog method.

    NASA Astrophysics Data System (ADS)

    Ballinas, R.; Versini, P.-A.; Sempere, D.; Escaler, I.

    2009-04-01

    Since anthropogenic climate change has become an important issue, the need to provide regional climate change information has increased, both for impact assessment studies and policy making. A regional climate is determined by interactions at large, regional and local scales. The general circulation models (GCMs) are run at too coarse resolution to permit accurate description of these regional and local interactions. So far, they have been unable to provide consistent estimates of climate change on a local scale. Several regionalization techniques have been developed to bridge the gap between the large-scale information provided by GCMs and fine spatial scales required for regional and environmental impact studies. Statistical downscaling technique is based on the view that regional climate may be seen to be conditioned by two factors: large-scale climatic state and regional/local features. Local climate information is derived by first developing a statistical model which relates large-scale variables or ‘‘predictors'' for which GCMs are trustable to regional or local surface ‘‘predictands'' for which models are less skilful. The main advantage of these techniques is that they are computationally inexpensive, and can be applied to outputs from different GCM experiments. In dynamical downscaling methods, a regional climate model (RCM) uses GCM outputs as its initial and boundary conditions. A statistical downscaling procedure based on an analogue technique has been used to determine projections for future climate change in the Llobregat River Basin in Catalunya, Spain. Llobregat Basin is one of the most important of Catalonia because it provides a significant amount of water for numerous cities that make up including Barcelona. This work is part of the European project "Water Change" (included in the LIFE + Environment Policy and Governance program). It deals with Medium and long term water resources modelling as a tool for planning and global change

  9. Determination of free acid by standard addition method in potassium thiocyanate

    SciTech Connect

    Baumann, E W

    1982-06-01

    The free acid content of solutions containing hydrolyzable ions has been determined potentiometrically by a standard addition method. Two increments of acid are added to the sample in 1M potassium thiocyanate solution. The sample concentration is calculated by solution of three simultaneous Nernst equations. The method has been demonstrated for solutions containing Al/sup 3 +/, Cr/sup 3 +/, Fe/sup 3 +/, Hg/sup 2 +/, Ni/sup 2 +/, Th/sup 4 +/, or UO/sub 2//sup 2 +/ with a metal-to-acid ratio of < 2.5. The method is suitable for determination of 10 ..mu..moles acid in 10 mL total volume. The accuracy can be judged from the agreement of the Nernst slopes found in the presence and absence of hydrolyzable ions. The relative standard deviation is < 2.5%. The report includes a survey of experiments with thermometric, pH, and Gran plot titrations in a variety of complexants, from which the method was evolved. Also included is a literature survey of sixty references, a discussion of the basic measurements, and a complete analytical procedure.

  10. Statistical Comparison and Improvement of Methods for Combining Random and Harmonic Loads

    NASA Technical Reports Server (NTRS)

    Brown, Andrew M.; McGhee, David S.

    2004-01-01

    Structures in many environments experience both random and harmonic excitation. A variety of closed-form techniques has been used in the aerospace industry to combine the loads resulting from the two sources. The resulting combined loads are then used to design for both yield ultimate strength and high cycle fatigue capability. This paper examines the cumulative distribution function (CDF) percentiles obtained using each method by integrating the joint probability density function of the sine and random components. A new Microsoft Excel spreadsheet macro that links with the software program Mathematics is then used to calculate the combined value corresponding to any desired percentile along with a curve fit to this value. Another Excel macro is used to calculate the combination using a Monte Carlo simulation. Unlike the traditional techniques, these methods quantify the calculated load value with a Consistent percentile. Using either of the presented methods can be extremely valuable in probabilistic design, which requires a statistical characterization of the loading. Also, since the CDF at high probability levels is very flat, the design value is extremely sensitive to the predetermined percentile; therefore, applying the new techniques can lower the design loading substantially without losing any of the identified structural reliability.

  11. A Review of the Statistical and Quantitative Methods Used to Study Alcohol-Attributable Crime

    PubMed Central

    Fitterer, Jessica L.; Nelson, Trisalyn A.

    2015-01-01

    Modelling the relationship between alcohol consumption and crime generates new knowledge for crime prevention strategies. Advances in data, particularly data with spatial and temporal attributes, have led to a growing suite of applied methods for modelling. In support of alcohol and crime researchers we synthesized and critiqued existing methods of spatially and quantitatively modelling the effects of alcohol exposure on crime to aid method selection, and identify new opportunities for analysis strategies. We searched the alcohol-crime literature from 1950 to January 2014. Analyses that statistically evaluated or mapped the association between alcohol and crime were included. For modelling purposes, crime data were most often derived from generalized police reports, aggregated to large spatial units such as census tracts or postal codes, and standardized by residential population data. Sixty-eight of the 90 selected studies included geospatial data of which 48 used cross-sectional datasets. Regression was the prominent modelling choice (n = 78) though dependent on data many variations existed. There are opportunities to improve information for alcohol-attributable crime prevention by using alternative population data to standardize crime rates, sourcing crime information from non-traditional platforms (social media), increasing the number of panel studies, and conducting analysis at the local level (neighbourhood, block, or point). Due to the spatio-temporal advances in crime data, we expect a continued uptake of flexible Bayesian hierarchical modelling, a greater inclusion of spatial-temporal point pattern analysis, and shift toward prospective (forecast) modelling over small areas (e.g., blocks). PMID:26418016

  12. On Statistical Methods for Common Mean and Reference Confidence Intervals in Interlaboratory Comparisons for Temperature

    NASA Astrophysics Data System (ADS)

    Witkovský, Viktor; Wimmer, Gejza; Ďuriš, Stanislav

    2015-08-01

    We consider a problem of constructing the exact and/or approximate coverage intervals for the common mean of several independent distributions. In a metrological context, this problem is closely related to evaluation of the interlaboratory comparison experiments, and in particular, to determination of the reference value (estimate) of a measurand and its uncertainty, or alternatively, to determination of the coverage interval for a measurand at a given level of confidence, based on such comparison data. We present a brief overview of some specific statistical models, methods, and algorithms useful for determination of the common mean and its uncertainty, or alternatively, the proper interval estimator. We illustrate their applicability by a simple simulation study and also by example of interlaboratory comparisons for temperature. In particular, we shall consider methods based on (i) the heteroscedastic common mean fixed effect model, assuming negligible laboratory biases, (ii) the heteroscedastic common mean random effects model with common (unknown) distribution of the laboratory biases, and (iii) the heteroscedastic common mean random effects model with possibly different (known) distributions of the laboratory biases. Finally, we consider a method, recently suggested by Singh et al., for determination of the interval estimator for a common mean based on combining information from independent sources through confidence distributions.

  13. Influence of harvest method and period on olive oil composition: an NMR and statistical study.

    PubMed

    D'Imperio, Marco; Gobbino, Marco; Picanza, Antonio; Costanzo, Simona; Della Corte, Anna; Mannina, Luisa

    2010-10-27

    The influence of harvest period and harvest method on olive oil composition was investigated by nuclear magnetic resonance (NMR) spectroscopy and by some quality parameters such as free acidity, peroxide value, and UV spectrophotometric indices. This work focuses on two secondary factors (harvest period and harvest method) and investigated their interactions with primary (genetic and pedoclimatic) and secondary (agronomic practices and technological procedures) factors. To avoid misinterpretation, the general linear model analysis (GLM) was used to adjust the result obtained from the analysis of variance (ANOVA). In this way, the effect of the factor of interest was corrected for the effects of the other factors that might influence the variable under investigation. The weight of each factor was evaluated by the variance component analysis (VCA). Finally, multivariate statistical analyses, namely, principal component analysis (PCA) and linear discriminant analysis (LDA), were applied. Samples were grouped according to the harvest period and harvest method. Volatile compounds, that is, hexanal and trans-2-hexenal, as well as the sn-1,3-diglycerides and squalene, significantly decreased during the ripening. The relative value of the ΔK parameter and the hexanal amount were higher in the olive oils obtained from olives harvested by one type of hand-held machine (shaker), whereas the unsaturated fatty chains in the olive oils were higher when another type (comb) was used.

  14. Statistical analysis to assess automated level of suspicion scoring methods in breast ultrasound

    NASA Astrophysics Data System (ADS)

    Galperin, Michael

    2003-05-01

    A well-defined rule-based system has been developed for scoring 0-5 the Level of Suspicion (LOS) based on qualitative lexicon describing the ultrasound appearance of breast lesion. The purposes of the research are to asses and select one of the automated LOS scoring quantitative methods developed during preliminary studies in benign biopsies reduction. The study has used Computer Aided Imaging System (CAIS) to improve the uniformity and accuracy of applying the LOS scheme by automatically detecting, analyzing and comparing breast masses. The overall goal is to reduce biopsies on the masses with lower levels of suspicion, rather that increasing the accuracy of diagnosis of cancers (will require biopsy anyway). On complex cysts and fibroadenoma cases experienced radiologists were up to 50% less certain in true negatives than CAIS. Full correlation analysis was applied to determine which of the proposed LOS quantification methods serves CAIS accuracy the best. This paper presents current results of applying statistical analysis for automated LOS scoring quantification for breast masses with known biopsy results. It was found that First Order Ranking method yielded most the accurate results. The CAIS system (Image Companion, Data Companion software) is developed by Almen Laboratories and was used to achieve the results.

  15. Two-time Green's functions and spectral density method in nonextensive quantum statistical mechanics.

    PubMed

    Cavallo, A; Cosenza, F; De Cesare, L

    2008-05-01

    We extend the formalism of the thermodynamic two-time Green's functions to nonextensive quantum statistical mechanics. Working in the optimal Lagrangian multiplier representation, the q -spectral properties and the methods for a direct calculation of the two-time q Green's functions and the related q -spectral density ( q measures the nonextensivity degree) for two generic operators are presented in strict analogy with the extensive (q=1) counterpart. Some emphasis is devoted to the nonextensive version of the less known spectral density method whose effectiveness in exploring equilibrium and transport properties of a wide variety of systems has been well established in conventional classical and quantum many-body physics. To check how both the equations of motion and the spectral density methods work to study the q -induced nonextensivity effects in nontrivial many-body problems, we focus on the equilibrium properties of a second-quantized model for a high-density Bose gas with strong attraction between particles for which exact results exist in extensive conditions. Remarkably, the contributions to several thermodynamic quantities of the q -induced nonextensivity close to the extensive regime are explicitly calculated in the low-temperature regime by overcoming the calculation of the q grand-partition function.

  16. Quantitative imaging biomarkers: a review of statistical methods for technical performance assessment.

    PubMed

    Raunig, David L; McShane, Lisa M; Pennello, Gene; Gatsonis, Constantine; Carson, Paul L; Voyvodic, James T; Wahl, Richard L; Kurland, Brenda F; Schwarz, Adam J; Gönen, Mithat; Zahlmann, Gudrun; Kondratovich, Marina V; O'Donnell, Kevin; Petrick, Nicholas; Cole, Patricia E; Garra, Brian; Sullivan, Daniel C

    2015-02-01

    Technological developments and greater rigor in the quantitative measurement of biological features in medical images have given rise to an increased interest in using quantitative imaging biomarkers to measure changes in these features. Critical to the performance of a quantitative imaging biomarker in preclinical or clinical settings are three primary metrology areas of interest: measurement linearity and bias, repeatability, and the ability to consistently reproduce equivalent results when conditions change, as would be expected in any clinical trial. Unfortunately, performance studies to date differ greatly in designs, analysis method, and metrics used to assess a quantitative imaging biomarker for clinical use. It is therefore difficult or not possible to integrate results from different studies or to use reported results to design studies. The Radiological Society of North America and the Quantitative Imaging Biomarker Alliance with technical, radiological, and statistical experts developed a set of technical performance analysis methods, metrics, and study designs that provide terminology, metrics, and methods consistent with widely accepted metrological standards. This document provides a consistent framework for the conduct and evaluation of quantitative imaging biomarker performance studies so that results from multiple studies can be compared, contrasted, or combined.

  17. A Review of the Statistical and Quantitative Methods Used to Study Alcohol-Attributable Crime.

    PubMed

    Fitterer, Jessica L; Nelson, Trisalyn A

    2015-01-01

    Modelling the relationship between alcohol consumption and crime generates new knowledge for crime prevention strategies. Advances in data, particularly data with spatial and temporal attributes, have led to a growing suite of applied methods for modelling. In support of alcohol and crime researchers we synthesized and critiqued existing methods of spatially and quantitatively modelling the effects of alcohol exposure on crime to aid method selection, and identify new opportunities for analysis strategies. We searched the alcohol-crime literature from 1950 to January 2014. Analyses that statistically evaluated or mapped the association between alcohol and crime were included. For modelling purposes, crime data were most often derived from generalized police reports, aggregated to large spatial units such as census tracts or postal codes, and standardized by residential population data. Sixty-eight of the 90 selected studies included geospatial data of which 48 used cross-sectional datasets. Regression was the prominent modelling choice (n = 78) though dependent on data many variations existed. There are opportunities to improve information for alcohol-attributable crime prevention by using alternative population data to standardize crime rates, sourcing crime information from non-traditional platforms (social media), increasing the number of panel studies, and conducting analysis at the local level (neighbourhood, block, or point). Due to the spatio-temporal advances in crime data, we expect a continued uptake of flexible Bayesian hierarchical modelling, a greater inclusion of spatial-temporal point pattern analysis, and shift toward prospective (forecast) modelling over small areas (e.g., blocks).

  18. An identification method for enclosed voids restriction in manufacturability design for additive manufacturing structures

    NASA Astrophysics Data System (ADS)

    Liu, Shutian; Li, Quhao; Chen, Wenjiong; Tong, Liyong; Cheng, Gengdong

    2015-06-01

    Additive manufacturing (AM) technologies, such as selective laser sintering (SLS) and fused deposition modeling (FDM), have become the powerful tools for direct manufacturing of complex parts. This breakthrough in manufacturing technology makes the fabrication of new geometrical features and multiple materials possible. Past researches on designs and design methods often focused on how to obtain desired functional performance of the structures or parts, specific manufacturing capabilities as well as manufacturing constraints of AM were neglected. However, the inherent constraints in AM processes should be taken into account in design process. In this paper, the enclosed voids, one type of manufacturing constraints of AM, are investigated. In mathematics, enclosed voids restriction expressed as the solid structure is simplyconnected. We propose an equivalent description of simply-connected constraint for avoiding enclosed voids in structures, named as virtual temperature method (VTM). In this method, suppose that the voids in structure are filled with a virtual heating material with high heat conductivity and solid areas are filled with another virtual material with low heat conductivity. Once the enclosed voids exist in structure, the maximum temperature value of structure will be very high. Based upon this method, the simplyconnected constraint is equivalent to maximum temperature constraint. And this method can be easily used to formulate the simply-connected constraint in topology optimization. The effectiveness of this description method is illustrated by several examples. Based upon topology optimization, an example of 3D cantilever beam is used to illustrate the trade-off between manufacturability and functionality. Moreover, the three optimized structures are fabricated by FDM technology to indicate further the necessity of considering the simply-connected constraint in design phase for AM.

  19. A comparison of statistical methods for the detection of hepatocellular carcinoma based on serum biomarkers and clinical variables

    PubMed Central

    2013-01-01

    Background Currently, a surgical approach is the best curative treatment for those with hepatocellular carcinoma (HCC). However, this requires HCC detection and removal of the lesion at an early stage. Unfortunately, most cases of HCC are detected at an advanced stage because of the lack of accurate biomarkers that can be used in the surveillance of those at risk. It is believed that biomarkers that could detect HCC early will play an important role in the successful treatment of HCC. Methods In this study, we analyzed serum levels of alpha fetoprotein, Golgi protein, fucosylated alpha-1-anti-trypsin, and fucosylated kininogen from 113 patients with cirrhosis and 164 serum samples from patients with cirrhosis plus HCC. We utilized two different methods, namely, stepwise penalized logistic regression (stepPLR) and model-based classification and regression trees (mob), along with the inclusion of clinical and demographic factors such as age and gender, to determine if these improved algorithms could be used to increase the detection of cancer. Results and discussion The performance of multiple biomarkers was found to be better than that of individual biomarkers. Using several statistical methods, we were able to detect HCC in the background of cirrhosis with an area under the receiver operating characteristic curve of at least 0.95. stepPLR and mob demonstrated better predictive performance relative to logistic regression (LR), penalized LR and classification and regression trees (CART) used in our prior study based on three-fold cross-validation and leave one out cross-validation. In addition, mob provided unparalleled intuitive interpretation of results and potential cut-points for biomarker levels. The inclusion of age and gender improved the overall performance of both methods among all models considered, while the stratified male-only subset provided the best overall performance among all methods and models considered. Conclusions In addition to multiple

  20. Adaptive and robust statistical methods for processing near-field scanning microwave microscopy images.

    PubMed

    Coakley, K J; Imtiaz, A; Wallis, T M; Weber, J C; Berweger, S; Kabos, P

    2015-03-01

    Near-field scanning microwave microscopy offers great potential to facilitate characterization, development and modeling of materials. By acquiring microwave images at multiple frequencies and amplitudes (along with the other modalities) one can study material and device physics at different lateral and depth scales. Images are typically noisy and contaminated by artifacts that can vary from scan line to scan line and planar-like trends due to sample tilt errors. Here, we level images based on an estimate of a smooth 2-d trend determined with a robust implementation of a local regression method. In this robust approach, features and outliers which are not due to the trend are automatically downweighted. We denoise images with the Adaptive Weights Smoothing method. This method smooths out additive noise while preserving edge-like features in images. We demonstrate the feasibility of our methods on topography images and microwave |S11| images. For one challenging test case, we demonstrate that our method outperforms alternative methods from the scanning probe microscopy data analysis software package Gwyddion. Our methods should be useful for massive image data sets where manual selection of landmarks or image subsets by a user is impractical.

  1. Determination of free acid by standard addition method in potassium thiocyanate

    SciTech Connect

    Not Available

    1981-06-01

    An analytical method for determination of free acidity in all SRP process solutions has been developed. Free acidity was successfully determined in solutions of nitric acid and the nitrates of aluminum, chromium(III), iron(III), mercury(II), nickel(II), thorium, and uranium(VI), at metal-to-acid ratios <2.5. Sample requirements, instrumentation, and mode of operation are similar to those currently used in the Laboratories Department free acid procedures. The simple procedure would be suitable for automation and microprocessor control. The method consists of two additions of known increments of acid into a solution containing the sample aliquot (10 ..mu..moles free acid) and 10 mL 1M potassium thiocyanate. The potential is determined in the initial solution and after each addition with a glass electrode and pH meter. The sample concentration is calculated by solution of three simultaneous Nernst equations. Two programs for this iterative computation are available: one written for the PDP-15 computer and another for a Hewlett-Packard 67 (or 97) programmable calculator. The accuracy of the result is verified by a slope that approximates the theoretical Nernst value. The relative standard deviation is <2.5%. This memorandum includes a survey of experiments with thermometric, pH, and Gran plot titrations in a variety of complexants, from which this particular system and technique logically evolved. The appendix includes a literature survey of sixty references, a discussion of the basic measurements, and a complete analytical procedure. The final step for completion of this RTA is training and consultation at the convenience of the Laboratories Department for demonstration of the method with process samples.

  2. Combining statistical and physics-based methods for predicting induced seismic hazard during reservoir stimulation

    NASA Astrophysics Data System (ADS)

    Gischig, V. S.; Mena Cabrera, B.; Goertz-Allmann, B.; Wiemer, S.

    2012-12-01

    observed data. We demonstrate that the model can reasonably reproduce both the temporal evolution of observed event statistics, and minimally the extent of at the seismic cloud recorded during the Basel reservoir stimulation in 2006. We also argue that triggering pressure is at a realistic order of magnitude, because modeled and measured wellhead pressure curves are in good agreement. Furthermore, the model is tested against observations in a pseudo-prospective manner, and compared to the existing purely statistical forecasting methods. Finally, we use the calibrated model to explore different injection scenarios, and their consequences for seismic hazard. Translating the calibrated models with different injection scenarios into probabilistic seismic hazard allows us to qualitatively compare their effects on the probability of occurrence of a hazardous event. Our modeling strategy and statistical testing procedure forms a test-bed that can be used to investigate the forecasting capabilities of future models developed towards higher physical complexity.

  3. Analyzing Planck and low redshift data sets with advanced statistical methods

    NASA Astrophysics Data System (ADS)

    Eifler, Tim

    The recent ESA/NASA Planck mission has provided a key data set to constrain cosmology that is most sensitive to physics of the early Universe, such as inflation and primordial NonGaussianity (Planck 2015 results XIII). In combination with cosmological probes of the LargeScale Structure (LSS), the Planck data set is a powerful source of information to investigate late time phenomena (Planck 2015 results XIV), e.g. the accelerated expansion of the Universe, the impact of baryonic physics on the growth of structure, and the alignment of galaxies in their dark matter halos. It is the main objective of this proposal to re-analyze the archival Planck data, 1) with different, more recently developed statistical methods for cosmological parameter inference, and 2) to combine Planck and ground-based observations in an innovative way. We will make the corresponding analysis framework publicly available and believe that it will set a new standard for future CMB-LSS analyses. Advanced statistical methods, such as the Gibbs sampler (Jewell et al 2004, Wandelt et al 2004) have been critical in the analysis of Planck data. More recently, Approximate Bayesian Computation (ABC, see Weyant et al 2012, Akeret et al 2015, Ishida et al 2015, for cosmological applications) has matured to an interesting tool in cosmological likelihood analyses. It circumvents several assumptions that enter the standard Planck (and most LSS) likelihood analyses, most importantly, the assumption that the functional form of the likelihood of the CMB observables is a multivariate Gaussian. Beyond applying new statistical methods to Planck data in order to cross-check and validate existing constraints, we plan to combine Planck and DES data in a new and innovative way and run multi-probe likelihood analyses of CMB and LSS observables. The complexity of multiprobe likelihood analyses scale (non-linearly) with the level of correlations amongst the individual probes that are included. For the multi

  4. The Role of Statistics and Research Methods in the Academic Success of Psychology Majors: Do Performance and Enrollment Timing Matter?

    ERIC Educational Resources Information Center

    Freng, Scott; Webber, David; Blatter, Jamin; Wing, Ashley; Scott, Walter D.

    2011-01-01

    Comprehension of statistics and research methods is crucial to understanding psychology as a science (APA, 2007). However, psychology majors sometimes approach methodology courses with derision or anxiety (Onwuegbuzie & Wilson, 2003; Rajecki, Appleby, Williams, Johnson, & Jeschke, 2005); consequently, students may postpone…

  5. Statistical downscaling of precipitation using local regression and high accuracy surface modeling method

    NASA Astrophysics Data System (ADS)

    Zhao, Na; Yue, Tianxiang; Zhou, Xun; Zhao, Mingwei; Liu, Yu; Du, Zhengping; Zhang, Lili

    2016-03-01

    Downscaling precipitation is required in local scale climate impact studies. In this paper, a statistical downscaling scheme was presented with a combination of geographically weighted regression (GWR) model and a recently developed method, high accuracy surface modeling method (HASM). This proposed method was compared with another downscaling method using the Coupled Model Intercomparison Project Phase 5 (CMIP5) database and ground-based data from 732 stations across China for the period 1976-2005. The residual which was produced by GWR was modified by comparing different interpolators including HASM, Kriging, inverse distance weighted method (IDW), and Spline. The spatial downscaling from 1° to 1-km grids for period 1976-2005 and future scenarios was achieved by using the proposed downscaling method. The prediction accuracy was assessed at two separate validation sites throughout China and Jiangxi Province on both annual and seasonal scales, with the root mean square error (RMSE), mean relative error (MRE), and mean absolute error (MAE). The results indicate that the developed model in this study outperforms the method that builds transfer function using the gauge values. There is a large improvement in the results when using a residual correction with meteorological station observations. In comparison with other three classical interpolators, HASM shows better performance in modifying the residual produced by local regression method. The success of the developed technique lies in the effective use of the datasets and the modification process of the residual by using HASM. The results from the future climate scenarios show that precipitation exhibits overall increasing trend from T1 (2011-2040) to T2 (2041-2070) and T2 to T3 (2071-2100) in RCP2.6, RCP4.5, and RCP8.5 emission scenarios. The most significant increase occurs in RCP8.5 from T2 to T3, while the lowest increase is found in RCP2.6 from T2 to T3, increased by 47.11 and 2.12 mm, respectively.

  6. Indoor Soiling Method and Outdoor Statistical Risk Analysis of Photovoltaic Power Plants

    NASA Astrophysics Data System (ADS)

    Rajasekar, Vidyashree

    This is a two-part thesis. Part 1 presents an approach for working towards the development of a standardized artificial soiling method for laminated photovoltaic (PV) cells or mini-modules. Construction of an artificial chamber to maintain controlled environmental conditions and components/chemicals used in artificial soil formulation is briefly explained. Both poly-Si mini-modules and a single cell mono-Si coupons were soiled and characterization tests such as I-V, reflectance and quantum efficiency (QE) were carried out on both soiled, and cleaned coupons. From the results obtained, poly-Si mini-modules proved to be a good measure of soil uniformity, as any non-uniformity present would not result in a smooth curve during I-V measurements. The challenges faced while executing reflectance and QE characterization tests on poly-Si due to smaller size cells was eliminated on the mono-Si coupons with large cells to obtain highly repeatable measurements. This study indicates that the reflectance measurements between 600-700 nm wavelengths can be used as a direct measure of soil density on the modules. Part 2 determines the most dominant failure modes of field aged PV modules using experimental data obtained in the field and statistical analysis, FMECA (Failure Mode, Effect, and Criticality Analysis). The failure and degradation modes of about 744 poly-Si glass/polymer frameless modules fielded for 18 years under the cold-dry climate of New York was evaluated. Defect chart, degradation rates (both string and module levels) and safety map were generated using the field measured data. A statistical reliability tool, FMECA that uses Risk Priority Number (RPN) is used to determine the dominant failure or degradation modes in the strings and modules by means of ranking and prioritizing the modes. This study on PV power plants considers all the failure and degradation modes from both safety and performance perspectives. The indoor and outdoor soiling studies were jointly

  7. How to choose the right statistical software?-a method increasing the post-purchase satisfaction.

    PubMed

    Cavaliere, Roberto

    2015-12-01

    Nowadays, we live in the "data era" where the use of statistical or data analysis software is inevitable, in any research field. This means that the choice of the right software tool or platform is a strategic issue for a research department. Nevertheless, in many cases decision makers do not pay the right attention to a comprehensive and appropriate evaluation of what the market offers. Indeed, the choice still depends on few factors like, for instance, researcher's personal inclination, e.g., which software have been used at the university or is already known. This is not wrong in principle, but in some cases it's not enough at all and might lead to a "dead end" situation, typically after months or years of investments already done on the wrong software. This article, far from being a full and complete guide to statistical software evaluation, aims to illustrate some key points of the decision process and introduce an extended range of factors which can help to undertake the right choice, at least in potential. There is not enough literature about that topic, most of the time underestimated, both in the traditional literature and even in the so called "gray literature", even if some documents or short pages can be found online. Anyhow, it seems there is not a common and known standpoint about the process of software evaluation from the final user perspective. We suggests a multi-factor analysis leading to an evaluation matrix tool, to be intended as a flexible and customizable tool, aimed to provide a clearer picture of the software alternatives available, not in abstract but related to the researcher's own context and needs. This method is a result of about twenty years of experience of the author in the field of evaluating and using technical-computing software and partially arises from a research made about such topics as part of a project funded by European Commission under the Lifelong Learning Programme 2011.

  8. Seasonal forecasting of hydrological drought in the Limpopo Basin: a comparison of statistical methods

    NASA Astrophysics Data System (ADS)

    Seibert, Mathias; Merz, Bruno; Apel, Heiko

    2017-03-01

    The Limpopo Basin in southern Africa is prone to droughts which affect the livelihood of millions of people in South Africa, Botswana, Zimbabwe and Mozambique. Seasonal drought early warning is thus vital for the whole region. In this study, the predictability of hydrological droughts during the main runoff period from December to May is assessed using statistical approaches. Three methods (multiple linear models, artificial neural networks, random forest regression trees) are compared in terms of their ability to forecast streamflow with up to 12 months of lead time. The following four main findings result from the study. 1. There are stations in the basin at which standardised streamflow is predictable with lead times up to 12 months. The results show high inter-station differences of forecast skill but reach a coefficient of determination as high as 0.73 (cross validated). 2. A large range of potential predictors is considered in this study, comprising well-established climate indices, customised teleconnection indices derived from sea surface temperatures and antecedent streamflow as a proxy of catchment conditions. El Niño and customised indices, representing sea surface temperature in the Atlantic and Indian oceans, prove to be important teleconnection predictors for the region. Antecedent streamflow is a strong predictor in small catchments (with median 42 % explained variance), whereas teleconnections exert a stronger influence in large catchments. 3. Multiple linear models show the best forecast skill in this study and the greatest robustness compared to artificial neural networks and random forest regression trees, despite their capabilities to represent nonlinear relationships. 4. Employed in early warning, the models can be used to forecast a specific drought level. Even if the coefficient of determination is low, the forecast models have a skill better than a climatological forecast, which is shown by analysis of receiver operating characteristics

  9. Solution identification and quantitative analysis of fiber-capacitive drop analyzer based on multivariate statistical methods

    NASA Astrophysics Data System (ADS)

    Chen, Zhe; Qiu, Zurong; Huo, Xinming; Fan, Yuming; Li, Xinghua

    2017-03-01

    A fiber-capacitive drop analyzer is an instrument which monitors a growing droplet to produce a capacitive opto-tensiotrace (COT). Each COT is an integration of fiber light intensity signals and capacitance signals and can reflect the unique physicochemical property of a liquid. In this study, we propose a solution analytical and concentration quantitative method based on multivariate statistical methods. Eight characteristic values are extracted from each COT. A series of COT characteristic values of training solutions at different concentrations compose a data library of this kind of solution. A two-stage linear discriminant analysis is applied to analyze different solution libraries and establish discriminant functions. Test solutions can be discriminated by these functions. After determining the variety of test solutions, Spearman correlation test and principal components analysis are used to filter and reduce dimensions of eight characteristic values, producing a new representative parameter. A cubic spline interpolation function is built between the parameters and concentrations, based on which we can calculate the concentration of the test solution. Methanol, ethanol, n-propanol, and saline solutions are taken as experimental subjects in this paper. For each solution, nine or ten different concentrations are chosen to be the standard library, and the other two concentrations compose the test group. By using the methods mentioned above, all eight test solutions are correctly identified and the average relative error of quantitative analysis is 1.11%. The method proposed is feasible which enlarges the applicable scope of recognizing liquids based on the COT and improves the concentration quantitative precision, as well.

  10. Feature Selection Applying Statistical and Neurofuzzy Methods to EEG-Based BCI.

    PubMed

    Martinez-Leon, Juan-Antonio; Cano-Izquierdo, Jose-Manuel; Ibarrola, Julio

    2015-01-01

    This paper presents an investigation aimed at drastically reducing the processing burden required by motor imagery brain-computer interface (BCI) systems based on electroencephalography (EEG). In this research, the focus has moved from the channel to the feature paradigm, and a 96% reduction of the number of features required in the process has been achieved maintaining and even improving the classification success rate. This way, it is possible to build cheaper, quicker, and more portable BCI systems. The data set used was provided within the framework of BCI Competition III, which allows it to compare the presented results with the classification accuracy achieved in the contest. Furthermore, a new three-step methodology has been developed which includes a feature discriminant character calculation stage; a score, order, and selection phase; and a final feature selection step. For the first stage, both statistics method and fuzzy criteria are used. The fuzzy criteria are based on the S-dFasArt classification algorithm which has shown excellent performance in previous papers undertaking the BCI multiclass motor imagery problem. The score, order, and selection stage is used to sort the features according to their discriminant nature. Finally, both order selection and Group Method Data Handling (GMDH) approaches are used to choose the most discriminant ones.

  11. Feature Selection Applying Statistical and Neurofuzzy Methods to EEG-Based BCI

    PubMed Central

    Martinez-Leon, Juan-Antonio; Cano-Izquierdo, Jose-Manuel; Ibarrola, Julio

    2015-01-01

    This paper presents an investigation aimed at drastically reducing the processing burden required by motor imagery brain-computer interface (BCI) systems based on electroencephalography (EEG). In this research, the focus has moved from the channel to the feature paradigm, and a 96% reduction of the number of features required in the process has been achieved maintaining and even improving the classification success rate. This way, it is possible to build cheaper, quicker, and more portable BCI systems. The data set used was provided within the framework of BCI Competition III, which allows it to compare the presented results with the classification accuracy achieved in the contest. Furthermore, a new three-step methodology has been developed which includes a feature discriminant character calculation stage; a score, order, and selection phase; and a final feature selection step. For the first stage, both statistics method and fuzzy criteria are used. The fuzzy criteria are based on the S-dFasArt classification algorithm which has shown excellent performance in previous papers undertaking the BCI multiclass motor imagery problem. The score, order, and selection stage is used to sort the features according to their discriminant nature. Finally, both order selection and Group Method Data Handling (GMDH) approaches are used to choose the most discriminant ones. PMID:25977685

  12. Bayesian Analysis of Two Stellar Populations in Galactic Globular Clusters. I. Statistical and Computational Methods

    NASA Astrophysics Data System (ADS)

    Stenning, D. C.; Wagner-Kaiser, R.; Robinson, E.; van Dyk, D. A.; von Hippel, T.; Sarajedini, A.; Stein, N.

    2016-07-01

    We develop a Bayesian model for globular clusters composed of multiple stellar populations, extending earlier statistical models for open clusters composed of simple (single) stellar populations. Specifically, we model globular clusters with two populations that differ in helium abundance. Our model assumes a hierarchical structuring of the parameters in which physical properties—age, metallicity, helium abundance, distance, absorption, and initial mass—are common to (i) the cluster as a whole or to (ii) individual populations within a cluster, or are unique to (iii) individual stars. An adaptive Markov chain Monte Carlo (MCMC) algorithm is devised for model fitting that greatly improves convergence relative to its precursor non-adaptive MCMC algorithm. Our model and computational tools are incorporated into an open-source software suite known as BASE-9. We use numerical studies to demonstrate that our method can recover parameters of two-population clusters, and also show how model misspecification can potentially be identified. As a proof of concept, we analyze the two stellar populations of globular cluster NGC 5272 using our model and methods. (BASE-9 is available from GitHub: https://github.com/argiopetech/base/releases).

  13. Determination of the neutrino mass hierarchy with a new statistical method

    NASA Astrophysics Data System (ADS)

    Stanco, L.; Dusini, S.; Tenti, M.

    2017-03-01

    Nowadays neutrino physics is undergoing a change of perspective: the discovery period is almost over and the phase of precise measurements is starting. Despite the limited statistics collected for some variables, the three-flavor oscillation neutrino framework is strengthening well. In this framework a new method has been developed to determine the neutrino mass ordering, one of the still unknown and most relevant parameters. The method is applied to the 2015 results of the NOvA experiment for νμ→νe appearance, including its systematic errors. A substantial gain in significance is obtained compared to the traditional Δ χ2 approach. Perspectives are provided for future results obtainable by NOvA with larger exposures. Assuming the number of the 2015 νe observed events scales with the exposure, an increase in only a factor three would exclude the inverted hierarchy at more than 95% C.L. over the full range of the C P violating phase. The preliminary 2016 NOvA measurement on νμ→νe appearance has also been analyzed.

  14. A Powerful Statistical Method for Identifying Differentially Methylated Markers in Complex Diseases

    PubMed Central

    Ahn, Surin; Wang, Tao

    2013-01-01

    DNA methylation is an important epigenetic modification that regulates transcriptional expression and plays an important role in complex diseases, such as cancer. Genome-wide methylation patterns have unique features and hence require the development of new analytic approaches. One important feature is that methylation levels in disease tissues often differ from those in normal tissues with respect to both average and variability. In this paper, we propose a new score test to identify methylation markers of disease. This approach simultaneously utilizes information from the first and second moments of methylation distribution to improve statistical efficiency. Because the proposed score test is derived from a generalized regression model, it can be used for analyzing both categorical and continuous disease phenotypes, and for adjusting for covariates. We evaluate the performance of the proposed method and compare it to other tests including the most commonly-used t-test through simulations. The simulation results show that the validity of the proposed method is robust to departures from the normal assumption of methylation levels and can be substantially more powerful than the t-test in the presence of heterogeneity of methylation variability between disease and normal tissues. We demonstrate our approach by analyzing the methylation dataset of an ovarian cancer study and identify novel methylation loci not identified by the t-test. PMID:23424113

  15. Method for simultaneous use of a single additive for coal flotation, dewatering, and reconstitution

    DOEpatents

    Wen, Wu-Wey; Gray, McMahan L.; Champagne, Kenneth J.

    1995-01-01

    A single dose of additive contributes to three consecutive fine coal unit operations, i.e., flotation, dewatering and reconstitution, whereby the fine coal is first combined with water in a predetermined proportion so as to formulate a slurry. The slurry is then mixed with a heavy hydrocarbon-based emulsion in a second predetermined proportion and at a first predetermined mixing speed and for a predetermined period of time. The conditioned slurry is then cleaned by a froth flotation method to form a clean coal froth and then the froth is dewatered by vacuum filtration or a centrifugation process to form reconstituted products that are dried to dust-less clumps prior to combustion.

  16. Method for simultaneous use of a single additive for coal flotation, dewatering and reconstitution

    SciTech Connect

    Wen, Wu-Wey; Gray, M.L.; Champagne, K.J.

    1993-11-09

    A single dose of additive contributes to three consecutive fine coal unit operations, i.e., flotation, dewatering and reconstitution, whereby the fine coal is first combined with water in a predetermined proportion so as to formulate a slurry. The slurry is then mixed with a heavy hydrocarbon-based emulsion in a second predetermined proportion and at a first predetermined mixing speed and for a predetermined period of time. The conditioned slurry is then cleaned by a froth flotation method to form a clean coal froth and then the froth is dewatered by vacuum filtration or a centrifugation process to form reconstituted products that are dried to dust-less clumps prior to combustion.

  17. A square-wave adsorptive stripping voltammetric method for the determination of Amaranth, a food additive dye.

    PubMed

    Alghamdi, Ahmad H

    2005-01-01

    Square-wave adsorptive stripping voltammetric (AdSV) determinations of trace concentrations of the azo coloring agent Amaranth are described. The analytical methodology used was based on the adsorptive preconcentration of the dye on the hanging mercury drop electrode, followed by initiation of a negative sweep. In a pH 10 carbonate supporting electrolyte, Amaranth gave a well-defined and sensitive AdSV peak at -518 mV. The electroanalytical determination of this azo dye was found to be optimal in carbonate buffer (pH 10) under the following experimental conditions: accumulation time, 120 s; accumulation potential, 0.0 V; scan rate, 600 mV/s; pulse amplitude, 90 mV; and frequency, 50 Hz. Under these optimized conditions the AdSV peak current was proportional over the concentration range 1 x 10(-8)-1.1 x 10(-7) mol/L (r = 0.999) with a detection limit of 1.7 x 10(-9) mol/L (1.03 ppb). This analytical approach possessed enhanced sensitivity, compared with conventional liquid chromatography or spectrophotometry and it was simple and fast. The precision of the method, expressed as the relative standard deviation, was 0.23%, whereas the accuracy, expressed as the mean recovery, was 104%. Possible interferences by several substances usually present as food additive azo dyes (E110, E102), gelatin, natural and artificial sweeteners, preservatives, and antioxidants were also investigated. The developed electroanalyticals method was applied to the determination of Amaranth in soft drink samples, and the results were compared with those obtained by a reference spectrophotometric method. Statistical analysis (paired t-test) of these data showed that the results of the 2 methods compared favorably.

  18. A hypertext-based tutorial with links to the Web for teaching statistics and research methods.

    PubMed

    Koch, C; Gobell, J

    1999-02-01

    An online tutorial for research design and statistics is described. This tutorial provides a way for students to learn how scales of measure, research design, statistics, and graphing data are related. The tutorial also helps students determine what statistical analysis is appropriate for a given design and how the results of the analysis should be plotted in order to effectively communicate the results of a study. Initial research suggests that students using the tutorial are more accurate in their decisions about the design and statistics associated with a study. Students are also more confident in the decisions and find them easier to make when using the tutorial. Furthermore, practice with the tutorial appears to improve problem-solving ability in subsequent design and statistics scenarios. Implications for teaching statistics and research design are discussed.

  19. Spectral-Lagrangian methods for collisional models of non-equilibrium statistical states

    SciTech Connect

    Gamba, Irene M. Tharkabhushanam, Sri Harsha

    2009-04-01

    We propose a new spectral Lagrangian based deterministic solver for the non-linear Boltzmann transport equation (BTE) in d-dimensions for variable hard sphere (VHS) collision kernels with conservative or non-conservative binary interactions. The method is based on symmetries of the Fourier transform of the collision integral, where the complexity in its computation is reduced to a separate integral over the unit sphere S{sup d-1}. The conservation of moments is enforced by Lagrangian constraints. The resulting scheme, implemented in free space, is very versatile and adjusts in a very simple manner to several cases that involve energy dissipation due to local micro-reversibility (inelastic interactions) or elastic models of slowing down process. Our simulations are benchmarked with available exact self-similar solutions, exact moment equations and analytical estimates for the homogeneous Boltzmann equation, both for elastic and inelastic VHS interactions. Benchmarking of the simulations involves the selection of a time self-similar rescaling of the numerical distribution function which is performed using the continuous spectrum of the equation for Maxwell molecules as studied first in Bobylev et al. [A.V. Bobylev, C. Cercignani, G. Toscani, Proof of an asymptotic property of self-similar solutions of the Boltzmann equation for granular materials, Journal of Statistical Physics 111 (2003) 403-417] and generalized to a wide range of related models in Bobylev et al. [A.V. Bobylev, C. Cercignani, I.M. Gamba, On the self-similar asymptotics for generalized non-linear kinetic Maxwell models, Communication in Mathematical Physics, in press. URL: ()]. The method also produces accurate results in the case of inelastic diffusive Boltzmann equations for hard spheres (inelastic collisions under thermal bath), where overpopulated non-Gaussian exponential tails have been conjectured in computations by stochastic methods [T.V. Noije, M. Ernst

  20. Statistical Track-Before-Detect Methods Applied to Faint Optical Observations of Resident Space Objects

    NASA Astrophysics Data System (ADS)

    Fujimoto, K.; Yanagisawa, T.; Uetsuhara, M.

    Automated detection and tracking of faint objects in optical, or bearing-only, sensor imagery is a topic of immense interest in space surveillance. Robust methods in this realm will lead to better space situational awareness (SSA) while reducing the cost of sensors and optics. They are especially relevant in the search for high area-to-mass ratio (HAMR) objects, as their apparent brightness can change significantly over time. A track-before-detect (TBD) approach has been shown to be suitable for faint, low signal-to-noise ratio (SNR) images of resident space objects (RSOs). TBD does not rely upon the extraction of feature points within the image based on some thresholding criteria, but rather directly takes as input the intensity information from the image file. Not only is all of the available information from the image used, TBD avoids the computational intractability of the conventional feature-based line detection (i.e., "string of pearls") approach to track detection for low SNR data. Implementation of TBD rooted in finite set statistics (FISST) theory has been proposed recently by Vo, et al. Compared to other TBD methods applied so far to SSA, such as the stacking method or multi-pass multi-period denoising, the FISST approach is statistically rigorous and has been shown to be more computationally efficient, thus paving the path toward on-line processing. In this paper, we intend to apply a multi-Bernoulli filter to actual CCD imagery of RSOs. The multi-Bernoulli filter can explicitly account for the birth and death of multiple targets in a measurement arc. TBD is achieved via a sequential Monte Carlo implementation. Preliminary results with simulated single-target data indicate that a Bernoulli filter can successfully track and detect objects with measurement SNR as low as 2.4. Although the advent of fast-cadence scientific CMOS sensors have made the automation of faint object detection a realistic goal, it is nonetheless a difficult goal, as measurements

  1. Statistical evaluation of an inductively coupled plasma atomic emission spectrometric method for routine water quality testing

    USGS Publications Warehouse

    Garbarino, J.R.; Jones, B.E.; Stein, G.P.

    1985-01-01

    In an interlaboratory test, inductively coupled plasma atomic emission spectrometry (ICP-AES) was compared with flame atomic absorption spectrometry and molecular absorption spectrophotometry for the determination of 17 major and trace elements in 100 filtered natural water samples. No unacceptable biases were detected. The analysis precision of ICP-AES was found to be equal to or better than alternative methods. Known-addition recovery experiments demonstrated that the ICP-AES determinations are accurate to between plus or minus 2 and plus or minus 10 percent; four-fifths of the tests yielded average recoveries of 95-105 percent, with an average relative standard deviation of about 5 percent.

  2. A statistical model for assessing performance standards for quantitative and semiquantitative disinfectant test methods.

    PubMed

    Parker, Albert E; Hamilton, Martin A; Tomasino, Stephen F

    2014-01-01

    A performance standard for a disinfectant test method can be evaluated by quantifying the (Type I) pass-error rate for ineffective products and the (Type II) fail-error rate for highly effective products. This paper shows how to calculate these error rates for test methods where the log reduction in a microbial population is used as a measure of antimicrobial efficacy. The calculations can be used to assess performance standards that may require multiple tests of multiple microbes at multiple laboratories. Notably, the error rates account for among-laboratory variance of the log reductions estimated from a multilaboratory data set and the correlation among tests of different microbes conducted in the same laboratory. Performance standards that require that a disinfectant product pass all tests or multiple tests on average, are considered. The proposed statistical methodology is flexible and allows for a different acceptable outcome for each microbe tested, since, for example, variability may be different for different microbes. The approach can also be applied to semiquantitative methods for which product efficacy is reported as the number of positive carriers out of a treated set and the density of the microbes on control carriers is quantified, thereby allowing a log reduction to be calculated. Therefore, using the approach described in this paper, the error rates can also be calculated for semiquantitative method performance standards specified solely in terms of the maximum allowable number of positive carriers per test. The calculations are demonstrated in a case study of the current performance standard for the semiquantitative AOAC Use-Dilution Methods for Pseudomonas aeruginosa (964.02) and Staphylococcus aureus (955.15), which allow up to one positive carrier out of a set of 60 inoculated and treated carriers in each test. A simulation study was also conducted to verify the validity of the model's assumptions and accuracy. Our approach, easily implemented

  3. Evaluation of Oceanic Transport Statistics By Use of Transient Tracers and Bayesian Methods

    NASA Astrophysics Data System (ADS)

    Trossman, D. S.; Thompson, L.; Mecking, S.; Bryan, F.; Peacock, S.

    2013-12-01

    Key variables that quantify the time scales over which atmospheric signals penetrate into the oceanic interior and their uncertainties are computed using Bayesian methods and transient tracers from both models and observations. First, the mean residence times, subduction rates, and formation rates of Subtropical Mode Water (STMW) and Subpolar Mode Water (SPMW) in the North Atlantic and Subantarctic Mode Water (SAMW) in the Southern Ocean are estimated by combining a model and observations of chlorofluorocarbon-11 (CFC-11) via Bayesian Model Averaging (BMA), statistical technique that weights model estimates according to how close they agree with observations. Second, a Bayesian method is presented to find two oceanic transport parameters associated with the age distribution of ocean waters, the transit-time distribution (TTD), by combining an eddying global ocean model's estimate of the TTD with hydrographic observations of CFC-11, temperature, and salinity. Uncertainties associated with objectively mapping irregularly spaced bottle data are quantified by making use of a thin-plate spline and then propagated via the two Bayesian techniques. It is found that the subduction of STMW, SPMW, and SAMW is mostly an advective process, but up to about one-third of STMW subduction likely owes to non-advective processes. Also, while the formation of STMW is mostly due to subduction, the formation of SPMW is mostly due to other processes. About half of the formation of SAMW is due to subduction and half is due to other processes. A combination of air-sea flux, acting on relatively short time scales, and turbulent mixing, acting on a wide range of time scales, is likely the dominant SPMW erosion mechanism. Air-sea flux is likely responsible for most STMW erosion, and turbulent mixing is likely responsible for most SAMW erosion. Two oceanic transport parameters, the mean age of a water parcel and the half-variance associated with the TTD, estimated using the model's tracers as

  4. Machine learning and statistical methods for the prediction of maximal oxygen uptake: recent advances

    PubMed Central

    Abut, Fatih; Akay, Mehmet Fatih

    2015-01-01

    Maximal oxygen uptake (VO2max) indicates how many milliliters of oxygen the body can consume in a state of intense exercise per minute. VO2max plays an important role in both sport and medical sciences for different purposes, such as indicating the endurance capacity of athletes or serving as a metric in estimating the disease risk of a person. In general, the direct measurement of VO2max provides the most accurate assessment of aerobic power. However, despite a high level of accuracy, practical limitations associated with the direct measurement of VO2max, such as the requirement of expensive and sophisticated laboratory equipment or trained staff, have led to the development of various regression models for predicting VO2max. Consequently, a lot of studies have been conducted in the last years to predict VO2max of various target audiences, ranging from soccer athletes, nonexpert swimmers, cross-country skiers to healthy-fit adults, teenagers, and children. Numerous prediction models have been developed using different sets of predictor variables and a variety of machine learning and statistical methods, including support vector machine, multilayer perceptron, general regression neural network, and multiple linear regression. The purpose of this study is to give a detailed overview about the data-driven modeling studies for the prediction of VO2max conducted in recent years and to compare the performance of various VO2max prediction models reported in related literature in terms of two well-known metrics, namely, multiple correlation coefficient (R) and standard error of estimate. The survey results reveal that with respect to regression methods used to develop prediction models, support vector machine, in general, shows better performance than other methods, whereas multiple linear regression exhibits the worst performance. PMID:26346869

  5. Introduction of a new critical p value correction method for statistical significance analysis of metabonomics data.

    PubMed

    Wang, Bo; Shi, Zhanquan; Weber, Georg F; Kennedy, Michael A

    2013-10-01

    Nuclear magnetic resonance (NMR) spectroscopy-based metabonomics is of growing importance for discovery of human disease biomarkers. Identification and validation of disease biomarkers using statistical significance analysis (SSA) is critical for translation to clinical practice. SSA is performed by assessing a null hypothesis test using a derivative of the Student's t test, e.g., a Welch's t test. Choosing how to correct the significance level for rejecting null hypotheses in the case of multiple testing to maintain a constant family-wise type I error rate is a common problem in such tests. The multiple testing problem arises because the likelihood of falsely rejecting the null hypothesis, i.e., a false positive, grows as the number of tests applied to the same data set increases. Several methods have been introduced to address this problem. Bonferroni correction (BC) assumes all variables are independent and therefore sacrifices sensitivity for detecting true positives in partially dependent data sets. False discovery rate (FDR) methods are more sensitive than BC but uniformly ascribe highest stringency to lowest p value variables. Here, we introduce standard deviation step down (SDSD), which is more sensitive and appropriate than BC for partially dependent data sets. Sensitivity and type I error rate of SDSD can be adjusted based on the degree of variable dependency. SDSD generates fundamentally different profiles of critical p values compared with FDR methods potentially leading to reduced type II error rates. SDSD is increasingly sensitive for more concentrated metabolites. SDSD is demonstrated using NMR-based metabonomics data collected on three different breast cancer cell line extracts.

  6. Machine learning and statistical methods for the prediction of maximal oxygen uptake: recent advances.

    PubMed

    Abut, Fatih; Akay, Mehmet Fatih

    2015-01-01

    Maximal oxygen uptake (VO2max) indicates how many milliliters of oxygen the body can consume in a state of intense exercise per minute. VO2max plays an important role in both sport and medical sciences for different purposes, such as indicating the endurance capacity of athletes or serving as a metric in estimating the disease risk of a person. In general, the direct measurement of VO2max provides the most accurate assessment of aerobic power. However, despite a high level of accuracy, practical limitations associated with the direct measurement of VO2max, such as the requirement of expensive and sophisticated laboratory equipment or trained staff, have led to the development of various regression models for predicting VO2max. Consequently, a lot of studies have been conducted in the last years to predict VO2max of various target audiences, ranging from soccer athletes, nonexpert swimmers, cross-country skiers to healthy-fit adults, teenagers, and children. Numerous prediction models have been developed using different sets of predictor variables and a variety of machine learning and statistical methods, including support vector machine, multilayer perceptron, general regression neural network, and multiple linear regression. The purpose of this study is to give a detailed overview about the data-driven modeling studies for the prediction of VO2max conducted in recent years and to compare the performance of various VO2max prediction models reported in related literature in terms of two well-known metrics, namely, multiple correlation coefficient (R) and standard error of estimate. The survey results reveal that with respect to regression methods used to develop prediction models, support vector machine, in general, shows better performance than other methods, whereas multiple linear regression exhibits the worst performance.

  7. SU-C-BRD-01: A Statistical Modeling Method for Quality Control of Intensity- Modulated Radiation Therapy Planning

    SciTech Connect

    Gao, S; Meyer, R; Shi, L; D'Souza, W; Zhang, H

    2014-06-15

    Purpose: To apply a statistical modeling approach, threshold modeling (TM), for quality control of intensity-modulated radiation therapy (IMRT) treatment plans. Methods: A quantitative measure, which was the weighted sum of violations of dose/dose-volume constraints, was first developed to represent the quality of each IMRT plan. Threshold modeling approach, which is is an extension of extreme value theory in statistics and is an effect way to model extreme values, was then applied to analyze the quality of the plans summarized by our quantitative measures. Our approach modeled the plans generated by planners as a series of independent and identically distributed random variables and described the behaviors of them if the plan quality was controlled below certain threshold. We tested our approach with five locally advanced head and neck cancer patients retrospectively. Two statistics were incorporated for numerical analysis: probability of quality improvement (PQI) of the plans and expected amount of improvement on the quantitative measure (EQI). Results: After clinical planners generated 15 plans for each patient, we applied our approach to obtain the PQI and EQI as if planners would generate additional 15 plans. For two of the patients, the PQI was significantly higher than the other three (0.17 and 0.18 comparing to 0.08, 0.01 and 0.01). The actual percentage of the additional 15 plans that outperformed the best of initial 15 plans was 20% and 27% comparing to 11%, 0% and 0%. EQI for the two potential patients were 34.5 and 32.9 and the rest of three patients were 9.9, 1.4 and 6.6. The actual improvements obtained were 28.3 and 20.5 comparing to 6.2, 0 and 0. Conclusion: TM is capable of reliably identifying the potential quality improvement of IMRT plans. It provides clinicians an effective tool to assess the trade-off between extra planning effort and achievable plan quality. This work was supported in part by NIH/NCI grant CA130814.

  8. Simulation of Powder Layer Deposition in Additive Manufacturing Processes Using the Discrete Element Method

    SciTech Connect

    Herbold, E. B.; Walton, O.; Homel, M. A.

    2015-10-26

    This document serves as a final report to a small effort where several improvements were added to a LLNL code GEODYN-­L to develop Discrete Element Method (DEM) algorithms coupled to Lagrangian Finite Element (FE) solvers to investigate powder-­bed formation problems for additive manufacturing. The results from these simulations will be assessed for inclusion as the initial conditions for Direct Metal Laser Sintering (DMLS) simulations performed with ALE3D. The algorithms were written and performed on parallel computing platforms at LLNL. The total funding level was 3-­4 weeks of an FTE split amongst two staff scientists and one post-­doc. The DEM simulations emulated, as much as was feasible, the physical process of depositing a new layer of powder over a bed of existing powder. The DEM simulations utilized truncated size distributions spanning realistic size ranges with a size distribution profile consistent with realistic sample set. A minimum simulation sample size on the order of 40-­particles square by 10-­particles deep was utilized in these scoping studies in order to evaluate the potential effects of size segregation variation with distance displaced in front of a screed blade. A reasonable method for evaluating the problem was developed and validated. Several simulations were performed to show the viability of the approach. Future investigations will focus on running various simulations investigating powder particle sizing and screen geometries.

  9. Lactic Acid Fermentation, Urea and Lime Addition: Promising Faecal Sludge Sanitizing Methods for Emergency Sanitation.

    PubMed

    Anderson, Catherine; Malambo, Dennis Hanjalika; Perez, Maria Eliette Gonzalez; Nobela, Happiness Ngwanamoseka; de Pooter, Lobke; Spit, Jan; Hooijmans, Christine Maria; de Vossenberg, Jack van; Greya, Wilson; Thole, Bernard; van Lier, Jules B; Brdjanovic, Damir

    2015-10-29

    In this research, three faecal sludge sanitizing methods-lactic acid fermentation, urea treatment and lime treatment-were studied for application in emergency situations. These methods were investigated by undertaking small scale field trials with pit latrine sludge in Blantyre, Malawi. Hydrated lime was able to reduce the E. coli count in the sludge to below the detectable limit within 1 h applying a pH > 11 (using a dosage from 7% to 17% w/w, depending faecal sludge alkalinity), urea treatment required about 4 days using 2.5% wet weight urea addition, and lactic acid fermentation needed approximately 1 week after being dosed with 10% wet weight molasses (2 g (glucose/fructose)/kg) and 10% wet weight pre-culture (99.8% pasteurised whole milk and 0.02% fermented milk drink containing Lactobacillus casei Shirota). Based on Malawian prices, the cost of sanitizing 1 m³ of faecal sludge was estimated to be €32 for lactic acid fermentation, €20 for urea treatment and €12 for hydrated lime treatment.

  10. Determination of robotic trajectory best distance using simple additive weighting method

    NASA Astrophysics Data System (ADS)

    Rohman, Muchamad Zainul

    2017-02-01

    Determination of the best distance, namely the closest distance and in the shortest time to reach a destination appropriately, has been applied in daily life. The determination of the best distance can be applied on robot trajectory so that robot can reach its destination quickly and appropriately without taking much time in robot contest, such as Indonesian Smart Robot Contest (KRCI). The difficulties to determine the closest distance occur due to the existing trajectory alternatives. In this aspect the reliability of a robot is tested and contested. Every year there are many robot contests either local, national, or international scale. Robot trajectory is a place or points passed by moving objects. This study used Simple Additive Method (SAW) method to find the closest distance by finding the value of alternative tracks existing on the trajectory. Determination of the closest distance on robot trajectory gives facility for the users to find the closest distance of a robot trajectory so as to input the correct algorithm in robot to reach the destination quickly and appropriately.

  11. DNA libraries for the construction of phage libraries: statistical and structural requirements and synthetic methods.

    PubMed

    Lindner, Thomas; Kolmar, Harald; Haberkorn, Uwe; Mier, Walter

    2011-02-15

    Peptide-based molecular probes identified by bacteriophage (phage) display technology expand the peptide repertoire for in vivo diagnosis and therapy of cancer. Numerous peptides that bind cancer-associated antigens have been discovered by panning phage libraries. However, until now only few of the peptides selected by phage display have entered clinical applications. The success of phage derived peptides essentially depends on the quality of the library screened. This review summarizes the methods to achieve highly homogenous libraries that cover a maximal sequence space. Biochemical and chemical strategies for the synthesis of DNA libraries and the techniques for their integration into the viral genome are discussed in detail. A focus is set on the methods that enable the exclusion of disturbing sequences. In addition, the parameters that define the variability, the minimal numbers of copies per library and the use of alternating panning cycles to avoid the loss of selected hits are evaluated.

  12. Experimental and Statistical Evaluation of Cutting Methods in Relation to Specific Energy and Rock Properties

    NASA Astrophysics Data System (ADS)

    Engin, Irfan Celal; Bayram, Fatih; Yasitli, Nazmi Erhan

    2013-07-01

    In a processing plant, natural stone can be cut by methods such as circular sawing (CS), frame sawing (FS), water jet cutting (WJC) and abrasive water jet cutting (AWJC). The efficiency of cutting systems can be compared using various parameters. In this study, the specific energy values were determined and compared to evaluate the efficiency of rock-cutting methods. Rock-cutting experiments were performed on 12 different types of rock samples using a circular sawing machine and an AWJC machine. The experimental results showed that the specific energy values in AWJC were generally higher than in CS. In addition, the relationships between specific energy values and rock properties were explained in this study. The Shore hardness and abrasion resistance were found to be strongly related to the specific energy values, and according to these parameters prediction charts of specific energy values were created.

  13. Multiple Linkage Disequilibrium Mapping Methods to Validate Additive Quantitative Trait Loci in Korean Native Cattle (Hanwoo)

    PubMed Central

    Li, Yi; Kim, Jong-Joo

    2015-01-01

    The efficiency of genome-wide association analysis (GWAS) depends on power of detection for quantitative trait loci (QTL) and precision for QTL mapping. In this study, three different strategies for GWAS were applied to detect QTL for carcass quality traits in the Korean cattle, Hanwoo; a linkage disequilibrium single locus regression method (LDRM), a combined linkage and linkage disequilibrium analysis (LDLA) and a BayesCπ approach. The phenotypes of 486 steers were collected for weaning weight (WWT), yearling weight (YWT), carcass weight (CWT), backfat thickness (BFT), longissimus dorsi muscle area, and marbling score (Marb). Also the genotype data for the steers and their sires were scored with the Illumina bovine 50K single nucleotide polymorphism (SNP) chips. For the two former GWAS methods, threshold values were set at false discovery rate <0.01 on a chromosome-wide level, while a cut-off threshold value was set in the latter model, such that the top five windows, each of which comprised 10 adjacent SNPs, were chosen with significant variation for the phenotype. Four major additive QTL from these three methods had high concordance found in 64.1 to 64.9Mb for Bos taurus autosome (BTA) 7 for WWT, 24.3 to 25.4Mb for BTA14 for CWT, 0.5 to 1.5Mb for BTA6 for BFT and 26.3 to 33.4Mb for BTA29 for BFT. Several candidate genes (i.e. glutamate receptor, ionotropic, ampa 1 [GRIA1], family with sequence similarity 110, member B [FAM110B], and thymocyte selection-associated high mobility group box [TOX]) may be identified close to these QTL. Our result suggests that the use of different linkage disequilibrium mapping approaches can provide more reliable chromosome regions to further pinpoint DNA makers or causative genes in these regions. PMID:26104396

  14. Multiple Linkage Disequilibrium Mapping Methods to Validate Additive Quantitative Trait Loci in Korean Native Cattle (Hanwoo).

    PubMed

    Li, Yi; Kim, Jong-Joo

    2015-07-01

    The efficiency of genome-wide association analysis (GWAS) depends on power of detection for quantitative trait loci (QTL) and precision for QTL mapping. In this study, three different strategies for GWAS were applied to detect QTL for carcass quality traits in the Korean cattle, Hanwoo; a linkage disequilibrium single locus regression method (LDRM), a combined linkage and linkage disequilibrium analysis (LDLA) and a BayesCπ approach. The phenotypes of 486 steers were collected for weaning weight (WWT), yearling weight (YWT), carcass weight (CWT), backfat thickness (BFT), longissimus dorsi muscle area, and marbling score (Marb). Also the genotype data for the steers and their sires were scored with the Illumina bovine 50K single nucleotide polymorphism (SNP) chips. For the two former GWAS methods, threshold values were set at false discovery rate <0.01 on a chromosome-wide level, while a cut-off threshold value was set in the latter model, such that the top five windows, each of which comprised 10 adjacent SNPs, were chosen with significant variation for the phenotype. Four major additive QTL from these three methods had high concordance found in 64.1 to 64.9Mb for Bos taurus autosome (BTA) 7 for WWT, 24.3 to 25.4Mb for BTA14 for CWT, 0.5 to 1.5Mb for BTA6 for BFT and 26.3 to 33.4Mb for BTA29 for BFT. Several candidate genes (i.e. glutamate receptor, ionotropic, ampa 1 [GRIA1], family with sequence similarity 110, member B [FAM110B], and thymocyte selection-associated high mobility group box [TOX]) may be identified close to these QTL. Our result suggests that the use of different linkage disequilibrium mapping approaches can provide more reliable chromosome regions to further pinpoint DNA makers or causative genes in these regions.

  15. Comparing Methods for Item Analysis: The Impact of Different Item-Selection Statistics on Test Difficulty

    ERIC Educational Resources Information Center

    Jones, Andrew T.

    2011-01-01

    Practitioners often depend on item analysis to select items for exam forms and have a variety of options available to them. These include the point-biserial correlation, the agreement statistic, the B index, and the phi coefficient. Although research has demonstrated that these statistics can be useful for item selection, no research as of yet has…

  16. The T(ea) Test: Scripted Stories Increase Statistical Method Selection Skills

    ERIC Educational Resources Information Center

    Hackathorn, Jana; Ashdown, Brien

    2015-01-01

    To teach statistics, teachers must attempt to overcome pedagogical obstacles, such as dread, anxiety, and boredom. There are many options available to teachers that facilitate a pedagogically conducive environment in the classroom. The current study examined the effectiveness of incorporating scripted stories and humor into statistical method…

  17. An Expressed Preference Determination of College Students' Valuation of Statistical Lives: Methods and Implications

    ERIC Educational Resources Information Center

    Brady, Kevin L.

    2008-01-01

    Government agencies typically apply a general value of statistical life (VSL) estimate when performing cost-benefit analysis (CBA). However, theory suggests that college students attach a value to statistical lives that differs from society's VSL; therefore, CBA may lead to inefficient levels of risk reduction among students. A contingent…

  18. USING STATISTICAL METHODS FOR WATER QUALITY MANAGEMENT: ISSUES, PROBLEMS AND SOLUTIONS

    EPA Science Inventory

    This book is readable, comprehensible and I anticipate, usable. The author has an enthusiasm which comes out in the text. Statistics is presented as a living breathing subject, still being debated, defined, and refined. This statistics book actually has examples in the field...

  19. On the Risk-Equivalence of Two Methods of Randomization in Statistics

    ERIC Educational Resources Information Center

    Kirschner, H. P.

    1976-01-01

    Considers the problem of risk-equivalence of two statistical procedures for statistical decision problems. The crucial argument is based on rewriting risk-equivalence in terms of Choquet's integral representation theorem. It is shown that for certain special cases that do not fulfill the assumptions of the Main Theorem, risk-equivalence holds at…

  20. Comparing Trend and Gap Statistics across Tests: Distributional Change Using Ordinal Methods and Bayesian Inference

    ERIC Educational Resources Information Center

    Denbleyker, John Nickolas

    2012-01-01

    The shortcomings of the proportion above cut (PAC) statistic used so prominently in the educational landscape renders it a very problematic measure for making correct inferences with student test data. The limitations of PAC-based statistics are more pronounced with cross-test comparisons due to their dependency on cut-score locations. A better…

  1. An Inferential Confidence Interval Method of Establishing Statistical Equivalence that Corrects Tryon's (2001) Reduction Factor

    ERIC Educational Resources Information Center

    Tryon, Warren W.; Lewis, Charles

    2008-01-01

    Evidence of group matching frequently takes the form of a nonsignificant test of statistical difference. Theoretical hypotheses of no difference are also tested in this way. These practices are flawed in that null hypothesis statistical testing provides evidence against the null hypothesis and failing to reject H[subscript 0] is not evidence…

  2. Beyond Statistical Methods: Teaching Critical Thinking to First-Year University Students

    ERIC Educational Resources Information Center

    David, Irene; Brown, Jennifer Ann

    2012-01-01

    We discuss a major change in the way we teach our first-year statistics course. We have redesigned this course with emphasis on teaching critical thinking. We recognized that most of the students take the course for general knowledge and support of other majors, and very few are planning to major in statistics. We identified the essential aspects…

  3. Statistical methods for biodosimetry in the presence of both Berkson and classical measurement error

    NASA Astrophysics Data System (ADS)

    Miller, Austin

    In radiation epidemiology, the true dose received by those exposed cannot be assessed directly. Physical dosimetry uses a deterministic function of the source term, distance and shielding to estimate dose. For the atomic bomb survivors, the physical dosimetry system is well established. The classical measurement errors plaguing the location and shielding inputs to the physical dosimetry system are well known. Adjusting for the associated biases requires an estimate for the classical measurement error variance, for which no data-driven estimate exists. In this case, an instrumental variable solution is the most viable option to overcome the classical measurement error indeterminacy. Biological indicators of dose may serve as instrumental variables. Specification of the biodosimeter dose-response model requires identification of the radiosensitivity variables, for which we develop statistical definitions and variables. More recently, researchers have recognized Berkson error in the dose estimates, introduced by averaging assumptions for many components in the physical dosimetry system. We show that Berkson error induces a bias in the instrumental variable estimate of the dose-response coefficient, and then address the estimation problem. This model is specified by developing an instrumental variable mixed measurement error likelihood function, which is then maximized using a Monte Carlo EM Algorithm. These methods produce dose estimates that incorporate information from both physical and biological indicators of dose, as well as the first instrumental variable based data-driven estimate for the classical measurement error variance.

  4. Spiked proteomic standard dataset for testing label-free quantitative software and statistical methods.

    PubMed

    Ramus, Claire; Hovasse, Agnès; Marcellin, Marlène; Hesse, Anne-Marie; Mouton-Barbosa, Emmanuelle; Bouyssié, David; Vaca, Sebastian; Carapito, Christine; Chaoui, Karima; Bruley, Christophe; Garin, Jérôme; Cianférani, Sarah; Ferro, Myriam; Dorssaeler, Alain Van; Burlet-Schiltz, Odile; Schaeffer, Christine; Couté, Yohann; Gonzalez de Peredo, Anne

    2016-03-01

    This data article describes a controlled, spiked proteomic dataset for which the "ground truth" of variant proteins is known. It is based on the LC-MS analysis of samples composed of a fixed background of yeast lysate and different spiked amounts of the UPS1 mixture of 48 recombinant proteins. It can be used to objectively evaluate bioinformatic pipelines for label-free quantitative analysis, and their ability to detect variant proteins with good sensitivity and low false discovery rate in large-scale proteomic studies. More specifically, it can be useful for tuning software tools parameters, but also testing new algorithms for label-free quantitative analysis, or for evaluation of downstream statistical methods. The raw MS files can be downloaded from ProteomeXchange with identifier PXD001819. Starting from some raw files of this dataset, we also provide here some processed data obtained through various bioinformatics tools (including MaxQuant, Skyline, MFPaQ, IRMa-hEIDI and Scaffold) in different workflows, to exemplify the use of such data in the context of software benchmarking, as discussed in details in the accompanying manuscript [1]. The experimental design used here for data processing takes advantage of the different spike levels introduced in the samples composing the dataset, and processed data are merged in a single file to facilitate the evaluation and illustration of software tools results for the detection of variant proteins with different absolute expression levels and fold change values.

  5. A statistical method to estimate outflow volume in case of levee breach due to overtopping

    NASA Astrophysics Data System (ADS)

    Brandimarte, Luigia; Martina, Mario; Dottori, Francesco; Mazzoleni, Maurizio

    2015-04-01

    The aim of this study is to propose a statistical method to assess the outflowing water volume through a levee breach, due to overtopping, in case of three different types of grass cover quality. The first step in the proposed methodology is the definition of the reliability function, a the relation between loading and resistance conditions on the levee system, in case of overtopping. Secondly, the fragility curve, which relates the probability of failure with loading condition over the levee system, is estimated having defined the stochastic variables in the reliability function. Thus, different fragility curves are assessed in case of different scenarios of grass cover quality. Then, a levee breach model is implemented and combined with a 1D hydrodynamic model in order to assess the outflow hydrograph given the water level in the main channel and stochastic values of the breach width. Finally, the water volume is estimated as a combination of the probability density function of the breach width and levee failure. The case study is located in the in 98km-braided reach of Po River, Italy, between the cross-sections of Cremona and Borgoforte. The analysis showed how different counter measures, different grass cover quality in this case, can reduce the probability of failure of the levee system. In particular, for a given values of breach width good levee cover qualities can significantly reduce the outflowing water volume, compared to bad cover qualities, inducing a consequent lower flood risk within the flood-prone area.

  6. Integrating Symbolic and Statistical Methods for Testing Intelligent Systems Applications to Machine Learning and Computer Vision

    SciTech Connect

    Jha, Sumit Kumar; Pullum, Laura L; Ramanathan, Arvind

    2016-01-01

    Embedded intelligent systems ranging from tiny im- plantable biomedical devices to large swarms of autonomous un- manned aerial systems are becoming pervasive in our daily lives. While we depend on the flawless functioning of such intelligent systems, and often take their behavioral correctness and safety for granted, it is notoriously difficult to generate test cases that expose subtle errors in the implementations of machine learning algorithms. Hence, the validation of intelligent systems is usually achieved by studying their behavior on representative data sets, using methods such as cross-validation and bootstrapping.In this paper, we present a new testing methodology for studying the correctness of intelligent systems. Our approach uses symbolic decision procedures coupled with statistical hypothesis testing to. We also use our algorithm to analyze the robustness of a human detection algorithm built using the OpenCV open-source computer vision library. We show that the human detection implementation can fail to detect humans in perturbed video frames even when the perturbations are so small that the corresponding frames look identical to the naked eye.

  7. An Efficient Augmented Lagrangian Method for Statistical X-Ray CT Image Reconstruction

    PubMed Central

    Li, Jiaojiao; Niu, Shanzhou; Huang, Jing; Bian, Zhaoying; Feng, Qianjin; Yu, Gaohang; Liang, Zhengrong; Chen, Wufan; Ma, Jianhua

    2015-01-01

    Statistical iterative reconstruction (SIR) for X-ray computed tomography (CT) under the penalized weighted least-squares criteria can yield significant gains over conventional analytical reconstruction from the noisy measurement. However, due to the nonlinear expression of the objective function, most exiting algorithms related to the SIR unavoidably suffer from heavy computation load and slow convergence rate, especially when an edge-preserving or sparsity-based penalty or regularization is incorporated. In this work, to address abovementioned issues of the general algorithms related to the SIR, we propose an adaptive nonmonotone alternating direction algorithm in the framework of augmented Lagrangian multiplier method, which is termed as “ALM-ANAD”. The algorithm effectively combines an alternating direction technique with an adaptive nonmonotone line search to minimize the augmented Lagrangian function at each iteration. To evaluate the present ALM-ANAD algorithm, both qualitative and quantitative studies were conducted by using digital and physical phantoms. Experimental results show that the present ALM-ANAD algorithm can achieve noticeable gains over the classical nonlinear conjugate gradient algorithm and state-of-the-art split Bregman algorithm in terms of noise reduction, contrast-to-noise ratio, convergence rate, and universal quality index metrics. PMID:26495975

  8. Statistical methods for identifying and bounding a UXO target area or minefield

    SciTech Connect

    McKinstry, Craig A.; Pulsipher, Brent A.; Gilbert, Richard O.; H. Sahli, A.M. Bottoms, J. Cornelis

    2003-09-18

    The sampling unit for minefield or UXO area characterization is typically represented by a geographical block or transect swath that lends itself to characterization by geophysical instrumentation such as mobile sensor arrays. New spatially based statistical survey methods and tools, more appropriate for these unique sampling units have been developed and implemented at PNNL (Visual Sample Plan software, ver. 2.0) with support from the US Department of Defense. Though originally developed to support UXO detection and removal efforts, these tools may also be used in current form or adapted to support demining efforts and aid in the development of new sensors and detection technologies by explicitly incorporating both sampling and detection error in performance assessments. These tools may be used to (1) determine transect designs for detecting and bounding target areas of critical size, shape, and density of detectable items of interest with a specified confidence probability, (2) evaluate the probability that target areas of a specified size, shape and density have not been missed by a systematic or meandering transect survey, and (3) support post-removal verification by calculating the number of transects required to achieve a specified confidence probability that no UXO or mines have been missed.

  9. Chemical indices and methods of multivariate statistics as a tool for odor classification.

    PubMed

    Mahlke, Ingo T; Thiesen, Peter H; Niemeyer, Bernd

    2007-04-01

    Industrial and agricultural off-gas streams are comprised of numerous volatile compounds, many of which have substantially different odorous properties. State-of-the-art waste-gas treatment includes the characterization of these molecules and is directed at, if possible, either the avoidance of such odorants during processing or the use of existing standardized air purification techniques like bioscrubbing or afterburning, which however, often show low efficiency under ecological and economical regards. Selective odor separation from the off-gas streams could ease many of these disadvantages but is not yet widely applicable. Thus, the aim of this paper is to identify possible model substances in selective odor separation research from 155 volatile molecules mainly originating from livestock facilities, fat refineries, and cocoa and coffee production by knowledge-based methods. All compounds are examined with regard to their structure and information-content using topological and information-theoretical indices. Resulting data are fitted in an observation matrix, and similarities between the substances are computed. Principal component analysis and k-means cluster analysis are conducted showing that clustering of indices data can depict odor information correlating well to molecular composition and molecular shape. Quantitative molecule describtion along with the application of such statistical means therefore provide a good classification tool of malodorant structure properties with no thermodynamic data needed. The approximate look-alike shape of odorous compounds within the clusters suggests a fair choice of possible model molecules.

  10. Foundations of statistical methods for multiple sequence alignment and structure prediction

    SciTech Connect

    Lawrence, C.

    1995-12-31

    Statistical algorithms have proven to be useful in computational molecular biology. Many statistical problems are most easily addressed by pretending that critical missing data are available. For some problems statistical inference in facilitated by creating a set of latent variables, none of whose variables are observed. A key observation is that conditional probabilities for the values of the missing data can be inferred by application of Bayes theorem to the observed data. The statistical framework described in this paper employs Boltzmann like models, permutated data likelihood, EM, and Gibbs sampler algorithms. This tutorial reviews the common statistical framework behind all of these algorithms largely in tabular or graphical terms, illustrates its application, and describes the biological underpinnings of the models used.

  11. Predictive analysis of beer quality by correlating sensory evaluation with higher alcohol and ester production using multivariate statistics methods.

    PubMed

    Dong, Jian-Jun; Li, Qing-Liang; Yin, Hua; Zhong, Cheng; Hao, Jun-Guang; Yang, Pan-Fei; Tian, Yu-Hong; Jia, Shi-Ru

    2014-10-15

    Sensory evaluation is regarded as a necessary procedure to ensure a reproducible quality of beer. Meanwhile, high-throughput analytical methods provide a powerful tool to analyse various flavour compounds, such as higher alcohol and ester. In this study, the relationship between flavour compounds and sensory evaluation was established by non-linear models such as partial least squares (PLS), genetic algorithm back-propagation neural network (GA-BP), support vector machine (SVM). It was shown that SVM with a Radial Basis Function (RBF) had a better performance of prediction accuracy for both calibration set (94.3%) and validation set (96.2%) than other models. Relatively lower prediction abilities were observed for GA-BP (52.1%) and PLS (31.7%). In addition, the kernel function of SVM played an essential role of model training when the prediction accuracy of SVM with polynomial kernel function was 32.9%. As a powerful multivariate statistics method, SVM holds great potential to assess beer quality.

  12. GPU-accelerated Direct Sampling method for multiple-point statistical simulation

    NASA Astrophysics Data System (ADS)

    Huang, Tao; Li, Xue; Zhang, Ting; Lu, De-Tang

    2013-08-01

    Geostatistical simulation techniques have become a widely used tool for the modeling of oil and gas reservoirs and the assessment of uncertainty. The Direct Sampling (DS) algorithm is a recent multiple-point statistical simulation technique. It directly samples the training image (TI) during the simulation process by calculating distances between the TI patterns and the given data events found in the simulation grid (SG). Omitting the prior storage of all the TI patterns in a database, the DS algorithm can be used to simulate categorical, continuous and multivariate variables. Three fundamental input parameters are required for the definition of DS applications: the number of neighbors n, the acceptance threshold t and the fraction of the TI to scan f. For very large grids and complex spatial models with more severe parameter restrictions, the computational costs in terms of simulation time often become the bottleneck of practical applications. This paper focuses on an innovative implementation of the Direct Sampling method which exploits the benefits of graphics processing units (GPUs) to improve computational performance. Parallel schemes are applied to deal with two of the DS input parameters, n and f. Performance tests are carried out with large 3D grid size and the results are compared with those obtained based on the simulations with central processing units (CPU). The comparison indicates that the use of GPUs reduces the computation time by a factor of 10X-100X depending on the input parameters. Moreover, the concept of the search ellipsoid can be conveniently combined with the flexible data template of the DS method, and our experimental results of sand channels reconstruction show that it can improve the reproduction of the long-range connectivity patterns.

  13. "Geo-statistics methods and neural networks in geophysical applications: A case study"

    NASA Astrophysics Data System (ADS)

    Rodriguez Sandoval, R.; Urrutia Fucugauchi, J.; Ramirez Cruz, L. C.

    2008-12-01

    The study is focus in the Ebano-Panuco basin of northeastern Mexico, which is being explored for hydrocarbon reservoirs. These reservoirs are in limestones and there is interest in determining porosity and permeability in the carbonate sequences. The porosity maps presented in this study are estimated from application of multiattribute and neural networks techniques, which combine geophysics logs and 3-D seismic data by means of statistical relationships. The multiattribute analysis is a process to predict a volume of any underground petrophysical measurement from well-log and seismic data. The data consist of a series of target logs from wells which tie a 3-D seismic volume. The target logs are neutron porosity logs. From the 3-D seismic volume a series of sample attributes is calculated. The objective of this study is to derive a set of attributes and the target log values. The selected set is determined by a process of forward stepwise regression. The analysis can be linear or nonlinear. In the linear mode the method consists of a series of weights derived by least-square minimization. In the nonlinear mode, a neural network is trained using the select attributes as inputs. In this case we used a probabilistic neural network PNN. The method is applied to a real data set from PEMEX. For better reservoir characterization the porosity distribution was estimated using both techniques. The case shown a continues improvement in the prediction of the porosity from the multiattribute to the neural network analysis. The improvement is in the training and the validation, which are important indicators of the reliability of the results. The neural network showed an improvement in resolution over the multiattribute analysis. The final maps provide more realistic results of the porosity distribution.

  14. Meta-analysis as Statistical and Analytical Method of Journal’s Content Scientific Evaluation

    PubMed Central

    Masic, Izet; Begic, Edin

    2015-01-01

    Introduction: A meta-analysis is a statistical and analytical method which combines and synthesizes different independent studies and integrates their results into one common result. Goal: Analysis of the journals “Medical Archives”, “Materia Socio Medica” and “Acta Informatica Medica”, which are located in the most eminent indexed databases of the biomedical milieu. Material and methods: The study has retrospective and descriptive character, and included the period of the calendar year 2014. Study included six editions of all three journals (total of 18 journals). Results: In this period was published a total of 291 articles (in the “Medical Archives” 110, “Materia Socio Medica” 97, and in “Acta Informatica Medica” 84). The largest number of articles was original articles. Small numbers have been published as professional, review articles and case reports. Clinical events were most common in the first two journals, while in the journal “Acta Informatica Medica” belonged to the field of medical informatics, as part of pre-clinical medical disciplines. Articles are usually required period of fifty to fifty nine days for review. Articles were received from four continents, mostly from Europe. The authors are most often from the territory of Bosnia and Herzegovina, then Iran, Kosovo and Macedonia. Conclusion: The number of articles published each year is increasing, with greater participation of authors from different continents and abroad. Clinical medical disciplines are the most common, with the broader spectrum of topics and with a growing number of original articles. Greater support of the wider scientific community is needed for further development of all three of the aforementioned journals. PMID:25870484

  15. An efficient enantioselective method for asymmetric Michael addition of nitroalkanes to alpha,beta-unsaturated aldehydes.

    PubMed

    Wang, Yongcan; Li, Pengfei; Liang, Xinmiao; Zhang, Tony Y; Ye, Jinxing

    2008-03-14

    The addition of nitroalkanes to alpha,beta-unsaturated aldehydes under the catalysis of (S)-2-(diphenyl(trimethylsilyloxy)methyl)pyrrolidine and lithium acetate as additive afforded gamma-nitroaldehydes in good yield and up to 97% ee.

  16. Deriving boundary layer mixing height from LIDAR measurements using a Bayesian statistical inference method.

    NASA Astrophysics Data System (ADS)

    Riccio, A.; Caporaso, L.; di Giuseppe, F.; Bonafè, G.; Gobbi, G. P.; Angelini, A.

    2010-09-01

    The nowadays availability of low-cost commercial LIDAR/ceilometer, provides the opportunity to widely employ these active instruments to furnish continuous observation of the planetary boundary layer (PBL) evolution which could serve the scope of both air-quality model initialization and numerical weather prediction system evaluation. Their range-corrected signal is in fact proportional to the aerosol backscatter cross section, and therefore, in clear conditions, it allows to track the PBL evolution using aerosols as markers. The LIDAR signal is then processed to retrieve an estimate of the PBL mixing height. A standard approach uses the so called wavelet covariance transform (WCT) method which consists in the convolution of the vertical signal with a step function, which is able to detect local discontinuities in the backscatter profile. There are, nevertheless, several drawbacks which have to be considered when the WCT method is employed. Since water droplets may have a very large extinction and backscattering cross section, the presence of rain, clouds or fog decreases the returning signal causing interference and uncertainties in the mixing height retrievals. Moreover, if vertical mixing is scarce, aerosols remain suspended in a persistent residual layer which is detected even if it is not significantly connected to the actual mixing height. Finally, multiple layers are also cause of uncertainties. In this work we present a novel methodology to infer the height of planetary boundary layers (PBLs) from LIDAR data which corrects the unrealistic fluctuations introduced by the WCT method. It implements the assimilation of WCT-PBL heights estimations into a Bayesian statistical inference procedure which includes a physical model for the boundary layer (bulk model) as the first guess hypothesis. A hierarchical Bayesian Markov chain Monte Carlo (MCMC) approach is then used to explore the posterior state space and calculate the data likelihood of previously assigned

  17. Examination of two methods for statistical analysis of data with magnitude and direction emphasizing vestibular research applications

    NASA Technical Reports Server (NTRS)

    Calkins, D. S.

    1998-01-01

    When the dependent (or response) variable response variable in an experiment has direction and magnitude, one approach that has been used for statistical analysis involves splitting magnitude and direction and applying univariate statistical techniques to the components. However, such treatment of quantities with direction and magnitude is not justifiable mathematically and can lead to incorrect conclusions about relationships among variables and, as a result, to flawed interpretations. This note discusses a problem with that practice and recommends mathematically correct procedures to be used with dependent variables that have direction and magnitude for 1) computation of mean values, 2) statistical contrasts of and confidence intervals for means, and 3) correlation methods.

  18. Statistical Diversions

    ERIC Educational Resources Information Center

    Petocz, Peter; Sowey, Eric

    2008-01-01

    In this article, the authors focus on hypothesis testing--that peculiarly statistical way of deciding things. Statistical methods for testing hypotheses were developed in the 1920s and 1930s by some of the most famous statisticians, in particular Ronald Fisher, Jerzy Neyman and Egon Pearson, who laid the foundations of almost all modern methods of…

  19. Numerical Method for the Design of Healing Chamber in Additive-Manufactured Dental Implants.

    PubMed

    Lee, Hsiao-Chien; Tsai, Pei-I; Huang, Chih-Chieh; Chen, San-Yuan; Chao, Chuen-Guang; Tsou, Nien-Ti

    2017-01-01

    The inclusion of a healing chamber in dental implants has been shown to promote biological healing. In this paper, a novel numerical approach to the design of the healing chamber for additive-manufactured dental implants is proposed. This study developed an algorithm for the modeling of bone growth and employed finite element method in ANSYS to facilitate the design of healing chambers with a highly complex configuration. The model was then applied to the design of dental implants for insertion into the posterior maxillary bones. Two types of ITI® solid cylindrical screwed implant with extra rectangular-shaped healing chamber as an initial design are adopted, with which to evaluate the proposed system. This resulted in several configurations for the healing chamber, which were then evaluated based on the corresponding volume fraction of healthy surrounding bone. The best of these implants resulted in a healing chamber surrounded by around 9.2% more healthy bone than that obtained from the original design. The optimal design increased the contact area between the bone and implant by around 52.9%, which is expected to have a significant effect on osseointegration. The proposed approach is highly efficient which typically completes the optimization of each implant within 3-5 days on an ordinary personal computer. It is also sufficiently general to permit extension to various loading conditions.

  20. Numerical Method for the Design of Healing Chamber in Additive-Manufactured Dental Implants

    PubMed Central

    Lee, Hsiao-Chien; Tsai, Pei-I; Huang, Chih-Chieh; Chen, San-Yuan; Chao, Chuen-Guang

    2017-01-01

    The inclusion of a healing chamber in dental implants has been shown to promote biological healing. In this paper, a novel numerical approach to the design of the healing chamber for additive-manufactured dental implants is proposed. This study developed an algorithm for the modeling of bone growth and employed finite element method in ANSYS to facilitate the design of healing chambers with a highly complex configuration. The model was then applied to the design of dental implants for insertion into the posterior maxillary bones. Two types of ITI® solid cylindrical screwed implant with extra rectangular-shaped healing chamber as an initial design are adopted, with which to evaluate the proposed system. This resulted in several configurations for the healing chamber, which were then evaluated based on the corresponding volume fraction of healthy surrounding bone. The best of these implants resulted in a healing chamber surrounded by around 9.2% more healthy bone than that obtained from the original design. The optimal design increased the contact area between the bone and implant by around 52.9%, which is expected to have a significant effect on osseointegration. The proposed approach is highly efficient which typically completes the optimization of each implant within 3–5 days on an ordinary personal computer. It is also sufficiently general to permit extension to various loading conditions. PMID:28293628

  1. Lactic Acid Fermentation, Urea and Lime Addition: Promising Faecal Sludge Sanitizing Methods for Emergency Sanitation

    PubMed Central

    Anderson, Catherine; Malambo, Dennis Hanjalika; Gonzalez Perez, Maria Eliette; Nobela, Happiness Ngwanamoseka; de Pooter, Lobke; Spit, Jan; Hooijmans, Christine Maria; van de Vossenberg, Jack; Greya, Wilson; Thole, Bernard; van Lier, Jules B.; Brdjanovic, Damir

    2015-01-01

    In this research, three faecal sludge sanitizing methods—lactic acid fermentation, urea treatment and lime treatment—were studied for application in emergency situations. These methods were investigated by undertaking small scale field trials with pit latrine sludge in Blantyre, Malawi. Hydrated lime was able to reduce the E. coli count in the sludge to below the detectable limit within 1 h applying a pH > 11 (using a dosage from 7% to 17% w/w, depending faecal sludge alkalinity), urea treatment required about 4 days using 2.5% wet weight urea addition, and lactic acid fermentation needed approximately 1 week after being dosed with 10% wet weight molasses (2 g (glucose/fructose)/kg) and 10% wet weight pre-culture (99.8% pasteurised whole milk and 0.02% fermented milk drink containing Lactobacillus casei Shirota). Based on Malawian prices, the cost of sanitizing 1 m3 of faecal sludge was estimated to be €32 for lactic acid fermentation, €20 for urea treatment and €12 for hydrated lime treatment. PMID:26528995

  2. Nonlinearity measurements of solar cells with an LED-based combinatorial flux addition method

    PubMed Central

    Hamadani, Behrang H.; Shore, Andrew; Roller, John; Yoon, Howard W; Campanelli, Mark

    2016-01-01

    We present a light emitting diode (LED)-based system utilizing a combinatorial flux addition method to investigate the nonlinear relationship in solar cells between the output current of the cell and the incident irradiance level. The magnitude of the light flux is controlled by the supplied currents to two LEDs (or two sets of them) in a combinatorial fashion. The signals measured from the cell are arranged within a related overdetermined linear system of equations derived from an appropriately chosen Nth degree polynomial representing the relationship between the measured signals and the incident fluxes. The flux values and the polynomial coefficients are then solved for by linear least squares to obtain the best fit. The technique can be applied to any solar cell, under either monochromatic or broadband spectrum. For the unscaled solution, no reference detectors or prior calibrations of the light flux are required. However, if at least one calibrated irradiance value is known, then the entire curve can be scaled to an appropriate spectral responsivity value. Using this technique, a large number of data points can be obtained in a relatively short time scale over a large signal range. PMID:27524837

  3. Nonlinearity measurements of solar cells with an LED-based combinatorial flux addition method.

    PubMed

    Hamadani, Behrang H; Shore, Andrew; Roller, John; Yoon, Howard W; Campanelli, Mark

    2016-02-01

    We present a light emitting diode (LED)-based system utilizing a combinatorial flux addition method to investigate the nonlinear relationship in solar cells between the output current of the cell and the incident irradiance level. The magnitude of the light flux is controlled by the supplied currents to two LEDs (or two sets of them) in a combinatorial fashion. The signals measured from the cell are arranged within a related overdetermined linear system of equations derived from an appropriately chosen N(th) degree polynomial representing the relationship between the measured signals and the incident fluxes. The flux values and the polynomial coefficients are then solved for by linear least squares to obtain the best fit. The technique can be applied to any solar cell, under either monochromatic or broadband spectrum. For the unscaled solution, no reference detectors or prior calibrations of the light flux are required. However, if at least one calibrated irradiance value is known, then the entire curve can be scaled to an appropriate spectral responsivity value. Using this technique, a large number of data points can be obtained in a relatively short time scale over a large signal range.

  4. Stable solidification of cesium with an allophane additive by a pressing/sintering method

    NASA Astrophysics Data System (ADS)

    Zhang, Xiaoxia; Wu, Yan; Wei, Yuezhou; Mimura, Hitoshi; Matsukura, Minoru

    2017-03-01

    Pyrolysis of AMP/SiO2 adsorbed Cs (AMP-Cs/SiO2) occurred at > 400 °C sintering temperature, and Cs immobilisation decreased from 100% to 40% after sintering at 1200 °C. To safely dispose radioactive Cs, allophane was immobilized with AMP-Cs/SiO2 to prepare a stable form by using a pressing/sintering method. The structure of AMP-Cs/SiO2 collapsed, and cesium aluminosilicate formed more easily under conditions of higher sintering temperature (>800 °C) or increasing mixing ratio of allophane (mass ratio = 1:3 AMP-Cs/SiO2-allophane). The decomposition products of AMP-Cs/SiO2 were Cs2O, MoO3 and P2O5 at 1200 °C. Cs2O volatilisation was depressed by allophane addition, and a stable immobilisation phase of Cs4Al4Si20O48 formed. An immobilisation ratio of Cs of approximately 100% was maintained. The leachability of Cs for AMP-Cs/SiO2-allophane (1:3, 1200 °C) in distilled water at 25 °C and 90 °C for 15 days was estimated as 0.174% and 1.55%, respectively.

  5. Statistical prediction of dynamic distortion of inlet flow using minimum dynamic measurement. An application to the Melick statistical method and inlet flow dynamic distortion prediction without RMS measurements

    NASA Technical Reports Server (NTRS)

    Schweikhard, W. G.; Chen, Y. S.

    1986-01-01

    The Melick method of inlet flow dynamic distortion prediction by statistical means is outlined. A hypothetic vortex model is used as the basis for the mathematical formulations. The main variables are identified by matching the theoretical total pressure rms ratio with the measured total pressure rms ratio. Data comparisons, using the HiMAT inlet test data set, indicate satisfactory prediction of the dynamic peak distortion for cases with boundary layer control device vortex generators. A method for the dynamic probe selection was developed. Validity of the probe selection criteria is demonstrated by comparing the reduced-probe predictions with the 40-probe predictions. It is indicated that the the number of dynamic probes can be reduced to as few as two and still retain good accuracy.

  6. Multivariate statistical data analysis methods for detecting baroclinic wave interactions in the thermally driven rotating annulus

    NASA Astrophysics Data System (ADS)

    von Larcher, Thomas; Harlander, Uwe; Alexandrov, Kiril; Wang, Yongtai

    2010-05-01

    Experiments on baroclinic wave instabilities in a rotating cylindrical gap have been long performed, e.g., to unhide regular waves of different zonal wave number, to better understand the transition to the quasi-chaotic regime, and to reveal the underlying dynamical processes of complex wave flows. We present the application of appropriate multivariate data analysis methods on time series data sets acquired by the use of non-intrusive measurement techniques of a quite different nature. While the high accurate Laser-Doppler-Velocimetry (LDV ) is used for measurements of the radial velocity component at equidistant azimuthal positions, a high sensitive thermographic camera measures the surface temperature field. The measurements are performed at particular parameter points, where our former studies show that kinds of complex wave patterns occur [1, 2]. Obviously, the temperature data set has much more information content as the velocity data set due to the particular measurement techniques. Both sets of time series data are analyzed by using multivariate statistical techniques. While the LDV data sets are studied by applying the Multi-Channel Singular Spectrum Analysis (M - SSA), the temperature data sets are analyzed by applying the Empirical Orthogonal Functions (EOF ). Our goal is (a) to verify the results yielded with the analysis of the velocity data and (b) to compare the data analysis methods. Therefor, the temperature data are processed in a way to become comparable to the LDV data, i.e. reducing the size of the data set in such a manner that the temperature measurements would imaginary be performed at equidistant azimuthal positions only. This approach initially results in a great loss of information. But applying the M - SSA to the reduced temperature data sets enable us to compare the methods. [1] Th. von Larcher and C. Egbers, Experiments on transitions of baroclinic waves in a differentially heated rotating annulus, Nonlinear Processes in Geophysics

  7. A New Method for Assessing the Statistical Significance in the Differential Functioning of Items and Tests (DFIT) Framework

    ERIC Educational Resources Information Center

    Oshima, T. C.; Raju, Nambury S.; Nanda, Alice O.

    2006-01-01

    A new item parameter replication method is proposed for assessing the statistical significance of the noncompensatory differential item functioning (NCDIF) index associated with the differential functioning of items and tests framework. In this new method, a cutoff score for each item is determined by obtaining a (1-alpha ) percentile rank score…

  8. Zu Problemen statistischer Methoden in der Sprachwissenschaft (Problems of Statistical Methods in Linguistics)

    ERIC Educational Resources Information Center

    Zorn, Klaus

    1973-01-01

    Discussion of statistical apparatus employed in L. Doncheva-Mareva's article on the wide-spread usage of the present and future tense forms with future meaning in German letters, Deutsch als Fremdsprache, n1 1971. (RS)

  9. Recent advances in statistical methods for the estimation of sediment and nutrient transport in rivers

    NASA Astrophysics Data System (ADS)

    Colin, T. A.

    1995-07-01

    This paper reviews advances in methods for estimating fluvial transport of suspended sediment and nutrients. Research from the past four years, mostly dealing with estimating monthly and annual loads, is emphasized. However, because this topic has not appeared in previous IUGG reports, some research prior to 1990 is included. The motivation for studying sediment transport has shifted during the past few decades. In addition to its role in filling reservoirs and channels, sediment is increasingly recognized as an important part of fluvial ecosystems and estuarine wetlands. Many groups want information about sediment transport [Bollman, 1992]: Scientists trying to understand benthic biology and catchment hydrology; citizens and policy-makers concerned about environmental impacts (e.g. impacts of logging [Beschta, 1978] or snow-fences [Sturges, 1992]); government regulators considering the effectiveness of programs to protect in-stream habitat and downstream waterbodies; and resource managers seeking to restore wetlands.

  10. An introduction to epidemiologic and statistical methods useful in environmental epidemiology.

    PubMed

    Nitta, Hiroshi; Yamazaki, Shin; Omori, Takashi; Sato, Tosiya

    2010-01-01

    Many developments in the design and analysis of environmental epidemiology have been made in air pollution studies. In the analysis of the short-term effects of particulate matter on daily mortality, Poisson regression models with flexible smoothing methods have been developed for the analysis of time-series data. Another option for such studies is the use of case-crossover designs, and there have been extensive discussions on the selection of control periods. In the Study on Respiratory Disease and Automobile Exhaust project conducted by the Japanese Ministry of the Environment, we adopted a new 2-stage case-control design that is efficient when both exposure and disease are rare. Based on our experience in conducting air pollution epidemiologic studies, we review 2-stage case-control designs, case-crossover designs, generalized linear models, generalized additive models, and generalized estimating equations, all of which are useful approaches in environmental epidemiology.

  11. The use of a calculus-based cyclone identification method for generating storm statistics

    NASA Astrophysics Data System (ADS)

    Benestad, R. E.; Chen, D.

    2006-08-01

    Maps of 12 hr sea-level pressure (SLP) from the former National Meteotrological Center (NMC) and 24 hr SLP maps from the European Centre for Medium-range Weather Forecasts (ECMWF) 40 yr re-analysis (ERA40) were used to identify extratropical cyclones in the North Atlantic region. A calculus-based cyclone identification (CCI) method is introduced and evaluated, where a multiple regression against a truncated series of sinusoids was used to obtain a Fourier approximation of the north-south and east-west SLP profiles, providing a basis for analytical expressions of the derivatives. Local SLP minima were found from the zero-crossing points of the first-order derivatives for the SLP gradients where the second-order derivatives were greater than zero. Evaluation of cyclone counts indicates a good correspondence with storm track maps and independent monthly large-scale SLP anomalies. The results derived from ERA40 also revealed that the central storm pressure sometimes could be extremely deep in the re-analysis product, and it is not clear whether such outliers are truly representative of the actual events. The position and the depth of the cyclones were subjects for a study of long-term trends in cyclone number for various regions around the North Atlantic. Noting that the re-analyses may contain time-dependent biases due to changes in the observing practises, a tentative positive linear trend, statistically significant at the 10% level, was found in the number of intense storms over the Nordic countries over the period 1955-1994 in both the NMC and the ERA40 data. However, there was no significant trend in the western parts of the North Atlantic where trend analysis derived from NMC and ERA40 yielded different results. The choice of data set had a stronger influence on the results than choices such as the number of harmonics to include or spatial resolution of interpolation.

  12. The evaluation of the statistical monomineral thermobarometric methods for the reconstruction of the lithospheric mantle structure

    NASA Astrophysics Data System (ADS)

    Ashchepkov, I.; Vishnyakova, E.

    2009-04-01

    The modified versions of the thermobarometers for the mantle assemblages were revised sing statistical calibrations on the results of Opx thermobarometry. The modifications suggest the calculation of the Fe# of coexisting olivine Fe#Ol according to the statistical approximations by the regressions obtained from the xenoliths from kimberlite data base including >700 associations. They allow reproduces the Opx based TP estimates and to receive the complete set of the TP values for mantle xenoliths and xenocrysts. For GARNET Three variants of barometer give similar results. The first is published (Ashchepkov, 2006). The second is calculating the Al2O3 from Garnet for Orthopyroxene according to procedure: xCrOpx=Cr2O3/CaO)/FeO/MgO/500 xAlOpx=1/(3875*(exp(Cr2O3^0.2/CaO)-0.3)*CaO/989+16)-XcrOpx Al2O3=xAlOp*24.64/Cr2O3^0.2*CaO/2.+FeO*(ToK-501)/1002 And then it suppose using of the Al2O3 in Opx barometer (McGregor, 1974). The third variant is transformation of the G. Grutter (2006) method by introducing of the influence of temperature. P=40+(Cr2O3)-4.5)*10/3-20/7*CaO+(ToC)*0.0000751*MgO)*CaO+2.45*Cr2O3*(7-xv(5,8)) -Fe*0.5 with the correction for P>55: P=55+(P-55)*55/(1+0.9*P) Average from this three methods give appropriate values comparable with determined with (McGregor,1974) barometer. Temperature are estimating according to transformed Krogh thermometer Fe#Ol_Gar=Fe#Gar/2+(T(K)-1420)*0.000112+0.01 For the deep seated associations P>55 kbar T=T-(0.25/(0.4-0.004*(20-P))-0.38/Ca)*275+51*Ca*Cr2-378*CaO-0.51)-Cr/Ca2*5+Mg/(Fe+0.0001)*17.4 ILMENITE P= ((TiO2-23.)*2.15-(T0-973)/20*MgO*Cr2O3 and next P=(60-P)/6.1+P ToK is determined according to (Taylor et al , 1998) Fe#Ol_Chr =(Fe/(Fe+Mg)ilm -0.35)/2.252-0.0000351*(T(K)-973) CHROMITE The equations for PT estimates with chromite compositions P=Cr/(Cr+Al)*T(K)/14.+Ti*0.10 with the next iteration P=-0.0053*P^2+1.1292*P+5.8059 +0.00135*T(K)*Ti*410-8.2 For P> 57 P=P+(P-57)*2.75 Temperature estimates are according to the O

  13. A habitat suitability model for Chinese sturgeon determined using the generalized additive method

    NASA Astrophysics Data System (ADS)

    Yi, Yujun; Sun, Jie; Zhang, Shanghong

    2016-03-01

    The Chinese sturgeon is a type of large anadromous fish that migrates between the ocean and rivers. Because of the construction of dams, this sturgeon's migration path has been cut off, and this species currently is on the verge of extinction. Simulating suitable environmental conditions for spawning followed by repairing or rebuilding its spawning grounds are effective ways to protect this species. Various habitat suitability models based on expert knowledge have been used to evaluate the suitability of spawning habitat. In this study, a two-dimensional hydraulic simulation is used to inform a habitat suitability model based on the generalized additive method (GAM). The GAM is based on real data. The values of water depth and velocity are calculated first via the hydrodynamic model and later applied in the GAM. The final habitat suitability model is validated using the catch per unit effort (CPUEd) data of 1999 and 2003. The model results show that a velocity of 1.06-1.56 m/s and a depth of 13.33-20.33 m are highly suitable ranges for the Chinese sturgeon to spawn. The hydraulic habitat suitability indexes (HHSI) for seven discharges (4000; 9000; 12,000; 16,000; 20,000; 30,000; and 40,000 m3/s) are calculated to evaluate integrated habitat suitability. The results show that the integrated habitat suitability reaches its highest value at a discharge of 16,000 m3/s. This study is the first to apply a GAM to evaluate the suitability of spawning grounds for the Chinese sturgeon. The study provides a reference for the identification of potential spawning grounds in the entire basin.

  14. Possibilities of CT Scanning as Analysis Method in Laser Additive Manufacturing

    NASA Astrophysics Data System (ADS)

    Karme, Aleksis; Kallonen, Aki; Matilainen, Ville-Pekka; Piili, Heidi; Salminen, Antti

    Laser additive manufacturing is an established and constantly developing technique. Structural assessment should be a key component to ensure directed evolution towards higher level of manufacturing. The macroscopic properties of metallic structures are determined by their internal microscopic features, which are difficult to assess using conventional surface measuring methodologies. X-ray microtomography (CT) is a promising technique for three-dimensional non-destructive probing of internal composition and build of various materials. Aim of this study is to define the possibilities of using CT scanning as quality control method in LAM fabricated parts. Since the parts fabricated with LAM are very often used in high quality and accuracy demanding applications in various industries such as medical and aerospace, it is important to be able to define the accuracy of the build parts. The tubular stainless steel test specimens were 3D modelled, manufactured with a modified research AM equipment and imaged after manufacturing with a high-power, high-resolution CT scanner. 3D properties, such as surface texture and the amount and distribution of internal pores, were also evaluated in this study. Surface roughness was higher on the interior wall of the tube, and deviation from the model was systematically directed towards the central axis. Pore distribution showed clear organization and divided into two populations; one following the polygon model seams along both rims, and the other being associated with the concentric and equidistant movement path of the laser. Assessment of samples can enhance the fabrication by guiding the improvement of both modelling and manufacturing process.

  15. Analysis methods for the determination of anthropogenic additions of P to agricultural soils

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Phosphorus additions and measurement in soil is of concern on lands where biosolids have been applied. Colorimetric analysis for plant-available P may be inadequate for the accurate assessment of soil P. Phosphate additions in a regulatory environment need to be accurately assessed as the reported...

  16. First-Grade Methods of Single-Digit Addition with Two or More Addends

    ERIC Educational Resources Information Center

    Guerrero, Shannon M.; Palomaa, Kimberly

    2012-01-01

    In an attempt to further understand connections between children's proficiency and development with single- and multidigit addition, this study investigated the conceptualizations and solution strategies of 26 first-graders presented with several single-digit, multiple addend addition problems. The changes in students' solution strategies over the…

  17. The addition of computer simulated noise to investigate radiation dose and image quality in images with spatial correlation of statistical noise: an example application to X-ray CT of the brain.

    PubMed

    Britten, A J; Crotty, M; Kiremidjian, H; Grundy, A; Adam, E J

    2004-04-01

    This study validates a method to add spatially correlated statistical noise to an image, applied to transaxial X-ray CT images of the head to simulate exposure reduction by up to 50%. 23 patients undergoing routine head CT had three additional slices acquired for validation purposes, two at the same clinical 420 mAs exposure and one at 300 mAs. Images at the level of the cerebrospinal fluid filled ventricles gave readings of noise from a single image, with subtraction of image pairs to obtain noise readings from non-uniform tissue regions. The spatial correlation of the noise was determined and added to the acquired 420 mAs image to simulate images at 340 mAs, 300 mAs, 260 mAs and 210 mAs. Two radiologists assessed the images, finding little difference between the 300 mAs simulated and acquired images. The presence of periventricular low density lesions (PVLD) was used as an example of the effect of simulated dose reduction on diagnostic accuracy, and visualization of the internal capsule was used as a measure of image quality. Diagnostic accuracy for the diagnosis of PVLD did not fall significantly even down to 210 mAs, though visualization of the internal capsule was poorer at lower exposure. Further work is needed to investigate means of measuring statistical noise without the need for uniform tissue areas, or image pairs. This technique has been shown to allow sufficiently accurate simulation of dose reduction and image quality degradation, even when the statistical noise is spatially correlated.

  18. Methods for applying statistical penalties when predicting factors of safety using the Tsai-Wu failure criterion

    NASA Astrophysics Data System (ADS)

    Richardson, D. E.; Regl, R. R.; Iverson, M. P.; Phipps, B. E.

    1993-06-01

    Engineers are often required to estimate safety factors for structures using statistically based allowable stresses. Several approaches for making such estimations are possible. Commonly, the Tsai-Wu failure criterion is used for composite materials. If the quadratic failure criterion proposed by S.W. Tsai and E.M. Wu is used with statistically penalized allowable stress levels, unrealistic results are possible unless the penalties are assessed carefully. Some approaches used in calculating safety factors can predict that the statistically determined allowable stress levels are greater than mean failure levels. Other methods predict that, under severe conditions, the penalized failure surface does not circumscribe the origin (i.e., the unloaded state would not be allowed). It is therefore important that designers and analysts take care when choosing an approach for predicting safety factors using statistically penalized data.

  19. What weather variables are important in predicting heat-related mortality? A new application of statistical learning methods

    PubMed Central

    Zhang, Kai; Li, Yun; Schwartz, Joel D.; O'Neill, Marie S.

    2014-01-01

    Hot weather increases risk of mortality. Previous studies used different sets of weather variables to characterize heat stress, resulting in variation in heat-mortality- associations depending on the metric used. We employed a statistical learning method – random forests – to examine which of various weather variables had the greatest impact on heat-related mortality. We compiled a summertime daily weather and mortality counts dataset from four U.S. cities (Chicago, IL; Detroit, MI; Philadelphia, PA; and Phoenix, AZ) from 1998 to 2006. A variety of weather variables were ranked in predicting deviation from typical daily all-cause and cause-specific death counts. Ranks of weather variables varied with city and health outcome. Apparent temperature appeared to be the most important predictor of heat-related mortality for all-cause mortality. Absolute humidity was, on average, most frequently selected one of the top variables for all-cause mortality and seven cause-specific mortality categories. Our analysis affirms that apparent temperature is a reasonable variable for activating heat alerts and warnings, which are commonly based on predictions of total mortality in next few days. Additionally, absolute humidity should be included in future heat-health studies. Finally, random forests can be used to guide choice of weather variables in heat epidemiology studies. PMID:24834832

  20. What weather variables are important in predicting heat-related mortality? A new application of statistical learning methods.

    PubMed

    Zhang, Kai; Li, Yun; Schwartz, Joel D; O'Neill, Marie S

    2014-07-01

    Hot weather increases risk of mortality. Previous studies used different sets of weather variables to characterize heat stress, resulting in variation in heat-mortality associations depending on the metric used. We employed a statistical learning method - random forests - to examine which of the various weather variables had the greatest impact on heat-related mortality. We compiled a summertime daily weather and mortality counts dataset from four U.S. cities (Chicago, IL; Detroit, MI; Philadelphia, PA; and Phoenix, AZ) from 1998 to 2006. A variety of weather variables were ranked in predicting deviation from typical daily all-cause and cause-specific death counts. Ranks of weather variables varied with city and health outcome. Apparent temperature appeared to be the most important predictor of heat-related mortality for all-cause mortality. Absolute humidity was, on average, most frequently selected as one of the top variables for all-cause mortality and seven cause-specific mortality categories. Our analysis affirms that apparent temperature is a reasonable variable for activating heat alerts and warnings, which are commonly based on predictions of total mortality in next few days. Additionally, absolute humidity should be included in future heat-health studies. Finally, random forests can be used to guide the choice of weather variables in heat epidemiology studies.

  1. Bifurcated method and apparatus for floating point addition with decreased latency time

    DOEpatents

    Farmwald, Paul M.

    1987-01-01

    Apparatus for decreasing the latency time associated with floating point addition and subtraction in a computer, using a novel bifurcated, pre-normalization/post-normalization approach that distinguishes between differences of floating point exponents.

  2. Statistical analysis of dose heterogeneity in circulating blood: Implications for sequential methods of total body irradiation

    SciTech Connect

    Molloy, Janelle A.

    2010-11-15

    Purpose: Improvements in delivery techniques for total body irradiation (TBI) using Tomotherapy and intensity modulated radiation therapy have been proven feasible. Despite the promise of improved dose conformality, the application of these ''sequential'' techniques has been hampered by concerns over dose heterogeneity to circulating blood. The present study was conducted to provide quantitative evidence regarding the potential clinical impact of this heterogeneity. Methods: Blood perfusion was modeled analytically as possessing linear, sinusoidal motion in the craniocaudal dimension. The average perfusion period for human circulation was estimated to be approximately 78 s. Sequential treatment delivery was modeled as a Gaussian-shaped dose cloud with a 10 cm length that traversed a 183 cm patient length at a uniform speed. Total dose to circulating blood voxels was calculated via numerical integration and normalized to 2 Gy per fraction. Dose statistics and equivalent uniform dose (EUD) were calculated for relevant treatment times, radiobiological parameters, blood perfusion rates, and fractionation schemes. The model was then refined to account for random dispersion superimposed onto the underlying periodic blood flow. Finally, a fully stochastic model was developed using binomial and trinomial probability distributions. These models allowed for the analysis of nonlinear sequential treatment modalities and treatment designs that incorporate deliberate organ sparing. Results: The dose received by individual blood voxels exhibited asymmetric behavior that depended on the coherence among the blood velocity, circulation phase, and the spatiotemporal characteristics of the irradiation beam. Heterogeneity increased with the perfusion period and decreased with the treatment time. Notwithstanding, heterogeneity was less than {+-}10% for perfusion periods less than 150 s. The EUD was compromised for radiosensitive cells, long perfusion periods, and short treatment times

  3. Methods for estimating flow-duration and annual mean-flow statistics for ungaged streams in Oklahoma

    USGS Publications Warehouse

    Esralew, Rachel A.; Smith, S. Jerrod

    2010-01-01

    Flow statistics can be used to provide decision makers with surface-water information needed for activities such as water-supply permitting, flow regulation, and other water rights issues. Flow statistics could be needed at any location along a stream. Most often, streamflow statistics are needed at ungaged sites, where no flow data are available to compute the statistics. Methods are presented in this report for estimating flow-duration and annual mean-flow statistics for ungaged streams in Oklahoma. Flow statistics included the (1) annual (period of record), (2) seasonal (summer-autumn and winter-spring), and (3) 12 monthly duration statistics, including the 20th, 50th, 80th, 90th, and 95th percentile flow exceedances, and the annual mean-flow (mean of daily flows for the period of record). Flow statistics were calculated from daily streamflow information collected from 235 streamflow-gaging stations throughout Oklahoma and areas in adjacent states. A drainage-area ratio method is the preferred method for estimating flow statistics at an ungaged location that is on a stream near a gage. The method generally is reliable only if the drainage-area ratio of the two sites is between 0.5 and 1.5. Regression equations that relate flow statistics to drainage-basin characteristics were developed for the purpose of estimating selected flow-duration and annual mean-flow statistics for ungaged streams that are not near gaging stations on the same stream. Regression equations were developed from flow statistics and drainage-basin characteristics for 113 unregulated gaging stations. Separate regression equations were developed by using U.S. Geological Survey streamflow-gaging stations in regions with similar drainage-basin characteristics. These equations can increase the accuracy of regression equations used for estimating flow-duration and annual mean-flow statistics at ungaged stream locations in Oklahoma. Streamflow-gaging stations were grouped by selected drainage

  4. Short-term predictions by statistical methods in regions of varying dynamical error growth in a chaotic system

    NASA Astrophysics Data System (ADS)

    Mittal, A. K.; Singh, U. P.; Tiwari, A.; Dwivedi, S.; Joshi, M. K.; Tripathi, K. C.

    2015-08-01

    In a nonlinear, chaotic dynamical system, there are typically regions in which an infinitesimal error grows and regions in which it decays. If the observer does not know the evolution law, recourse is taken to non-dynamical methods, which use the past values of the observables to fit an approximate evolution law. This fitting can be local, based on past values in the neighborhood of the present value as in the case of Farmer-Sidorowich (FS) technique, or it can be global, based on all past values, as in the case of Artificial Neural Networks (ANN). Short-term predictions are then made using the approximate local or global mapping so obtained. In this study, the dependence of statistical prediction errors on dynamical error growth rates is explored using the Lorenz-63 model. The regions of dynamical error growth and error decay are identified by the bred vector growth rates or by the eigenvalues of the symmetric Jacobian matrix. The prediction errors by the FS and ANN techniques in these two regions are compared. It is found that the prediction errors by statistical methods do not depend on the dynamical error growth rate. This suggests that errors using statistical methods are independent of the dynamical situation and the statistical methods may be potentially advantageous over dynamical methods in regions of low dynamical predictability.

  5. Generalized net analyte signal standard addition as a novel method for simultaneous determination: application in spectrophotometric determination of some pesticides.

    PubMed

    Asadpour-Zeynali, Karim; Saeb, Elhameh; Vallipour, Javad; Bamorowat, Mehdi

    2014-01-01

    Simultaneous spectrophotometric determination of three neonicotinoid insecticides (acetamiprid, imidacloprid, and thiamethoxam) by a novel method named generalized net analyte signal standard addition method (GNASSAM) in some binary and ternary synthetic mixtures was investigated. For this purpose, standard addition was performed using a single standard solution consisting of a mixture of standards of all analytes. Savings in time and amount of used materials are some of the advantages of this method. All determinations showed appropriate applicability of this method with less than 5% error. This method may be applied for linearly dependent data in the presence of known interferents. The GNASSAM combines the advantages of both the generalized standard addition method and net analyte signal; therefore, it may be a proper alternative for some other multivariate methods.

  6. Further Insight and Additional Inference Methods for Polynomial Regression Applied to the Analysis of Congruence

    ERIC Educational Resources Information Center

    Cohen, Ayala; Nahum-Shani, Inbal; Doveh, Etti

    2010-01-01

    In their seminal paper, Edwards and Parry (1993) presented the polynomial regression as a better alternative to applying difference score in the study of congruence. Although this method is increasingly applied in congruence research, its complexity relative to other methods for assessing congruence (e.g., difference score methods) was one of the…

  7. Application of statistical methods for analyzing the relationship between casting distortion, mold filling, and interfacial heat transfer in sand molds

    SciTech Connect

    Y. A. Owusu

    1999-03-31

    This report presents a statistical method of evaluating geometric tolerances of casting products using point cloud data generated by coordinate measuring machine (CMM) process. The focus of this report is to present a statistical-based approach to evaluate the differences in dimensional and form variations or tolerances of casting products as affected by casting gating system, molding material, casting thickness, and casting orientation at the mold-metal interface. Form parameters such as flatness, parallelism, and other geometric profiles such as angularity, casting length, and height of casting products were obtained and analyzed from CMM point cloud data. In order to relate the dimensional and form errors to the factors under consideration such as flatness and parallelism, a factorial analysis of variance and statistical test means methods were performed to identify the factors that contributed to the casting distortion at the mold-metal interface.

  8. The Flipped Class: A Method to Address the Challenges of an Undergraduate Statistics Course

    ERIC Educational Resources Information Center

    Wilson, Stephanie Gray

    2013-01-01

    Undergraduate statistics courses are perceived as challenging by both students and instructors. Students' attitudes, motivation, math anxiety, and preparedness can negatively impact the student and instructor experience and have the potential to negatively impact student learning. This article describes an attempt to address some of these…

  9. Using the Bootstrap Method to Evaluate the Critical Range of Misfit for Polytomous Rasch Fit Statistics.

    PubMed

    Seol, Hyunsoo

    2016-06-01

    The purpose of this study was to apply the bootstrap procedure to evaluate how the bootstrapped confidence intervals (CIs) for polytomous Rasch fit statistics might differ according to sample sizes and test lengths in comparison with the rule-of-thumb critical value of misfit. A total of 25 simulated data sets were generated to fit the Rasch measurement and then a total of 1,000 replications were conducted to compute the bootstrapped CIs under each of 25 testing conditions. The results showed that rule-of-thumb critical values for assessing the magnitude of misfit were not applicable because the infit and outfit mean square error statistics showed different magnitudes of variability over testing conditions and the standardized fit statistics did not exactly follow the standard normal distribution. Further, they also do not share the same critical range for the item and person misfit. Based on the results of the study, the bootstrapped CIs can be used to identify misfitting items or persons as they offer a reasonable alternative solution, especially when the distributions of the infit and outfit statistics are not well known and depend on sample size.

  10. Study of UV Cu + Ne – CuBr laser lifetime by statistical methods

    SciTech Connect

    Iliev, I P; Gocheva-Ilieva, S G

    2013-11-30

    On the basis of a large amount of experimental data, statistical investigation of the average lifetime of a UV Cu + Ne – CuBr laser depending on ten input physical laser parameters is carried out. It is found that only three of the parameters have a substantial influence on the laser lifetime. Physical analysis and interpretation of the results are provided. (lasers)

  11. Statistical Methods for Assessments in Simulations and Serious Games. Research Report. ETS RR-14-12

    ERIC Educational Resources Information Center

    Fu, Jianbin; Zapata, Diego; Mavronikolas, Elia

    2014-01-01

    Simulation or game-based assessments produce outcome data and process data. In this article, some statistical models that can potentially be used to analyze data from simulation or game-based assessments are introduced. Specifically, cognitive diagnostic models that can be used to estimate latent skills from outcome data so as to scale these…

  12. From association to prediction: statistical methods for the dissection and selection of complex traits in plants

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Quantification of genotype-to-phenotype associations is central to many scientific investigations, yet the ability to obtain consistent results may be thwarted without appropriate statistical analyses. Models for association can consider confounding effects in the materials and complex genetic inter...

  13. A Comparison of Computer-Assisted Instruction and the Traditional Method of Teaching Basic Statistics

    ERIC Educational Resources Information Center

    Ragasa, Carmelita Y.

    2008-01-01

    The objective of the study is to determine if there is a significant difference in the effects of the treatment and control groups on achievement as well as on attitude as measured by the posttest. A class of 38 sophomore college students in the basic statistics taught with the use of computer-assisted instruction and another class of 15 students…

  14. Engaging Students in Survey Research Projects across Research Methods and Statistics Courses

    ERIC Educational Resources Information Center

    Lovekamp, William E.; Soboroff, Shane D.; Gillespie, Michael D.

    2017-01-01

    One innovative way to help students make sense of survey research has been to create a multifaceted, collaborative assignment that promotes critical thinking, comparative analysis, self-reflection, and statistical literacy. We use a short questionnaire adapted from the Higher Education Research Institute's Cooperative Institutional Research…

  15. Building Conceptual Understanding of Research and Statistical Methods through Student Projects.

    ERIC Educational Resources Information Center

    Jamison, Margaret Godwin

    Student projects in both research and statistics classes promote active learning and critical thinking not found in more passive types of course delivery. Students start the dialogue of researchers as they internalize the process of conducting research projects with "real world" issues of interest to them in introductions to research and…

  16. Research Design and Statistical Methods in Indian Medical Journals: A Retrospective Survey

    PubMed Central

    Hassan, Shabbeer; Yellur, Rajashree; Subramani, Pooventhan; Adiga, Poornima; Gokhale, Manoj; Iyer, Manasa S.; Mayya, Shreemathi S.

    2015-01-01

    Good quality medical research generally requires not only an expertise in the chosen medical field of interest but also a sound knowledge of statistical methodology. The number of medical research articles which have been published in Indian medical journals has increased quite substantially in the past decade. The aim of this study was to collate all evidence on study design quality and statistical analyses used in selected leading Indian medical journals. Ten (10) leading Indian medical journals were selected based on impact factors and all original research articles published in 2003 (N = 588) and 2013 (N = 774) were categorized and reviewed. A validated checklist on study design, statistical analyses, results presentation, and interpretation was used for review and evaluation of the articles. Main outcomes considered in the present study were – study design types and their frequencies, error/defects proportion in study design, statistical analyses, and implementation of CONSORT checklist in RCT (randomized clinical trials). From 2003 to 2013: The proportion of erroneous statistical analyses did not decrease (χ2=0.592, Φ=0.027, p=0.4418), 25% (80/320) in 2003 compared to 22.6% (111/490) in 2013. Compared with 2003, significant improvement was seen in 2013; the proportion of papers using statistical tests increased significantly (χ2=26.96, Φ=0.16, p<0.0001) from 42.5% (250/588) to 56.7 % (439/774). The overall proportion of errors in study design decreased significantly (χ2=16.783, Φ=0.12 p<0.0001), 41.3% (243/588) compared to 30.6% (237/774). In 2013, randomized clinical trials designs has remained very low (7.3%, 43/588) with majority showing some errors (41 papers, 95.3%). Majority of the published studies were retrospective in nature both in 2003 [79.1% (465/588)] and in 2013 [78.2% (605/774)]. Major decreases in error proportions were observed in both results presentation (χ2=24.477, Φ=0.17, p<0.0001), 82.2% (263/320) compared to 66.3% (325

  17. Research design and statistical methods in Indian medical journals: a retrospective survey.

    PubMed

    Hassan, Shabbeer; Yellur, Rajashree; Subramani, Pooventhan; Adiga, Poornima; Gokhale, Manoj; Iyer, Manasa S; Mayya, Shreemathi S

    2015-01-01

    Good quality medical research generally requires not only an expertise in the chosen medical field of interest but also a sound knowledge of statistical methodology. The number of medical research articles which have been published in Indian medical journals has increased quite substantially in the past decade. The aim of this study was to collate all evidence on study design quality and statistical analyses used in selected leading Indian medical journals. Ten (10) leading Indian medical journals were selected based on impact factors and all original research articles published in 2003 (N = 588) and 2013 (N = 774) were categorized and reviewed. A validated checklist on study design, statistical analyses, results presentation, and interpretation was used for review and evaluation of the articles. Main outcomes considered in the present study were - study design types and their frequencies, error/defects proportion in study design, statistical analyses, and implementation of CONSORT checklist in RCT (randomized clinical trials). From 2003 to 2013: The proportion of erroneous statistical analyses did not decrease (χ2=0.592, Φ=0.027, p=0.4418), 25% (80/320) in 2003 compared to 22.6% (111/490) in 2013. Compared with 2003, significant improvement was seen in 2013; the proportion of papers using statistical tests increased significantly (χ2=26.96, Φ=0.16, p<0.0001) from 42.5% (250/588) to 56.7 % (439/774). The overall proportion of errors in study design decreased significantly (χ2=16.783, Φ=0.12 p<0.0001), 41.3% (243/588) compared to 30.6% (237/774). In 2013, randomized clinical trials designs has remained very low (7.3%, 43/588) with majority showing some errors (41 papers, 95.3%). Majority of the published studies were retrospective in nature both in 2003 [79.1% (465/588)] and in 2013 [78.2% (605/774)]. Major decreases in error proportions were observed in both results presentation (χ2=24.477, Φ=0.17, p<0.0001), 82.2% (263/320) compared to 66.3% (325/490) and

  18. An Inventory of Methods for the Assessment of Additive Increased Addictiveness of Tobacco Products

    PubMed Central

    van de Nobelen, Suzanne; Kienhuis, Anne S.

    2016-01-01

    Background: Cigarettes and other forms of tobacco contain the addictive drug nicotine. Other components, either naturally occurring in tobacco or additives that are intentionally added during the manufacturing process, may add to the addictiveness of tobacco products. As such, these components can make cigarette smokers more easily and heavily dependent. Efforts to regulate tobacco product dependence are emerging globally. Additives that increase tobacco dependence will be prohibited under the new European Tobacco Product Directive. Objective: This article provides guidelines and recommendations for developing a regulatory strategy for assessment of increase in tobacco dependence due to additives. Relevant scientific literature is summarized and criteria and experimental studies that can define increased dependence of tobacco products are described. Conclusions: Natural tobacco smoke is a very complex matrix of components, therefore analysis of the contribution of an additive or a combination of additives to the level of dependence on this product is challenging. We propose to combine different type of studies analyzing overall tobacco product dependence potential and the functioning of additives in relation to nicotine. By using a combination of techniques, changes associated with nicotine dependence such as behavioral, physiological, and neurochemical alterations can be examined to provide sufficient information. Research needs and knowledge gaps will be discussed and recommendations will be made to translate current knowledge into legislation. As such, this article aids in implementation of the Tobacco Product Directive, as well as help enable regulators and researchers worldwide to develop standards to reduce dependence on tobacco products. Implications: This article provides an overall view on how to assess tobacco product constituents for their potential contribution to use and dependence. It provides guidelines that help enable regulators worldwide to

  19. Overcoming Student Disengagement and Anxiety in Theory, Methods, and Statistics Courses by Building a Community of Learners

    ERIC Educational Resources Information Center

    Macheski, Ginger E.; Buhrmann, Jan; Lowney, Kathleen S.; Bush, Melanie E. L.

    2008-01-01

    Participants in the 2007 American Sociological Association teaching workshop, "Innovative Teaching Practices for Difficult Subjects," shared concerns about teaching statistics, research methods, and theory. Strategies for addressing these concerns center on building a community of learners by creating three processes throughout the course: 1) an…

  20. A Meta-Analytic Review of Studies of the Effectiveness of Small-Group Learning Methods on Statistics Achievement

    ERIC Educational Resources Information Center

    Kalaian, Sema A.; Kasim, Rafa M.

    2014-01-01

    This meta-analytic study focused on the quantitative integration and synthesis of the accumulated pedagogical research in undergraduate statistics education literature. These accumulated research studies compared the academic achievement of students who had been instructed using one of the various forms of small-group learning methods to those who…