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Simultaneous Inference On Sample Covariances
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Book Synopsis Simultaneous Inference on Sample Covariances by : Han Xiao
Download or read book Simultaneous Inference on Sample Covariances written by Han Xiao and published by . This book was released on 2011 with total page 125 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis considers the maximum deviations of the sample covariances in the contexts of high dimensional data analysis and time series analysis.
Book Synopsis Simultaneous Statistical Inference by : Rupert G. Jr. Miller
Download or read book Simultaneous Statistical Inference written by Rupert G. Jr. Miller and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 311 pages. Available in PDF, EPUB and Kindle. Book excerpt: Simultaneous Statistical Inference, which was published originally in 1966 by McGraw-Hill Book Company, went out of print in 1973. Since then, it has been available from University Microfilms International in xerox form. With this new edition Springer-Verlag has republished the original edition along with my review article on multiple comparisons from the December 1977 issue of the Journal of the American Statistical Association. This review article covered developments in the field from 1966 through 1976. A few minor typographical errors in the original edition have been corrected in this new edition. A new table of critical points for the studentized maximum modulus is included in this second edition as an addendum. The original edition included the table by K. C. S. Pillai and K. V. Ramachandran, which was meager but the best available at the time. This edition contains the table published in Biometrika in 1971 by G. 1. Hahn and R. W. Hendrickson, which is far more comprehensive and therefore more useful. The typing was ably handled by Wanda Edminster for the review article and Karola Decleve for the changes for the second edition. My wife, Barbara, again cheerfully assisted in the proofreading. Fred Leone kindly granted permission from the American Statistical Association to reproduce my review article. Also, Gerald Hahn, Richard Hendrickson, and, for Biometrika, David Cox graciously granted permission to reproduce the new table of the studentized maximum modulus. The work in preparing the review article was partially supported by NIH Grant ROI GM21215.
Book Synopsis Simultaneous Statistical Inference by : Thorsten Dickhaus
Download or read book Simultaneous Statistical Inference written by Thorsten Dickhaus and published by Springer Science & Business Media. This book was released on 2014-01-23 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph will provide an in-depth mathematical treatment of modern multiple test procedures controlling the false discovery rate (FDR) and related error measures, particularly addressing applications to fields such as genetics, proteomics, neuroscience and general biology. The book will also include a detailed description how to implement these methods in practice. Moreover new developments focusing on non-standard assumptions are also included, especially multiple tests for discrete data. The book primarily addresses researchers and practitioners but will also be beneficial for graduate students.
Book Synopsis Simultaneous Inference on Jointly Considered Subsets of Treatment Effects by : Stephen A. Rowe
Download or read book Simultaneous Inference on Jointly Considered Subsets of Treatment Effects written by Stephen A. Rowe and published by . This book was released on 1993 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Simultaneous Inference Procedures Using the Method of Quasi-likelihood with an Application to Feedback Models by : Suparni Gunasekera
Download or read book Simultaneous Inference Procedures Using the Method of Quasi-likelihood with an Application to Feedback Models written by Suparni Gunasekera and published by . This book was released on 1992 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Simultaneous Statistical Inference and Statistical Power in Survey Research Applications of the General Linear Model by : William T. Bielby
Download or read book Simultaneous Statistical Inference and Statistical Power in Survey Research Applications of the General Linear Model written by William T. Bielby and published by . This book was released on 1976 with total page 43 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Simultaneous Inference for High Dimensional and Correlated Data by : Afroza Polin
Download or read book Simultaneous Inference for High Dimensional and Correlated Data written by Afroza Polin and published by . This book was released on 2019 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt: In high dimensional data, the number of covariates is larger than the sample size, which makes the estimation process challenging. We consider a high-dimensional and longitudinal data where at each time point, the number of covariates is much higher than the number of subjects. We consider two different settings of longitudinal data. First, we consider that the samples at different time points are generated from different populations. Second, we consider that the samples at different time points are generated from a multivariate distribution. In both cases, the number of covariates is much larger than the sample size and the standard least square methods are not applicable.In longitudinal study, our main focus is in the changes of the mean responses over the time and how these changes are related to the explanatory variables. Thus we are interested in testing the effect of the covariates over the time points simultaneously. In the first scenario, we use lasso at each time point to regress the response on the explanatory variables. Along with estimating the regression coefficients lasso also does dimension reduction. We use de-biased lasso for inference. To adjust the multiplicity effect in simultaneous testing we apply Bonferroni, Holm's, Hochberg's and the coherent stepwise procedures. In the second scenario, the samples at different time points are generated from a multivariate distribution and the dimension of the multivariate distribution is equal to the number of time points. We use lasso and de-biased lasso for inferences. To adjust the multiplicity effect in simultaneous testing, we use Bonferroni, Holm's, Hochberg's and stepwise procedures. We provide theoretical details that Bonferroni, Holm's step-down and the coherent step-wise procedures controls the family-wise error rate in strong sense for de-biased lasso estimators. While Hochberg's procedure provides a strong control of family-wise error rate only for independent or positively correlated test statistics.
Book Synopsis Generalized Inference in Repeated Measures by : Samaradasa Weerahandi
Download or read book Generalized Inference in Repeated Measures written by Samaradasa Weerahandi and published by John Wiley & Sons. This book was released on 2004-08-24 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: A complete guide to powerful and practical statistical modeling using MANOVA Numerous statistical applications are time dependent. Virtually all biomedical, pharmaceutical, and industrial experiments demand repeated measurements over time. The same holds true for market research and analysis. Yet conventional methods, such as the Repeated Measures Analysis of Variance (Rm ANOVA), do not always yield exact solutions, obliging practitioners to settle for asymptotic results and approximate solutions. Generalized inference in Multivariate Analysis of Variance (MANOVA), mixed models, and growth curves offer exact methods of data analysis under milder conditions without deviating from the conventional philosophy of statistical inference. Generalized Inference in Repeated Measures is a concise, self-contained guide to the use of these innovative solutions, presenting them as extensions of–rather than alternatives to–classical methods of statistical evaluation. Requiring minimal prior knowledge of statistical concepts in the evaluation of linear models, the book provides exact parametric methods for each application considered, with solutions presented in terms of generalized p-values. Coverage includes: New concepts in statistical inference, with special focus on generalized p-values and generalized confidence intervals One-way and two-way ANOVA, in cases of equal and unequal variances Basic and higher-way mixed models, including testing and estimation of fixed effects and variance components Multivariate populations, including basic inference, comparison, and analysis of variance Basic, widely used repeated measures models including crossover designs and growth curves With a comprehensive set of formulas, illustrative examples, and exercises in each chapter, Generalized Inference in Repeated Measures is ideal as both a comprehensive reference for research professionals and a text for students.
Book Synopsis Simultaneous Inference for Proportions in Arbitrary Sampling Designs by : Andreas Stich
Download or read book Simultaneous Inference for Proportions in Arbitrary Sampling Designs written by Andreas Stich and published by . This book was released on 1997 with total page 15 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Multivariate T-Distributions and Their Applications by : Samuel Kotz
Download or read book Multivariate T-Distributions and Their Applications written by Samuel Kotz and published by Cambridge University Press. This book was released on 2004-02-16 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: Almost all the results available in the literature on multivariate t-distributions published in the last 50 years are now collected together in this comprehensive reference. Because these distributions are becoming more prominent in many applications, this book is a must for any serious researcher or consultant working in multivariate analysis and statistical distributions. Much of this material has never before appeared in book form. The first part of the book emphasizes theoretical results of a probabilistic nature. In the second part of the book, these are supplemented by a variety of statistical aspects. Various generalizations and applications are dealt with in the final chapters. The material on estimation and regression models is of special value for practitioners in statistics and economics. A comprehensive bibliography of over 350 references is included.
Book Synopsis Multivariate Observations by : George A. F. Seber
Download or read book Multivariate Observations written by George A. F. Seber and published by John Wiley & Sons. This book was released on 2009-09-25 with total page 718 pages. Available in PDF, EPUB and Kindle. Book excerpt: WILEY-INTERSCIENCE PAPERBACK SERIES The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "In recent years many monographs have been published on specialized aspects of multivariate data-analysis–on cluster analysis, multidimensional scaling, correspondence analysis, developments of discriminant analysis, graphical methods, classification, and so on. This book is an attempt to review these newer methods together with the classical theory. . . . This one merits two cheers." –J. C. Gower, Department of Statistics Rothamsted Experimental Station, Harpenden, U.K. Review in Biometrics, June 1987 Multivariate Observations is a comprehensive sourcebook that treats data-oriented techniques as well as classical methods. Emphasis is on principles rather than mathematical detail, and coverage ranges from the practical problems of graphically representing high-dimensional data to the theoretical problems relating to matrices of random variables. Each chapter serves as a self-contained survey of a specific topic. The book includes many numerical examples and over 1,100 references.
Book Synopsis Simultaneous Inference with Application to Dose-response Study by : Rachana Maharjan
Download or read book Simultaneous Inference with Application to Dose-response Study written by Rachana Maharjan and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of the common applications of simultaneous inference problems is in the dose-response study, where different dosage levels need to be tested simultaneously. Although several multiple comparison procedures such as Bonferroni, Holm (1979), Hochberg (1988), Dunnett (1955) can be used to adjust multiplicity and control family-wise error rate, Ma and McDermott (2019) proposed a modification of the MCP-Mod approach to finding the dose-response relationship when the responses are normal. However, there are many cases where the response variable is not symmetry and follows a skew-normal distribution. In my research, we proposed a new multiple contrast test statistic to find the significant dose-response relationship for skew-normal responses. Later, we used the proposed test statistics to find the lower confidence bound in the simultaneous confidence step-wise procedure. Simultaneous confidence sets are used when information regarding follow-up investigation in clinical trials is needed. Further in this dissertation, we discussed the step-wise procedure to find the minimum effective dosage for the survival data. To do this, we combined the Kaplan-Meier estimator to estimate the survival function and Holm’s stepdown procedure to strongly control the family-wise error rate while testing different treatment groups with the control group.
Download or read book Multiple Comparisons written by Jason Hsu and published by CRC Press. This book was released on 1996-02-01 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multiple Comparisons introduces simultaneous statistical inference and covers the theory and techniques for all-pairwise comparisons, multiple comparisons with the best, and multiple comparisons with a control. The author describes confidence intervals methods and stepwise exposes abuses and misconceptions, and guides readers to the correct method
Book Synopsis Causal Inference in Statistics by : Judea Pearl
Download or read book Causal Inference in Statistics written by Judea Pearl and published by John Wiley & Sons. This book was released on 2016-01-25 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: CAUSAL INFERENCE IN STATISTICS A Primer Causality is central to the understanding and use of data. Without an understanding of cause–effect relationships, we cannot use data to answer questions as basic as "Does this treatment harm or help patients?" But though hundreds of introductory texts are available on statistical methods of data analysis, until now, no beginner-level book has been written about the exploding arsenal of methods that can tease causal information from data. Causal Inference in Statistics fills that gap. Using simple examples and plain language, the book lays out how to define causal parameters; the assumptions necessary to estimate causal parameters in a variety of situations; how to express those assumptions mathematically; whether those assumptions have testable implications; how to predict the effects of interventions; and how to reason counterfactually. These are the foundational tools that any student of statistics needs to acquire in order to use statistical methods to answer causal questions of interest. This book is accessible to anyone with an interest in interpreting data, from undergraduates, professors, researchers, or to the interested layperson. Examples are drawn from a wide variety of fields, including medicine, public policy, and law; a brief introduction to probability and statistics is provided for the uninitiated; and each chapter comes with study questions to reinforce the readers understanding.
Book Synopsis Selected Papers on Differential Equations and Analysis by :
Download or read book Selected Papers on Differential Equations and Analysis written by and published by American Mathematical Soc.. This book was released on 2005 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains translations of papers that originally appeared in the Japanese journal Sugaku. The papers range over a variety of topics, including differential equations with free boundary, singular integral operators, operator algebras, and relations between the Brownian motion on a manifold with function theory. The volume is suitable for graduate students and research mathematicians interested in analysis and differential equations."
Book Synopsis The Analysis of Covariance and Alternatives by : Bradley Huitema
Download or read book The Analysis of Covariance and Alternatives written by Bradley Huitema and published by John Wiley & Sons. This book was released on 2011-10-24 with total page 562 pages. Available in PDF, EPUB and Kindle. Book excerpt: A complete guide to cutting-edge techniques and best practices for applying covariance analysis methods The Second Edition of Analysis of Covariance and Alternatives sheds new light on its topic, offering in-depth discussions of underlying assumptions, comprehensive interpretations of results, and comparisons of distinct approaches. The book has been extensively revised and updated to feature an in-depth review of prerequisites and the latest developments in the field. The author begins with a discussion of essential topics relating to experimental design and analysis, including analysis of variance, multiple regression, effect size measures and newly developed methods of communicating statistical results. Subsequent chapters feature newly added methods for the analysis of experiments with ordered treatments, including two parametric and nonparametric monotone analyses as well as approaches based on the robust general linear model and reversed ordinal logistic regression. Four groundbreaking chapters on single-case designs introduce powerful new analyses for simple and complex single-case experiments. This Second Edition also features coverage of advanced methods including: Simple and multiple analysis of covariance using both the Fisher approach and the general linear model approach Methods to manage assumption departures, including heterogeneous slopes, nonlinear functions, dichotomous dependent variables, and covariates affected by treatments Power analysis and the application of covariance analysis to randomized-block designs, two-factor designs, pre- and post-test designs, and multiple dependent variable designs Measurement error correction and propensity score methods developed for quasi-experiments, observational studies, and uncontrolled clinical trials Thoroughly updated to reflect the growing nature of the field, Analysis of Covariance and Alternatives is a suitable book for behavioral and medical scineces courses on design of experiments and regression and the upper-undergraduate and graduate levels. It also serves as an authoritative reference work for researchers and academics in the fields of medicine, clinical trials, epidemiology, public health, sociology, and engineering.
Book Synopsis A First Course on Parametric Inference by : Balvant Keshav Kale
Download or read book A First Course on Parametric Inference written by Balvant Keshav Kale and published by Alpha Science Int'l Ltd.. This book was released on 2005 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: "After a brief historical perspective, A First Course on Parametric Inference, discusses the basic concept of sufficient statistic and the classical approach based on minimum variance unbiased estimator. There is a separate chapter on simultaneous estimation of several parameters. Large sample theory of estimation, based on consistent asymptotically normal estimators obtained by method of moments, percentile and the method of maximum likelihood is also introduced. The tests of hypotheses for finite samples with classical Neyman-Pearson theory is developed pointing out its connection with Bayesian approach. The hypotheses testing and confidence interval techniques are developed leading to likelihood ratio tests, score tests and tests based on maximum likelihood estimators."--BOOK JACKET.
