The Multivariate Student T Model In Robust Inference And Data Analysis
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The Multivariate Student T Model In Robust Inference And Data Analysis
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Author : Trevor S. Breusch
language : en
Publisher:
Release Date : 1993
The Multivariate Student T Model In Robust Inference And Data Analysis written by Trevor S. Breusch and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993 with Bayesian statistical decision theory categories.
Statistical Inference For Models With Multivariate T Distributed Errors
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Author : A. K. Md. Ehsanes Saleh
language : en
Publisher: John Wiley & Sons
Release Date : 2014-10-01
Statistical Inference For Models With Multivariate T Distributed Errors written by A. K. Md. Ehsanes Saleh and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-10-01 with Mathematics categories.
This book summarizes the results of various models under normal theory with a brief review of the literature. Statistical Inference for Models with Multivariate t-Distributed Errors: Includes a wide array of applications for the analysis of multivariate observations Emphasizes the development of linear statistical models with applications to engineering, the physical sciences, and mathematics Contains an up-to-date bibliography featuring the latest trends and advances in the field to provide a collective source for research on the topic Addresses linear regression models with non-normal errors with practical real-world examples Uniquely addresses regression models in Student's t-distributed errors and t-models Supplemented with an Instructor's Solutions Manual, which is available via written request by the Publisher
Multivariate Analysis
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Author : Kanti V. Mardia
language : en
Publisher: John Wiley & Sons
Release Date : 2024-08-05
Multivariate Analysis written by Kanti V. Mardia and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-05 with Mathematics categories.
Multivariate Analysis Comprehensive Reference Work on Multivariate Analysis and its Applications The first edition of this book, by Mardia, Kent and Bibby, has been used globally for over 40 years. This second edition brings many topics up to date, with a special emphasis on recent developments. A wide range of material in multivariate analysis is covered, including the classical themes of multivariate normal theory, multivariate regression, inference, multidimensional scaling, factor analysis, cluster analysis and principal component analysis. The book also now covers modern developments such as graphical models, robust estimation, statistical learning, and high-dimensional methods. The book expertly blends theory and application, providing numerous worked examples and exercises at the end of each chapter. The reader is assumed to have a basic knowledge of mathematical statistics at an undergraduate level together with an elementary understanding of linear algebra. There are appendices which provide a background in matrix algebra, a summary of univariate statistics, a collection of statistical tables and a discussion of computational aspects. The work includes coverage of: Basic properties of random vectors, copulas, normal distribution theory, and estimation Hypothesis testing, multivariate regression, and analysis of variance Principal component analysis, factor analysis, and canonical correlation analysis Discriminant analysis, cluster analysis, and multidimensional scaling New advances and techniques, including supervised and unsupervised statistical learning, graphical models and regularization methods for high-dimensional data Although primarily designed as a textbook for final year undergraduates and postgraduate students in mathematics and statistics, the book will also be of interest to research workers and applied scientists.
Bayesian Data Analysis Second Edition
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Author : Andrew Gelman
language : en
Publisher: CRC Press
Release Date : 2003-07-29
Bayesian Data Analysis Second Edition written by Andrew Gelman and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-07-29 with Mathematics categories.
Incorporating new and updated information, this second edition of THE bestselling text in Bayesian data analysis continues to emphasize practice over theory, describing how to conceptualize, perform, and critique statistical analyses from a Bayesian perspective. Its world-class authors provide guidance on all aspects of Bayesian data analysis and include examples of real statistical analyses, based on their own research, that demonstrate how to solve complicated problems. Changes in the new edition include: Stronger focus on MCMC Revision of the computational advice in Part III New chapters on nonlinear models and decision analysis Several additional applied examples from the authors' recent research Additional chapters on current models for Bayesian data analysis such as nonlinear models, generalized linear mixed models, and more Reorganization of chapters 6 and 7 on model checking and data collection Bayesian computation is currently at a stage where there are many reasonable ways to compute any given posterior distribution. However, the best approach is not always clear ahead of time. Reflecting this, the new edition offers a more pluralistic presentation, giving advice on performing computations from many perspectives while making clear the importance of being aware that there are different ways to implement any given iterative simulation computation. The new approach, additional examples, and updated information make Bayesian Data Analysis an excellent introductory text and a reference that working scientists will use throughout their professional life.
Robust Inference
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Author : Moti Lal Tiku
language : en
Publisher: Marcel Dekker
Release Date : 1986
Robust Inference written by Moti Lal Tiku and has been published by Marcel Dekker this book supported file pdf, txt, epub, kindle and other format this book has been release on 1986 with Mathematics categories.
This authoritative new volume treats a wide class of distributions that constitute plausible alternatives to normality -- such as short- and long-tailed symmetric distributions and moderately skewed distributions -- all having finite mean and variance. Robust Inference illustrates the appropriateness of various robust methods for solving both one-sample and multisample statistical inference problems ... develops Laguerre series expansions for Student's t and variance-ratio F statistic distributions ... analyzes normal and nonnormal distribution efficiencies ... works out modified maximum likelihood (MML) estimators based on type II censored samples for log-normal, logistic, exponential, and Rayleigh distributions ... uses MML estimators in constructing robust hypothesis-testing procedures ... considers the specialized topics of regression, analysis of variance, classification, and sample survey ... discusses goodness-of-fit tests ... describes Q-Q plots in a special appendix ... and much more. An outstanding, time-saving reference for theoreticians and practitioners of statistics, Robust Inference is also an excellent auxiliary text for an undergraduate- or graduate-level course on robustness. Book jacket.
Inference In Multivariate Student T Models With Serial Correlation And Dynamic Heteroskedasticity
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Author : Trevor S. Breusch
language : en
Publisher:
Release Date : 1993
Inference In Multivariate Student T Models With Serial Correlation And Dynamic Heteroskedasticity written by Trevor S. Breusch and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993 with Correlation (Statistics) categories.
Quantitative Psychology
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Author : L. Andries van der Ark
language : en
Publisher: Springer
Release Date : 2017-06-06
Quantitative Psychology written by L. Andries van der Ark and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-06-06 with Social Science categories.
This proceedings volume compiles and expands on selected and peer reviewed presentations given at the 81st Annual Meeting of the Psychometric Society (IMPS), organized by the University of North Carolina at Greensboro, and held in Asheville, North Carolina, July 11th to 17th, 2016. IMPS is one of the largest international meetings focusing on quantitative measurement in psychology, education, and the social sciences, both in terms of participants and number of presentations. The meeting built on the Psychometric Society's mission to share quantitative methods relevant to psychology, addressing a diverse set of psychometric topics including item response theory, factor analysis, structural equation modeling, time series analysis, mediation analysis, cognitive diagnostic models, and multi-level models. Selected presenters were invited to revise and expand their contributions and to have them peer reviewed and published in this proceedings volume. Previous volumes to showcase work from the Psychometric Society’s meetings are New Developments in Quantitative Psychology: Presentations from the 77th Annual Psychometric Society Meeting (Springer, 2013), Quantitative Psychology Research: The 78th Annual Meeting of the Psychometric Society (Springer, 2015), Quantitative Psychology Research: The 79th Annual Meeting of the Psychometric Society, Madison, Wisconsin, 2014 (Springer, 2015), and Quantitative Psychology Research: The 80th Annual Meeting of the Psychometric Society, Beijing, 2015 (Springer, 2016).
Bayesian Inference
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Author : Javier Prieto Tejedor
language : en
Publisher: BoD – Books on Demand
Release Date : 2017-11-02
Bayesian Inference written by Javier Prieto Tejedor and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-02 with Mathematics categories.
The range of Bayesian inference algorithms and their different applications has been greatly expanded since the first implementation of a Kalman filter by Stanley F. Schmidt for the Apollo program. Extended Kalman filters or particle filters are just some examples of these algorithms that have been extensively applied to logistics, medical services, search and rescue operations, or automotive safety, among others. This book takes a look at both theoretical foundations of Bayesian inference and practical implementations in different fields. It is intended as an introductory guide for the application of Bayesian inference in the fields of life sciences, engineering, and economics, as well as a source document of fundamentals for intermediate Bayesian readers.
Robust And Multivariate Statistical Methods
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Author : Mengxi Yi
language : en
Publisher: Springer Nature
Release Date : 2023-04-19
Robust And Multivariate Statistical Methods written by Mengxi Yi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-19 with Mathematics categories.
This book presents recent developments in multivariate and robust statistical methods. Featuring contributions by leading experts in the field it covers various topics, including multivariate and high-dimensional methods, time series, graphical models, robust estimation, supervised learning and normal extremes. It will appeal to statistics and data science researchers, PhD students and practitioners who are interested in modern multivariate and robust statistics. The book is dedicated to David E. Tyler on the occasion of his pending retirement and also includes a review contribution on the popular Tyler’s shape matrix.
Robust Multivariate Analysis
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Author : David J. Olive
language : en
Publisher: Springer
Release Date : 2017-11-28
Robust Multivariate Analysis written by David J. Olive and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-28 with Mathematics categories.
This text presents methods that are robust to the assumption of a multivariate normal distribution or methods that are robust to certain types of outliers. Instead of using exact theory based on the multivariate normal distribution, the simpler and more applicable large sample theory is given. The text develops among the first practical robust regression and robust multivariate location and dispersion estimators backed by theory. The robust techniques are illustrated for methods such as principal component analysis, canonical correlation analysis, and factor analysis. A simple way to bootstrap confidence regions is also provided. Much of the research on robust multivariate analysis in this book is being published for the first time. The text is suitable for a first course in Multivariate Statistical Analysis or a first course in Robust Statistics. This graduate text is also useful for people who are familiar with the traditional multivariate topics, but want to know more about handling data sets with outliers. Many R programs and R data sets are available on the author’s website.