Yasunori Fujikoshi's Books

Multivariate Statistics

High-Dimensional and Large-Sample Approximations

By: Yasunori Fujikoshi,Vladimir V. Ulyanov,Ryoichi Shimizu

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Multivariate Statistics

High-Dimensional and Large-Sample Approximations

By: Yasunori Fujikoshi,Vladimir V. Ulyanov,Ryoichi Shimizu

A comprehensive examination of high-dimensional analysis of multivariate methods and their real-world applications Multivariate Statistics: High-Dimensional and Large-Sample Approximations is the first book of its kind to explore how classical multivariate methods can be revised and used in place of conventional statistical tools. Written by prominent researchers in the field, the book focuses on high-dimensional and large-scale approximations and details the many basic multivariate methods used to achieve high levels of accuracy. The authors begin with a fundamental presentation of the basic tools and exact distributional results of multivariate statistics, and, in addition, the derivations of most distributional results are provided. Statistical methods for high-dimensional data, such as curve data, spectra, images, and DNA microarrays, are discussed. Bootstrap approximations from a methodological point of view, theoretical accuracies in MANOVA tests, and model selection criteria are also presented. Subsequent chapters feature additional topical coverage including: High-dimensional approximations of various statistics High-dimensional statistical methods Approximations with computable error bound Selection of variables based on model selection approach Statistics with error bounds and their appearance in discriminant analysis, growth curve models, generalized linear models, profile analysis, and multiple comparison Each chapter provides real-world applications and thorough analyses of the real data. In addition, approximation formulas found throughout the book are a useful tool for both practical and theoretical statisticians, and basic results on exact distributions in multivariate analysis are included in a comprehensive, yet accessible, format. Multivariate Statistics is an excellent book for courses on probability theory in statistics at the graduate level. It is also an essential reference for both practical and theoretical statisticians who are interested in multivariate analysis and who would benefit from learning the applications of analytical probabilistic methods in statistics.

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Page Count

564

Publisher

John Wiley & Sons

Published Date

ISBN 10

0470539860

ISBN 13

9780470539866

Non-Asymptotic Analysis of Approximations for Multivariate Statistics

By: Yasunori Fujikoshi,Vladimir V. Ulyanov

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Non-Asymptotic Analysis of Approximations for Multivariate Statistics

By: Yasunori Fujikoshi,Vladimir V. Ulyanov

This book presents recent non-asymptotic results for approximations in multivariate statistical analysis. The book is unique in its focus on results with the correct error structure for all the parameters involved. Firstly, it discusses the computable error bounds on correlation coefficients, MANOVA tests and discriminant functions studied in recent papers. It then introduces new areas of research in high-dimensional approximations for bootstrap procedures, Cornish–Fisher expansions, power-divergence statistics and approximations of statistics based on observations with random sample size. Lastly, it proposes a general approach for the construction of non-asymptotic bounds, providing relevant examples for several complicated statistics. It is a valuable resource for researchers with a basic understanding of multivariate statistics.

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Page Count

133

Publisher

Springer Nature

Published Date

ISBN 10

9811326169

ISBN 13

9789811326165

Multivariate Statistics

High-Dimensional and Large-Sample Approximations

By: Yasunori Fujikoshi,Vladimir V. Ulyanov,Ryoichi Shimizu

Write a review Read reviews Take a Quiz Solve Book Puzzle

Multivariate Statistics

High-Dimensional and Large-Sample Approximations

By: Yasunori Fujikoshi,Vladimir V. Ulyanov,Ryoichi Shimizu

Average ratings

N/A

Write a review

Solve jigsaw puzzle

Age

Page Count

564

Publisher

John Wiley & Sons

Published Date

ISBN 10

0470539860

ISBN 13

9780470539866

Non-Asymptotic Analysis of Approximations for Multivariate Statistics

By: Yasunori Fujikoshi,Vladimir V. Ulyanov

Write a review Read reviews Take a Quiz Solve Book Puzzle

Non-Asymptotic Analysis of Approximations for Multivariate Statistics

By: Yasunori Fujikoshi,Vladimir V. Ulyanov

This book presents recent non-asymptotic results for approximations in multivariate statistical analysis. The book is unique in its focus on results with the correct error structure for all the parameters involved. Firstly, it discusses the computable error bounds on correlation coefficients, MANOVA tests and discriminant functions studied in recent papers. It then introduces new areas of research in high-dimensional approximations for bootstrap procedures, Cornish-Fisher expansions, power-divergence statistics and approximations of statistics based on observations with random sample size. Lastly, it proposes a general approach for the construction of non-asymptotic bounds, providing relevant examples for several complicated statistics. It is a valuable resource for researchers with a basic understanding of multivariate statistics.

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Age

Page Count

133

Published Date

ISBN 10

9811326177

ISBN 13

9789811326172

Book's by Yasunori Fujikoshi

Multivariate Statistics

Multivariate Statistics

Non-Asymptotic Analysis of Approximations for Multivariate Statistics

Non-Asymptotic Analysis of Approximations for Multivariate Statistics

Multivariate Statistics

Multivariate Statistics

Non-Asymptotic Analysis of Approximations for Multivariate Statistics

Non-Asymptotic Analysis of Approximations for Multivariate Statistics

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