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Non-Asymptotic Analysis of Approximations for Multivariate Statistics by Yasunori Fujikoshi
Non-Asymptotic Analysis of Approximations for Multivariate Statistics by Yasunori Fujikoshi
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Non-Asymptotic Analysis of Approximations for Multivariate Statistics

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Description

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.  

Author Biography:

Fujikoshi, Yasunori, Hiroshima University, Higashi-Hiroshima, Japan Ulyanov, Vladimir V., Moscow State University and HSE University, Moscow, Russia
Release date Australia
June 28th, 2020
Audience
  • Professional & Vocational
Edition
1st ed. 2020
Illustrations
16 Illustrations, black and white; IX, 130 p. 16 illus.
Pages
130
ISBN-13
9789811326158
Product ID
28335083

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