Non-Asymptotic Analysis of Approximations for Multivariate Statistics (SpringerBriefs in Statistics) - Softcover

Fujikoshi, Yasunori; Ulyanov, Vladimir V.

Softcover

ISBN 10: 9811326150 ISBN 13: 9789811326158

Publisher: Springer, 2020

Synopsis

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.

 

About this title

About the Author

Fujikoshi, Yasunori, Hiroshima University, Higashi-Hiroshima, Japan

Ulyanov, Vladimir V., Moscow State University and HSE University, Moscow, Russia

Edition details

• Publisher: Springer
• Publication date: 2020
• Language: English
• ISBN 10: 9811326150
• ISBN 13: 9789811326158
• Binding: Paperback
• Edition number: 1
• Number of pages: 139