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Non-Asymptotic Analysis of Approximations for Multivariate Statistics

Non-Asymptotic Analysis of Approximations for Multivariate Statistics
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Field name Details
Dewey Class 519.5
Title Non-Asymptotic Analysis of Approximations for Multivariate Statistics ([EBook]) / by Yasunori Fujikoshi, Vladimir V. Ulyanov.
Author Fujikoshi, Yasunori
Added Personal Name Ulyanov, Vladimir V.
Other name(s) SpringerLink (Online service)
Edition statement 1st ed. 2020.
Publication Singapore : Springer Singapore , 2020.
Physical Details IX, 130 pages: 16 illus. : online resource.
Series JSS Research Series in Statistics 2364-0057
ISBN 9789811326165
Summary Note 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. .:
Contents note 1. Introduction -- 2. Correlation Coefficient -- 3. MANOVA Test Statistics -- 4. Linear and Quadratic Discriminant Functions -- 5. Bootstrap Confidence Sets -- 6. Gaussian Comparison -- 7. Cornish-Fisher Expansions -- 8 Approximations for Statistics Based on Random Sample Sizes -- 9. Power-divergence Statistics -- 10.General Approach to Construct Non-asymptotic Bounds -- 11 - Other Topics -- Index.
Mode of acces to digital resource Digital book. Cham Springer Nature 2020. - Mode of access: World Wide Web. System requirements: Internet Explorer 6.0 (or higher) or Firefox 2.0 (or higher). Available as searchable text in PDF format
System details note Online access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users).
Internet Site https://doi.org/10.1007/978-981-13-2616-5
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