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Non-asymptotic analysis of approxima...

Fujikoshi, Yasunori.

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Non-asymptotic analysis of approximations for multivariate statistics

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Non-asymptotic analysis of approximations for multivariate statistics/ by Yasunori Fujikoshi, Vladimir V. Ulyanov.
作者:	Fujikoshi, Yasunori.
其他作者:	Ulyanov, Vladimir V.
出版者:	Singapore :Springer Singapore : : 2020.,
面頁冊數:	ix, 130 p. :ill., digital ;24 cm.
內容註:	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.
Contained By:	Springer eBooks
標題:	Multivariate analysis. -
電子資源:	https://doi.org/10.1007/978-981-13-2616-5
ISBN:	9789811326165

Non-asymptotic analysis of approximations for multivariate statistics
Fujikoshi, Yasunori.

Non-asymptotic analysis of approximations for multivariate statistics[electronic resource] /by Yasunori Fujikoshi, Vladimir V. Ulyanov. - Singapore :Springer Singapore :2020. - ix, 130 p. :ill., digital ;24 cm. - SpringerBriefs in statistics, JSS research series in statistics. - SpringerBriefs in statistics.JSS research series in statistics..

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.

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.

ISBN: 9789811326165

Standard No.: 10.1007/978-981-13-2616-5doiSubjects--Topical Terms:

517467
Multivariate analysis.

LC Class. No.: QA278 / .F855 2020

Dewey Class. No.: 519.535

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520 $a 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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