My Account Log in

1 option

Non-Asymptotic Analysis of Approximations for Multivariate Statistics / by Yasunori Fujikoshi, Vladimir V. Ulyanov.

Springer Nature - Springer Mathematics and Statistics eBooks 2020 English International Available online

View online
Format:
Book
Author/Creator:
Fujikoshi, Yasunori, 1942- author.
Ulyanov, Vladimir V., 1953- author.
Contributor:
SpringerLink (Online service)
Series:
Mathematics and Statistics (SpringerNature-11649)
SpringerBriefs in statistics. JSS research series in statistics 2364-0057
JSS Research Series in Statistics, 2364-0057
Language:
English
Subjects (All):
Statistics.
Statistical Theory and Methods.
Statistics and Computing/Statistics Programs.
Applied Statistics.
Local Subjects:
Statistical Theory and Methods.
Statistics and Computing/Statistics Programs.
Applied Statistics.
Physical Description:
1 online resource (IX, 130 pages) : 16 illustrations.
Edition:
First edition 2020.
Contained In:
Springer Nature eBook
Place of Publication:
Singapore : Springer Singapore : Imprint: Springer, 2020.
System Details:
text file PDF
Summary:
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:
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.
Other Format:
Printed edition:
ISBN:
978-981-13-2616-5
9789811326165
Access Restriction:
Restricted for use by site license.

The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.

My Account

Shelf Request an item Bookmarks Fines and fees Settings

Guides

Using the Library Catalog Using Articles+ Library Account