| 书目名称 | Non-Asymptotic Analysis of Approximations for Multivariate Statistics |
| 编辑 | Yasunori Fujikoshi,Vladimir V. Ulyanov |
| 视频video | |
| 概述 | Is the first book on non-asymptotic approximations and computable error bounds in multivariate analysis.Focuses on the errors in high-dimensional approximations as well as large sample approximations |
| 丛书名称 | SpringerBriefs in Statistics |
| 图书封面 |  |
| 描述 | .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... . |
| 出版日期 | Book 2020 |
| 关键词 | Multivariate Statistics; Non-asymptotic Analysis; Computable Error Bounds; Edgeworth Expansions; Cornish |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-981-13-2616-5 |
| isbn_softcover | 978-981-13-2615-8 |
| isbn_ebook | 978-981-13-2616-5Series ISSN 2191-544X Series E-ISSN 2191-5458 |
| issn_series | 2191-544X |
| copyright | The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2020 |
发表于 2025-3-21 18:23:00
