| 书目名称 | Mathematical Statistics | | 编辑 | Jun Shao | | 视频video | | | 概述 | Includes supplementary material: | | 丛书名称 | Springer Texts in Statistics | | 图书封面 |  | | 描述 | .This graduate textbook covers topics in statistical theory essential for graduate students preparing for work on a Ph.D. degree in statistics. The first chapter provides a quick overview of concepts and results in measure-theoretic probability theory that are useful in statistics. The second chapter introduces some fundamental concepts in statistical decision theory and inference. Chapters 3-7 contain detailed studies on some important topics: unbiased estimation, parametric estimation, nonparametric estimation, hypothesis testing, and confidence sets. A large number of exercises in each chapter provide not only practice problems for students, but also many additional results. . .In addition to improving the presentation, the new edition makes Chapter 1 a self-contained chapter for probability theory with emphasis in statistics. Added topics include useful moment inequalities, more discussions of moment generating and characteristic functions, conditional independence, Markov chains, martingales, Edgeworth and Cornish-Fisher expansions, and proofs to many key theorems such as the dominated convergence theorem, monotone convergence theorem, uniqueness theorem, continuity theorem, l | | 出版日期 | Textbook 2003Latest edition | | 关键词 | Mathematical Statistics; Statistical Theory; likelihood; Markov chain; Mathematica; mathematical statisti | | 版次 | 2 | | doi | https://doi.org/10.1007/b97553 | | isbn_softcover | 978-1-4419-2978-5 | | isbn_ebook | 978-0-387-21718-5Series ISSN 1431-875X Series E-ISSN 2197-4136 | | issn_series | 1431-875X | | copyright | Springer-Verlag New York 2003 |
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发表于 2025-3-21 18:02:59
