Mathematical statistics
- 作者: Shao, Jun,
- 出版: New York : Springer ©1999.
- 稽核項: 1 online resource (xiv, 529 pages).
- 叢書名: Springer texts in statistics
- 標題: Statistique mathématique. , Probability & StatisticsGeneral. , MATHEMATICS Probability & Statistics -- General. , MATHEMATICS , Electronic books. , Mathematical statistics.
- ISBN: 1584888563 , 9781584888567
- ISBN: 9780387986746 , 038798674X
- 試查全文@TNUA:
- 附註: Includes bibliographical references (pages 493-503) and indexes. Cover -- Preface -- Table of Contents -- 1. Probability Theory -- 2. Fundamentals of Statistics -- 3. Unbiased Estimation -- 4. Estimation in Parametric Models -- 5. Estimation in Nonparametric Models -- 6. Hypothesis Tests -- 7. Confidence Sets -- References -- Appendix A -- Abbreviations -- Appendix B -- Notation -- Author Index.
- 摘要: 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 the classical results that are typically covered in a textbook of a similar level, this book introduces some topics in modern statistical theory that have been developed in recent years, such as Markov chain Monte Carlo, quasi-likelihoods, empirical likelihoods, statistical functionals, generalized estimation equations, the jackknife, and the bootstrap. Jun Shao is Professor of Statistics at the University of Wisconsin, Madison.
- 電子資源: https://dbs.tnua.edu.tw/login?url=https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=104556
- 系統號: 005307185
- 資料類型: 電子書
- 讀者標籤: 需登入
- 引用網址: 複製連結
Traditional texts in mathematical statistics can seem - to some readers-heavily weighted with optimality theory of the various flavors developed in the 1940s and50s, and not particularly relevant to statistical practice. Mathematical Statistics stands apart from these treatments. While mathematically rigorous, its focus is on providing a set of useful tools that allow students to understand the theoretical underpinnings of statistical methodology. The author concentrates on inferential procedures within the framework of parametric models, but - acknowledging that models are often incorrectly specified - he also views estimation from a non-parametric perspective. Overall, Mathematical Statistics places greater emphasis on frequentist methodology than on Bayesian, but claims no particular superiority for that approach. It does emphasize, however, the utility of statistical and mathematical software packages, and includes several sections addressing computational issues. The result reaches beyond "nice" mathematics to provide a balanced, practical text that brings life and relevance to a subject so often perceived as irrelevant and dry.
來源: Google Book
來源: Google Book
評分
