| 书目名称 | Mathematical Statistics | | 编辑 | Jun Shao | | 视频video | | | 丛书名称 | Springer Texts in Statistics | | 图书封面 |  | | 描述 | This book is intended for a course entitled Mathematical Statistics o?ered at the Department of Statistics, University of Wisconsin-Madison. This course, taught in a mathematically rigorous fashion, covers essential - terials in statistical theory that a ?rst or second year graduate student typically needs to learn as preparation for work on a Ph. D. degree in stat- tics. The course is designed for two 15-week semesters, with three lecture hours and two discussion hours in each week. Students in this course are assumed to have a good knowledge of advanced calculus. A course in real analysis or measure theory prior to this course is often recommended. Chapter 1 provides a quick overview of important concepts and results in measure-theoretic probability theory that are used as tools in the rest of the book. Chapter 2 introduces some fundamental concepts in statistics, including statistical models, the principle of su?ciency in data reduction, and two statistical approaches adopted throughout the book: statistical decision theory and statistical inference. Each of Chapters 3 through 7 provides a detailed study of an important topic in statistical decision t- ory and inference; Chapter | | 出版日期 | Textbook 19991st edition | | 关键词 | Likelihood; mathematical statistics; probability; probability theory; statistical theory; statistics | | 版次 | 1 | | doi | https://doi.org/10.1007/b98900 | | isbn_ebook | 978-0-387-22759-7Series ISSN 1431-875X Series E-ISSN 2197-4136 | | issn_series | 1431-875X | | copyright | Springer Science+Business Media New York 1999 |
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发表于 2025-3-21 18:24:52
