Mathematical statistics / Jun Shao
- 作者： Shao, Jun.
- 其他作者：
- 其他題名：
- Springer e-books
- 出版： New York : Springer c1999
- 叢書名： Springer texts in statistics
- 主題： Mathematical statistics
- ISBN： 9780387227597 (electronic bk.) 、 9780387986746 (paper)
- URL：
電子書
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讀者標籤：
- 系統號： 005167294 | 機讀編目格式
館藏資訊
This graduate textbook covers those topics in statistical theory essential for 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, while the second introduces some fundamental concepts in statistical decision theory and inference. The remaining chapters contain detailed studies on such important topics as: 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 this 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.