[学科前沿] 【2013年springer】Essential Statistical Inference [推广有奖]

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delmarloop(真实交易用户) 发表于 2013-5-2 10:21:56

THANKS....

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delmarloop(真实交易用户) 发表于 2013-5-2 10:22:24

THANKS.....

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ym2009(真实交易用户) 发表于 2013-5-2 14:51:27

谢谢分享。、。

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gemini69(真实交易用户) 发表于 2013-5-2 17:31:40

Essential Statistical Inference: Theory and Methods

Dennis D. Boos (Author), L A Stefanski (Author)

Publication Date: February 6, 2013 | ISBN-10: 1461448174 | ISBN-13: 978-1461448174 | Edition: 2013

This book is for students and researchers who have had a first year graduate level mathematical statistics course. It covers classical likelihood, Bayesian, and permutation inference; an introduction to basic asymptotic distribution theory; and modern topics like M-estimation, the jackknife, and the bootstrap. R code is woven throughout the text, and there are a large number of examples and problems. An important goal has been to make the topics accessible to a wide audience, with little overt reliance on measure theory. A typical semester course consists of Chapters 1-6 (likelihood-based estimation and testing, Bayesian inference, basic asymptotic results) plus selections from M-estimation and related testing and resampling methodology. Dennis Boos and Len Stefanski are professors in the Department of Statistics at North Carolina State. Their research has been eclectic, often with a robustness angle, although Stefanski is also known for research concentrated on measurement error, including a co-authored book on non-linear measurement error models. In recent years the authors have jointly worked on variable selection methods.