Essential Statistical Inference PDF ePub eBook

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Essential Statistical Inference free pdf 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.

About Dennis D Boos

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.

Details Book

Author : Dennis D Boos
Publisher : Springer-Verlag New York Inc.
Data Published : 06 February 2013
ISBN : 1461448174
EAN : 9781461448174
Format Book : PDF, Epub, DOCx, TXT
Number of Pages : 568 pages
Age + : 15 years
Language : English
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