Essential Statistical Inference: Theory and Methods (Springer Texts in Statistics, 120)

Boos, Dennis D.; Stefanski, L A

ISBN 10: 1461448174 / ISBN 13: 9781461448174

Published by Springer (edition 2013), 2013

About this Item

The item might be beaten up but readable. May contain markings or highlighting, as well as stains, bent corners, or any other major defect, but the text is not obscured in any way.

Seller Inventory # 1461448174-7-1

Bibliographic Details

• Title: Essential Statistical Inference: Theory and Methods (Springer Texts in Statistics, 120)
• Publisher: Springer (edition 2013)
• Publication Date: 2013
• Language: English
• ISBN 10: 1461448174
• ISBN 13: 9781461448174
• Binding: Hardcover
• Edition: 2013.
• Condition: Fair

About this title

Synopsis

​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 the Author

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.