for Kindle Fire, Apple, Android, Nook, Kobo, PC, Mac, BlackBerry ...

New to eBooks.com?

Learn more

Essential Statistical Inference

Theory and Methods

Essential Statistical Inference by Dennis D. Boos
Add to cart
US$ 99.00
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.
Springer; October 2012
566 pages; ISBN 9781461448181
Read online, or download in secure PDF format
Title: Essential Statistical Inference
Author: Dennis D. Boos; L. A. Stefanski
 
Buy, download and read Essential Statistical Inference (eBook) by Dennis D. Boos; L. A. Stefanski today!