Statistical Decision Theory and Bayesian Analysis

by James O. Berger

Overview

In this new edition the author has added substantial material on Bayesian analysis, including lengthy new sections on such important topics as empirical and hierarchical Bayes analysis, Bayesian calculation, Bayesian communication, and group decision making. With these changes, the book can be used as a self-contained introduction to Bayesian analysis. In addition, much of the decision-theoretic portion of the text was updated, including new sections covering such modern topics as minimax multivariate (Stein) estimation.

Product Details

ISBN-13:	9781441930743
Publisher:	Springer New York
Publication date:	12/01/2010
Series:	Springer Series in Statistics
Edition description:	Second Edition 1985
Pages:	618
Product dimensions:	6.10(w) x 9.20(h) x 1.40(d)

Table of Contents

1 Basic Concepts.- 2 Utility and Loss.- 3 Prior Information and Subjective Probability.- 4 Bayesian Analysis.- 5 Minimax Analysis.- 6 Invariance.- 7 Preposterior and Sequential Analysis.- 8 Complete and Essentially Complete Classes.- Appendix 1 Common Statistical Densities.- I Continuous.- II Discrete.- Appendix 2 Supplement to Chapter 4.- II Development of (4.121) and (4.122).- III Verification of Formula (4.123).- Appendix 3 Technical Arguments from Chapter 7.- I Verification of Formula (7.8).- II Verification of Formula (7.10).- Notation and Abbreviations.- Author Index.

Editorial Reviews

"The outstanding strengths of the book are its topic coverage, references, exposition, examples and problem sets... This book is an excellent addition to any mathematical statistician's library."

(Bulletin of the Am. Mathematical Soc.)

From the Publisher