Statistical Decision Theory and Bayesian Analysis, 2/e
James O. Berger
"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 American Mathematical Society 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.
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; Appendices.