Statistical Decision Theory and Bayesian Analysis

1. Front Matter

   Pages i-xvi

   PDF

2. Basic Concepts

   • James O. Berger

   Pages 1-45

3. Utility and Loss

   • James O. Berger

   Pages 46-73

4. Prior Information and Subjective Probability

   • James O. Berger

   Pages 74-117

5. Bayesian Analysis

   • James O. Berger

   Pages 118-307

6. Minimax Analysis

   • James O. Berger

   Pages 308-387

7. Invariance

   • James O. Berger

   Pages 388-431

8. Preposterior and Sequential Analysis

   • James O. Berger

   Pages 432-520

9. Complete and Essentially Complete Classes

   • James O. Berger

   Pages 521-558

10. Back Matter

    Pages 559-618

    PDF

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.

• Analysis
• Bayessches Verfahren
• Entscheidung (Math.)
• Excel
• decision theory

"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.)

• Institute of Statistics and Decision Sciences, Duke University, Durham, USA

  James O. Berger

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