Subjective and Objective Bayesian Statistics: Principles, Models, and Applications / Edition 2

Subjective and Objective Bayesian Statistics: Principles, Models, and Applications / Edition 2

by S. James Press, Chib, Press
     
 

ISBN-10: 0471348430

ISBN-13: 9780471348436

Pub. Date: 12/09/2002

Publisher: Wiley

  • Shorter, more concise chapters provide flexible coverage of the subject.
  • Expanded coverage includes: uncertainty and randomness, prior distributions, predictivism, estimation, analysis of variance, and classification and imaging.
  • Includes topics not covered in other books, such as the de Finetti Transform.
  • Author S. James Press

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Overview

  • Shorter, more concise chapters provide flexible coverage of the subject.
  • Expanded coverage includes: uncertainty and randomness, prior distributions, predictivism, estimation, analysis of variance, and classification and imaging.
  • Includes topics not covered in other books, such as the de Finetti Transform.
  • Author S. James Press is the modern guru of Bayesian statistics.

Product Details

ISBN-13:
9780471348436
Publisher:
Wiley
Publication date:
12/09/2002
Series:
Wiley Series in Probability and Statistics Series, #328
Edition description:
REV
Pages:
600
Product dimensions:
6.24(w) x 9.55(h) x 1.42(d)

Related Subjects

Table of Contents

Preface.

Preface to the First Edition.

A Bayesian Hall of Fame.

PART I: FOUNDATIONS AND PRINCIPLES.

1. Background.

2. A Bayesian Perspective on Probability.

3. The Likelihood Function.

4. Bayes' Theorem.

5. Prior Distributions.

PART II: NUMERICAL IMPLEMENTATION OF THE BAYESIAN PARADIGM.

6. Markov Chain Monte Carlo Methods (Siddhartha Chib).

7. Large Sample Posterior Distributions and Approximations.

PART III: BAYESIAN STATISTICAL INFERENCE AND DECISION MAKING.

8. Bayesian Estimation.

9. Bayesian Hypothesis Testing.

10. Predictivism.

11. Bayesian Decision Making.

PART IV: MODELS AND APPLICATIONS.

12. Bayesian Inference in the General Linear Model.

13. Model Averaging (Merlise Clyde).

14. Hierarchical Bayesian Modeling (Alan Zaslavsky).

15. Bayesian Factor Analysis.

16. Bayesian Inference in Classification and Discrimination.

Description of Appendices.

Appendix 1. Bayes, Thomas, (Hilary L. Seal).

Appendix 2. Thomas Bayes. A Bibliographical Note (George A. Barnard).

Appendix 3. Communication of Bayes' Essay to the Philosophical Transactions of the Royal Society of London (Richard Price).

Appendix 4. An Essay Towards Solving a Problem in the Doctrine of Chances (Reverend Thomas Bayes).

Appendix 5. Applications of Bayesian Statistical Science.

Appendix 6. Selecting the Bayesian Hall of Fame.

Appendix 7. Solutions to Selected Exercises.

Bibliography.

Subject Index.

Author Index.

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