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

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  • 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.
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Editorial Reviews

From the Publisher
"…written in a clear, accessible manner…an enjoyable read and a comprehensive introduction to Bayesian theory and methods." (Journal of the American Statistical Association, March 2005)

"The book is well written. It should continue the success of the first edition and become the main reference book in the field.” (Interfaces, March-April 2004)

"…among several books I have reviewed, this is one of the best. I very strongly recommend this book to statisticians and applied researchers." (Journal of Statistical Computation & Simulation, March 2004)

"...a welcome addition to the library of any practicing statistician, not only as a thorough and readable text on Bayesian statistics, but also as a rich source of reference material for understanding the historical development of the subject." (Technometrics, Vol. 45, No. 4, November 2003)

“...a second edition...but really a new book, not merely the first edition with a few changes inserted...a completely restructured book with major new chapters and material...” (Quarterly of Applied Mathematics, Vol. LXI, No. 2, June 2003)

"...this second edition is a completely restructured book with major new chapters and material..." (Zentralblatt Math, 2003)

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Product Details

Meet the Author

S. JAMES PRESS, PhD, is a Distinguished Professor in the Department of Statistics at the University of California, Riverside. He is the author (with Judith M. Tanur) of The Subjectivity of Scientists and the Bayesian Approach, also published by John Wiley & Sons, Inc., 2001.
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Table of Contents


Preface to the First Edition.

A Bayesian Hall of Fame.


1. Background.

2. A Bayesian Perspective on Probability.

3. The Likelihood Function.

4. Bayes' Theorem.

5. Prior Distributions.


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

7. Large Sample Posterior Distributions and Approximations.


8. Bayesian Estimation.

9. Bayesian Hypothesis Testing.

10. Predictivism.

11. Bayesian Decision Making.


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.


Subject Index.

Author Index.

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