Bayesian Choice From Decision-Theoretic Foundations to Computational Implementation
Edition: 2nd 2007 (Revised)
List price: $119.00
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Description: Winner of the 2004 DeGroot PrizeThe DeGroot Prize is awarded every two years by the International Societyfor Bayesian Analysis in recognition of an important, timely, thorough andnotably original contribution to the statistics literature.This graduate-level textbook presents an introduction to Bayesian statistics and decision theory. Its scope covers both the basic ideas of statistical theory, and also some of the more modern and advanced topics of Bayesian statistics such as complete class theorems, the Stein effect, Bayesian model choice, hierarchical and empirical Bayes modeling, Monte Carlo integration, including Gibbs sampling and other MCMC techniques. The second edition includes a new chapter on model choice (Chapter 7) and the chapter on Bayesian calculations (6) has been extensively revised. Chapter 4 includes a new section on dynamic models. In Chapter 3, the material on noninformative priors has been expanded, and Chapter 10 has been supplemented with more examples. The Bayesian Choice will be suitable as a text for courses on Bayesian analysis, decision theory or a combination of them.
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All the information you need in one place! Each Study Brief is a summary of one specific subject; facts, figures, and explanations to help you learn faster.
List price: $119.00
Copyright year: 2007
Publication date: 5/25/2001
Size: 6.25" wide x 9.25" long x 1.25" tall
|Preface to the Second Edition|
|Preface to the First Edition|
|List of Tables|
|List of Figures|
|From Prior Information to Prior Distributions|
|Bayesian Point Estimation|
|Tests and Confidence Regions|
|Admissibility and Complete Classes|
|Invariance, Haar Measures, and Equivariant Estimators|
|Hierarchical and Empirical Bayes Extensions|
|A Defense of the Bayesian Choice|
|A: Probability Distributions|
|Usual Pseudo-random Generators|