Subjective and objective Bayesian statistics : principles, models, and applications /

* 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 Finet...

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Bibliographic Details
Main Author:	Press, S. James
Format:	eBook
Language:	English
Language Notes:	English.
Published:	Hoboken, N.J. : Wiley-Interscience, ©2003.
Edition:	2nd ed.
Series:	Wiley series in probability and statistics.
Subjects:	Bayesian statistical decision theory. Electronic books.
Online Access:	Connect to the full text of this electronic book

Table of Contents:

Subjective and Objective Bayesian Statistics Principles, Models, and Applications; 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. Bayeds' Theorem; 5. Prior Distributions; PART II. NUMERICAL IMPLEMENTATION OF THE BAYESIAN PARADIGM; 6. Markov Chain Monte Carlo Methads; 7. Large Sample Posterior Distributions and Approximations; PART III. BAYESIAN STATISTICAL INFERENCE AND DECISION MAKING; 8. Bayesian Estimation; 9. Bayesian Hypothesis Testing.