Bayesian methods for data analysis

Author(s)

Bibliographic Information

Bayesian methods for data analysis

Bradley P. Carlin, Thomas A. Louis

（Texts in statistical science）

CRC Press, c2009

3rd ed

  • : hardcover

Available at  / 35 libraries

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Note

Includes bibliographical references (p. [487]-520) and indexes

Description and Table of Contents

Description

Broadening its scope to nonstatisticians, Bayesian Methods for Data Analysis, Third Edition provides an accessible introduction to the foundations and applications of Bayesian analysis. Along with a complete reorganization of the material, this edition concentrates more on hierarchical Bayesian modeling as implemented via Markov chain Monte Carlo (MCMC) methods and related data analytic techniques. New to the Third Edition New data examples, corresponding R and WinBUGS code, and homework problems Explicit descriptions and illustrations of hierarchical modeling-now commonplace in Bayesian data analysis A new chapter on Bayesian design that emphasizes Bayesian clinical trials A completely revised and expanded section on ranking and histogram estimation A new case study on infectious disease modeling and the 1918 flu epidemic A solutions manual for qualifying instructors that contains solutions, computer code, and associated output for every homework problem-available both electronically and in print Ideal for Anyone Performing Statistical Analyses Focusing on applications from biostatistics, epidemiology, and medicine, this text builds on the popularity of its predecessors by making it suitable for even more practitioners and students.

Table of Contents

Approaches for Statistical Inference. The Bayes Approach. Bayesian Computation. Model Criticism and Selection. The Empirical Bayes Approach. Bayesian Design. Special Methods and Models. Case Studies. Appendices. References. Indices.

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