Bayesian Methods for Data Analysis, Third Edition (Google eBook)

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CRC Press, Mar 23, 2011 - Mathematics - 552 pages
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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.

      

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    Contents

    CHAPTER 1 Approaches for statistical inference
    1
    CHAPTER 2 The Bayes approach
    15
    CHAPTER 3 Bayesian computation
    105
    CHAPTER 4 Model criticism and selection
    167
    CHAPTER 5 The empirical Bayes approach
    225
    CHAPTER 6 Bayesian design
    269
    CHAPTER 7 Special methods and models
    311
    CHAPTER 8 Case studies
    373
    APPENDIX A Distributional catalog
    419
    APPENDIX B Decision theory
    429
    APPENDIX C Answers to selected exercises
    445
    References
    487
    Back cover
    521
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