Bayesian Data Analysis, Second Edition

Front Cover
CRC Press, Jul 29, 2003 - Mathematics - 696 pages
6 Reviews

Incorporating new and updated information, this second edition of THE bestselling text in Bayesian data analysis continues to emphasize practice over theory, describing how to conceptualize, perform, and critique statistical analyses from a Bayesian perspective. Its world-class authors provide guidance on all aspects of Bayesian data analysis and include examples of real statistical analyses, based on their own research, that demonstrate how to solve complicated problems. Changes in the new edition include:

  • Stronger focus on MCMC
  • Revision of the computational advice in Part III
  • New chapters on nonlinear models and decision analysis
  • Several additional applied examples from the authors' recent research
  • Additional chapters on current models for Bayesian data analysis such as nonlinear models, generalized linear mixed models, and more
  • Reorganization of chapters 6 and 7 on model checking and data collection

Bayesian computation is currently at a stage where there are many reasonable ways to compute any given posterior distribution. However, the best approach is not always clear ahead of time. Reflecting this, the new edition offers a more pluralistic presentation, giving advice on performing computations from many perspectives while making clear the importance of being aware that there are different ways to implement any given iterative simulation computation. The new approach, additional examples, and updated information make Bayesian Data Analysis an excellent introductory text and a reference that working scientists will use throughout their professional life.

  

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384 utiliser sigma -1 et pas sigma

Review: Bayesian Data Analysis

User Review  - Lurino - Goodreads

the definitive textbook for bayesian statistics. almost everything is here, but it's definitely not a gentle introduction. Read full review

Contents

Fundamentals of Bayesian Inference
1
Fundamentals of Bayesian Data Analysis
118
Advanced Computation
280
Regression Models
359
Specific Models and Problems
472
Appendixes
583
References
623
Author index
652
Subject index
666
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