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Bayesian Data Analysis (2ND 03 Edition)by Gelman and Carlin and Stern and Rubin (eds.)
Synopses & ReviewsPublisher Comments: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. Book News Annotation:This graduate textbook introduces the fundamentals of Bayesian
inference and modeling, describes methods for computing posterior
distributions in hierarchical models, and explores a few standard
linear regression and generalized linear models. The second edition
adds chapters on nonlinear models and decision analysis.
Annotation (c)2003 Book News, Inc., Portland, OR (booknews.com) Synopsis:Emphasising practice over theory, this second edition incorporates new material on how Bayesian methods are connected to other approaches. It features a stronger focus upon MCMC, more examples and an added chapter on further computation topics. Synopsis: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 critiques statistical analysis from a Bayesian perspective. Changes in the new edition include: added material on how Bayesian methods are connected to other approaches, stronger focus on MCMC, added chapter on further computation topics, more examples, and additional chapters on current models for Bayesian data analysis such as equation models, generalized linear mixed models, and more. The book is an introductory text and a reference for working scientists throughout their professional life. Synopsis:Includes bibliographical references (p. 611-646) and indexes.
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