Synopses & 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.
Synopsis
Incorporating new and updated information, this edition of the bestselling text continues to emphasize practice over theory, describing how to conceptualize, perform, and critique statistical analyses from a Bayesian perspective.
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
Includes bibliographical references (p. 611-646) and indexes.
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.