Bayesian Data Analysis Andrew Gelman

Description: About this productProduct InformationIncorporating 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.Product IdentifiersPublisherCRC Press LLCISBN-10158488388xISBN-139781584883883eBay Product ID (ePID)2309770467Product Key FeaturesAuthorAndrew GelmanPublication NameBayesian Data AnalysisFormatHardcoverLanguageEnglishSeriesChapman and Hall/Crc Texts in Statistical Science Ser.Publication Year2003TypeTextbookNumber of Pages690 PagesDimensionsItem Length9.3in.Item Height1.6in.Item Width6.4in.Item Weight38.5 OzAdditional Product FeaturesSeries Volume Number106Lc Classification NumberQa279.5.B386 2003Edition DescriptionRevised Edition,New EditionEdition Number2Table of ContentFUNDAMENTALS OF BAYESIAN INFERENCE Background Single-Parameter Models Introduction to Multiparameter Models Large-Sample Inference and Connections to Standard Statistical Methods FUNDAMENTALS OF BAYESIAN DATA ANALYSIS Hierarchical Models Model Checking and Improvement Modeling Accounting for Data Collection Connections and Controversies General Advice ADVANCED COMPUTATION Overview of Computation Posterior Simulation Approximations Based on Posterior Modes Topics in Computation REGRESSION MODELS Introduction to Regression Models Hierarchical Linear Models Generalized Linear Models Models for Robust Inference and Sensitivity Analysis Analysis of Variance SPECIFIC MODELS AND PROBLEMS Mixture Models Multivariate Models Nonlinear Models Models for Missing Data Decision Analysis APPENDICES A: Standard Probability Distributions B: Outline of Proofs of Asymptotic Theorems C: Example of Computation in R and Bugs ReferencesCopyright Date2003Target AudienceCollege AudienceTopicProbability & Statistics / General, Probability & Statistics / Bayesian AnalysisLccn2003-051474Dewey Decimal519.542Dewey Edition21IllustratedYesGenreMathematics

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