9781584883883-158488388X-Bayesian Data Analysis, Second Edition (Chapman & Hall/CRC Texts in Statistical Science)

Bayesian Data Analysis, Second Edition (Chapman & Hall/CRC Texts in Statistical Science)

ISBN-13: 9781584883883
ISBN-10: 158488388X
Edition: 2
Author: Andrew Gelman, Donald B. Rubin, John B. Carlin, Hal S. Stern
Publication date: 2003
Publisher: Chapman and Hall/CRC
Format: Hardcover 690 pages
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Book details

ISBN-13: 9781584883883
ISBN-10: 158488388X
Edition: 2
Author: Andrew Gelman, Donald B. Rubin, John B. Carlin, Hal S. Stern
Publication date: 2003
Publisher: Chapman and Hall/CRC
Format: Hardcover 690 pages

Summary

Bayesian Data Analysis, Second Edition (Chapman & Hall/CRC Texts in Statistical Science) (ISBN-13: 9781584883883 and ISBN-10: 158488388X), written by authors Andrew Gelman, Donald B. Rubin, John B. Carlin, Hal S. Stern, was published by Chapman and Hall/CRC in 2003. With an overall rating of 4.0 stars, it's a notable title among other Applied (Mathematics) books. You can easily purchase or rent Bayesian Data Analysis, Second Edition (Chapman & Hall/CRC Texts in Statistical Science) (Hardcover) from BooksRun, along with many other new and used Applied books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.3.

Description

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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