Bayesian data analysis

Author(s)

• Gelman, Andrew
• Carlin, John B.
• Stern, Hal S.
• Dunson, David B.
• Vehtari, Aki
• Rubin, Donald B.

Bibliographic Information

Bayesian data analysis

Andrew Gelman ... [et al.]

（Texts in statistical science）

CRC Press, c2014

3rd ed

• : hardback

Other Title

BDA3

Note

Includes bibliographical references (p. 607-639) and indexes

Other editors: John B. Carlin, Hal S. Stern, David B. Dunson, Aki Vehtari, Donald B. Rubin

Description and Table of Contents

Description

Winner of the 2016 De Groot Prize from the International Society for Bayesian Analysis Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The authors-all leaders in the statistics community-introduce basic concepts from a data-analytic perspective before presenting advanced methods. Throughout the text, numerous worked examples drawn from real applications and research emphasize the use of Bayesian inference in practice. New to the Third Edition Four new chapters on nonparametric modeling Coverage of weakly informative priors and boundary-avoiding priors Updated discussion of cross-validation and predictive information criteria Improved convergence monitoring and effective sample size calculations for iterative simulation Presentations of Hamiltonian Monte Carlo, variational Bayes, and expectation propagation New and revised software code The book can be used in three different ways. For undergraduate students, it introduces Bayesian inference starting from first principles. For graduate students, the text presents effective current approaches to Bayesian modeling and computation in statistics and related fields. For researchers, it provides an assortment of Bayesian methods in applied statistics. Additional materials, including data sets used in the examples, solutions to selected exercises, and software instructions, are available on the book's web page.

Table of Contents

Fundamentals of Bayesian Inference. Fundamentals of Bayesian Data Analysis. Advanced Computation. Regression Models. Nonlinear and Nonparametric Models. Appendices.

by "Nielsen BookData"

Details

• NCID: BB13945229
• ISBN:
  • 9781439840955
• LCCN: 2013039507
• Country Code: us
• Title Language Code: eng
• Text Language Code: eng
• Place of Publication: Boca Raton
• Pages/Volumes: xiv, 661 p.
• Size: 26 cm
• Classification:
  • LCC : QA279.5
  • DC23 : 519.5/42
• Subject Headings:
  • LCSH : Bayesian statistical decision theory
• Parent Bibliography ID:
  • BA22776704