Bayesian Data Analysis

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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. Ba...
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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.
Uitgever Taylor & Francis
Druk 3
ISBN/EAN 9781439840955
Auteur Gelman, Andrew Carlin, John B. Stern, Hal S. Dunson, David B. Vehtari, Aki Rubin, Donald B.
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