By Andrew Gelman,John B. Carlin,Hal S. Stern,David B. Dunson,Aki Vehtari,Donald B. Rubin
Winner of the 2016 De Groot Prize from the overseas Society for Bayesian Analysis
Now in its 3rd version, this vintage e-book is broadly thought of the major textual content on Bayesian equipment, lauded for its available, sensible method of reading info and fixing examine difficulties. Bayesian information research, 3rd Edition keeps to take an utilized method of research utilizing up to date Bayesian equipment. The authors—all leaders within the facts community—introduce simple recommendations from a data-analytic standpoint prior to offering complex tools. through the textual content, a variety of labored examples drawn from actual purposes and study emphasize using Bayesian inference in practice.
New to the 3rd Edition
- Four new chapters on nonparametric modeling
- Coverage of weakly informative priors and boundary-avoiding priors
- Updated dialogue of cross-validation and predictive details criteria
- Improved convergence tracking and potent pattern measurement calculations for iterative simulation
- Presentations of Hamiltonian Monte Carlo, variational Bayes, and expectation propagation
- New and revised software program code
The e-book can be utilized in 3 alternative ways. For undergraduate scholars, it introduces Bayesian inference ranging from first rules. For graduate scholars, the textual content offers powerful present techniques to Bayesian modeling and computation in records and similar fields. For researchers, it presents an collection of Bayesian tools in utilized records. extra fabrics, together with info units utilized in the examples, suggestions to chose workouts, and software program directions, can be found at the book’s net page.
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Extra info for Bayesian Data Analysis, Third Edition (Chapman & Hall/CRC Texts in Statistical Science)
Bayesian Data Analysis, Third Edition (Chapman & Hall/CRC Texts in Statistical Science) by Andrew Gelman,John B. Carlin,Hal S. Stern,David B. Dunson,Aki Vehtari,Donald B. Rubin