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 foreign Society for Bayesian Analysis
Now in its 3rd variation, this vintage ebook is greatly thought of the best textual content on Bayesian equipment, lauded for its available, sensible method of examining info and fixing study difficulties. Bayesian facts research, 3rd Edition maintains to take an utilized method of research utilizing up to date Bayesian tools. The authors—all leaders within the data community—introduce simple innovations from a data-analytic viewpoint ahead of featuring complicated tools. in the course of the textual content, various labored examples drawn from actual functions and examine 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 info criteria
- Improved convergence tracking and powerful pattern dimension 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 ideas. For graduate scholars, the textual content provides powerful present techniques to Bayesian modeling and computation in records and comparable fields. For researchers, it presents an collection of Bayesian equipment in utilized records. extra fabrics, together with facts units utilized in the examples, options to chose workouts, and software program directions, can be found at the book’s internet page.
Read or Download Bayesian Data Analysis, Third Edition (Chapman & Hall/CRC Texts in Statistical Science) PDF
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