Bayesian Data Analysis
Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its …
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.
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Solutions to some exercises from Bayesian Data Analysis, second edition, by Gelman, Carlin, Stern, and Rubin. 4 Mar 2012. These solutions are in progress.
Edited by Deborah G. Mayo, Aris Spanos and Kent W. Staley http://www.rmm-journal.de/. Andrew Gelman. Induction and Deduction in Bayesian. Data Analysis*.
Popular view of Bayesian statistics. ▫ Subjective probability. ▫ Elicited prior distributions. ▫ Bayesian data analysis as we do it. ▫ Hierarchical modeling.
2018年9月18日 - Ascii data files are used through out the entire Bayesian Analysis software. Often they are used for simple things like input to various packages.