An edition of Understanding computational Bayesian statistics
(2010)
Understanding computational Bayesian statistics
by William M. Bolstad
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Table of Contents
Introduction to Bayesian statistics
Monte Carlo sampling from the posterior
Bayesian inference
Bayesian statistics using conjugate priors
Markov chains
Markov chain Monte Carlo sampling from the posterior
Statistical inference from a Markov chain Monte Carlo sample
Logistic regression
Poisson regression and proportional hazards model
Gibbs sampling and hierarchical models
Going forward with Markov chain Monte Carlo
Appendix A: Using the included Minitab macros
Appendix B: Using the included R functions.
Edition Notes
Includes bibliographical references (p. 307-311) and index.
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- Created November 23, 2010
- 5 revisions
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| December 25, 2022 | Edited by MARC Bot | import existing book |
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| November 23, 2010 | Created by ImportBot | Imported from Library of Congress MARC record |