Understanding computational Bayesian statistics
By: William M. Bolstad
Series: Wiley series in computational statistics; Wiley series in computational statistics
Publisher: Wiley
Published: 2010
Place of publication: Hoboken, N.J
Language: eng
Number of pages: 315
ISBN-13: 9780470046098
Description: 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.
Notes: Includes bibliographical references (p. 307-311) and index.
Table of contents: title: Introduction to Bayesian statistics; title: Monte Carlo sampling from the posterior; title: Bayesian inference; title: Bayesian statistics using conjugate priors; title: Markov chains; title: Markov chain Monte Carlo sampling from the posterior; title: Statistical inference from a Markov chain Monte Carlo sample; title: Logistic regression; title: Poisson regression and proportional hazards model; title: Gibbs sampling and hierarchical models; title: Going forward with Markov chain Monte Carlo; title: Appendix A: Using the included Minitab macros; title: Appendix B: Using the included R functions.