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Bayesian methods : a social and behavioral sciences approach / Jeff Gill.

By: Material type: TextTextSeries: Statistics in the social and behavioral sciences seriesPublication details: Boca Raton : CRC Press, c2015.Edition: 3rd edDescription: xiii, 680 p. : illustrations ; 26 cmISBN:
  • 9781439862483 (hardcover : alk. paper)
Subject(s): DDC classification:
  • 000SA.161 23 G475
Contents:
1. Background and introduction-- 2. Specifying Bayesian models-- 3. The normal and student's-t models-- 4. The Bayesian prior-- 5. The Bayesian linear model-- 6. Assessing model quality-- 7. Bayesian hypothesis testing and the Bayes factor-- 8. Bayesian decision theory-- 9. Monte Carlo and related iterative methods-- 10. Basic of Markov Chain Monte Carlo-- 11. Implementing Bayesian models with Markov Chain Monte Carlo-- 12. Bayesian Hierarchical Models-- 13. Some Markov chain Monte Carlo theory-- 14. Utilitarian Markov Chain Monte Carlo-- 15. Markov Chain Monte Carlo extensions-- Appendix A. Generalized linear model review-- Appendix B. common probability distributions-- References-- Author index-- Subject index.
Summary: Now that Bayesian modeling has become standard, MCMC is well understood and trusted, and computing power continues to increase, Bayesian Methods: A Social and Behavioral Sciences Approach, Third Edition focuses more on implementation details of the procedures and less on justifying procedures. The expanded examples reflect this updated approach.
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Holdings
Item type Current library Call number Status Date due Barcode Item holds
Books ISI Library, Kolkata 000SA.161 G475 (Browse shelf(Opens below)) Available 136114
Total holds: 0

Includes bibliographical references and index.

1. Background and introduction--
2. Specifying Bayesian models--
3. The normal and student's-t models--
4. The Bayesian prior--
5. The Bayesian linear model--
6. Assessing model quality--
7. Bayesian hypothesis testing and the Bayes factor--
8. Bayesian decision theory--
9. Monte Carlo and related iterative methods--
10. Basic of Markov Chain Monte Carlo--
11. Implementing Bayesian models with Markov Chain Monte Carlo--
12. Bayesian Hierarchical Models--
13. Some Markov chain Monte Carlo theory--
14. Utilitarian Markov Chain Monte Carlo--
15. Markov Chain Monte Carlo extensions--
Appendix A. Generalized linear model review--
Appendix B. common probability distributions--
References--
Author index--
Subject index.

Now that Bayesian modeling has become standard, MCMC is well understood and trusted, and computing power continues to increase, Bayesian Methods: A Social and Behavioral Sciences Approach, Third Edition focuses more on implementation details of the procedures and less on justifying procedures. The expanded examples reflect this updated approach.

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