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Bayesian Computation with R

Jim Albert
11.2 An R Interface to WinBUGS
Bayesian Computation with R - Jim Albert - Your Highlight Location 2244-2246 | Added on Tuesday, 9 April 13 01:02:24
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WinBUGS is a program for sampling from a general posterior distribution of a Bayesian model by use of Gibbs sampling and a general class of proposal densities. To describe the use of WinBUGS in a very simple setting, suppose you observe y distributed binomial(n, p) and a beta(a, ~3) prior is placed on p where a = 0.5 and 0 = 0.5. You observe y = 7 successes in a sample of n = 50 and you wish to construct a 90% interval estimate for p.
Bayesian Computation with R - Jim Albert - Your Highlight Location 2227-2230 | Added on Monday, 8 April 13 20:54:56
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Gelman et al (2003), chapter 5, provide a good introduction to hierarchical models.
Bayesian Computation with R - Jim Albert - Your Highlight Location 1461-1462 | Added on Monday, 8 April 13 19:02:58
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Howard (1998) gives a general discussion of inference for the two-by-two contingency table, contrasting frequentist and Bayesian approaches.
Bayesian Computation with R - Jim Albert - Your Highlight Location 672-673 | Added on Monday, 8 April 13 18:46:31
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Berry (1996) and Albert and Rossman (2001) describe the Bayesian approach for proportions at an introductory statistics level. Albert (1996) describes Bayesian computational algorithms for proportions using the statistics package Minitab. Antleman (1996) and Bolstad (2004) provide elementary descriptions of Bayesian thinking suitable for undergraduate statistics classes.
Bayesian Computation with R - Jim Albert - Your Highlight Location 338-340 | Added on Monday, 8 April 13 18:41:38
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Verzani (2004) is a good book describing the use of R in an introductory statistics course; in particular, the book is helpful
Bayesian Computation with R - Jim Albert - Your Highlight Location 188-189 | Added on Monday, 8 April 13 18:33:59
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An R package, LearnBayes, available from the CRAN site, has been written to accompany this text.
Bayesian Computation with R - Jim Albert - Your Highlight Location 30-30 | Added on Monday, 8 April 13 18:27:28
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This book would serve as a useful companion to the introductory Bayesian texts Gelman et al (2003), Carlin and Louis (2000), Press (2003), Gill (2002), or Lee (2004).
Bayesian Computation with R - Jim Albert - Your Highlight Location 19-20 | Added on Monday, 8 April 13 18:26:48
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