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Bayesian Computation Via the Gibbs Sampler and Related Markov Chain Monte Carlo Methods

A. F. M. Smith and G. O. Roberts
Journal of the Royal Statistical Society. Series B (Methodological)
Vol. 55, No. 1 (1993), pp. 3-23
Published by: Wiley for the Royal Statistical Society
Stable URL: http://www.jstor.org/stable/2346063
Page Count: 21
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Bayesian Computation Via the Gibbs Sampler and Related Markov Chain Monte Carlo Methods
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Abstract

The use of the Gibbs sampler for Bayesian computation is reviewed and illustrated in the context of some canonical examples. Other Markov chain Monte Carlo simulation methods are also briefly described, and comments are made on the advantages of sample-based approaches for Bayesian inference summaries.

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