Bayesian Computation Via the Gibbs Sampler and Related Markov Chain Monte Carlo Methods
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ID: 291615
1993
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Abstract
SUMMARY 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.
| Reference Key |
openalex_W2017899835
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|---|---|
| Authors | A. F. M. Smith, Gareth O. Roberts |
| Journal | Journal of the Royal Statistical Society Series B (Statistical Methodology) |
| Year | 1993 |
| DOI |
10.1111/j.2517-6161.1993.tb01466.x
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| URL | |
| Keywords | Keywords not found |
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