Abstract
Abstract Computer-intensive algorithms, such as the Gibbs sampler, have become increasingly popular statistical tools, both in applied and theoretical work. The properties of such algorithms, however, may sometimes not be obvious. Here we give a simple explanation of how and why the Gibbs sampler works. We analytically establish its properties in a simple case and provide insight for more complicated cases. There are also a number of examples.
Keywords
Gibbs samplingSimple (philosophy)Computer scienceStatistical physicsAlgorithmMathematicsArtificial intelligenceBayesian probabilityPhysicsEpistemologyPhilosophy
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Publication Info
- Year
- 1992
- Type
- article
- Volume
- 46
- Issue
- 3
- Pages
- 167-174
- Citations
- 2342
- Access
- Closed
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Cite This
George Casella,
Edward I. George
(1992).
Explaining the Gibbs Sampler.
The American Statistician
, 46
(3)
, 167-174.
https://doi.org/10.1080/00031305.1992.10475878
Identifiers
- DOI
- 10.1080/00031305.1992.10475878