A slowly mixing Markov chain with implications for Gibbs sampling

We give a Markov chain that converges to its stationary distribution very slowly. It has the form of a Gibbs sampler running on a posterior distribution of a parameter [theta] given data X. Consequences for Gibbs sampling are discussed.

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Year of publication:	1993
Authors:	Matthews, Peter
Published in:	Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 17.1993, 3, p. 231-236
Publisher:	Elsevier
Keywords:	Gibbs sampling posterior distribution mixing rate coupling

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005223128