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.
Year of publication: |
1993
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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 |
Saved in:
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