Bridge estimation, as described by Meng and Wong in 1996, is used to estimate the value taken by a probability density at a point in the state space. When the normalisation of the prior density is known, this value may be used to estimate a Bayes factor. It is shown that the multi-block Metropolis-Hastings estimators of citeN{chib01} are bridge sampling estimators. This identification leads to estimators for the quantity of interest which may be substantially more efficient. This report was submitted in July 2000. A revised version of this report was submitted in September 2003. The version below is the revised version. Print and electronic copies of the original version are available on request. |
Keywords
Bayes factor, Bridge estimator, Metropolis-Hastings Markov chain Monte carlo
Math Review Classification
Last Updated
Length
19 pages
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