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Conditioning in Markov Chain Monte Carlo
Authors:Charles J. Geyer
Affiliation:School of Statistics, University of Minnesota , 270 Vincent Hall, 206 Church St. S.E., Minneapolis , MN , 55455 , USA
Abstract:Abstract

The so-called “Rao-Blackwellized” estimators proposed by Gelfand and Smith do not always reduce variance in Markov chain Monte Carlo when the dependence in the Markov chain is taken into account. An illustrative example is given, and a theorem characterizing the necessary and sufficient condition for such an estimator to always reduce variance is proved.
Keywords:Gibbs sampler  Markov chain Monte Carlo  Rao-Blackwellization
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