Markov Chain Sampling and the Product Estimator

George S. Fishman
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George S. Fishman: University of North Carolina, Chapel Hill, North Carolina

Operations Research, 1994, vol. 42, issue 6, 1137-1145

Abstract: Several recent papers have suggested using a product estimator in Monte Carlo Markov chain sampling for estimating the volume of a convex body, the permanent of a matrix and the distribution of first-passage time for a positive recurrent Markov chain. The present paper analyzes the properties of this estimator when each replication starts in an arbitrarily selected state. In particular, it describes a procedure for determining optimal warm-up intervals and optimal sample sizes to achieve a specified level of statistical accuracy at minimal cost. Also, it examines the variation in the optimal solution in response to changes in the parameters of the problem.

Keywords: simulation:; statistical; analysis (search for similar items in EconPapers)
Date: 1994
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Persistent link: https://EconPapers.repec.org/RePEc:inm:oropre:v:42:y:1994:i:6:p:1137-1145

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