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Efficient Simulation via Coupling

Published online by Cambridge University Press:  27 July 2009

Peter W. Glynn  and
Eugene W. Wong
Peter W. Glynn
Affiliation:
Department of Operations Research, Stanford University, Stanford, California 94305-4022
Eugene W. Wong
Affiliation:
Department of Operations Research, Stanford University, Stanford, California 94305-4022
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Abstract

This paper is concerned with how coupling can be used to enhance the efficiency of a certain class of terminating simulations, in Markov process settings in which the stationary distribution is known. We are able to theoretically establish that our coupling-based estimator is often more efficient than the naive estimator. In addition, we discuss extensions of our methodology to Markov process settings in which conventional coupling fails and show (for Doeblin chains) that knowledge of the stationary distribution is sometimes unnecessary.

Information

Type
Research Article
Information
Probability in the Engineering and Informational Sciences , Volume 10 , Issue 2 , April 1996 , pp. 165 - 186
Copyright
Copyright © Cambridge University Press 1996

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