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Accelerated Regeneration for Markov Chain Simulations

Published online by Cambridge University Press:  27 July 2009

Sigrún Andradóttir ,
James M. Calvin  and
Peter W. Glynn
Sigrún Andradóttir
Affiliation:
Department of Industrial Engineering, University of Wisconsin-Madison, 1513 University Avenue, Madison, Wisconsin 53706
James M. Calvin
Affiliation:
School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia, 30332
Peter W. Glynn
Affiliation:
Department of Operations Research, Stanford University, Stanford, California 94305
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Abstract

This paper describes a generalization of the classical regenerative method of simulation output analysis. Instead of blocking a generated sample path on returns to a fixed return state, a more general scheme to randomly decompose the path is used. In some cases, this decomposition scheme results in regeneration times that are a supersequence of the classical regeneration times. This “accelerated” regeneration is advantageous in several simulation contexts. It is shown that when this decomposition scheme accelerates regeneration relative to the classical regenerative method, it also yields a smaller asymptotic variance of the regenerative variance estimator than the classical method. Several other contexts in which increased regeneration frequency is beneficial are also discussed.

Information

Type
Research Article
Information
Probability in the Engineering and Informational Sciences , Volume 9 , Issue 4 , October 1995 , pp. 497 - 523
Copyright
Copyright © Cambridge University Press 1995

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