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Comparing stochastic systems using regenerative simulation with common random numbers

Published online by Cambridge University Press:  01 July 2016

Philip Heidelberger  and
Donald L. Iglehart
Philip Heidelberger*
Affiliation:
IBM Thomas J. Watson Research Center
Donald L. Iglehart*
Affiliation:
Stanford University
*
∗Postal address: IBM Thomas J. Watson Research Center, P.O. Box 218, Yorktown Heights, N.Y. 10598, U.S.A.
∗∗Postal address: Department of Operations Research, Stanford University, Stanford, CA 94305, U.S.A.
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Abstract

Suppose two alternative designs for a stochastic system are to be compared. These two systems can be simulated independently or dependently. This paper presents a method for comparing two regenerative stochastic processes in a dependent fashion using common random numbers. A set of sufficient conditions is given that guarantees that the dependent simulations will produce a variance reduction over independent simulations. Numerical examples for a variety of simple stochastic models are included which illustrate the variance reduction achieved.

Keywords

CENTRAL LIMIT THEOREMCOMMON RANDOM NUMBERSREGENERATIVE METHODSIMULATIONSTATISTICAL ESTIMATIONVARIANCE REDUCTION
Type
Research Article
Information
Advances in Applied Probability , Volume 11 , Issue 4 , December 1979 , pp. 804 - 819
Copyright
Copyright © Applied Probability Trust 1979 

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Footnotes

Research supported by NSF Grant MCS-23607 and ONR Contract N00014-76-C-0578.

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