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Replication Schemes For Limiting Expectations

Published online by Cambridge University Press:  27 July 2009

Bennett L. Fox  and
Peter W. Glynn
Bennett L. Fox
Affiliation:
Department of MathematicsUniversity of Colorado Denver, Colorado 80204
Peter W. Glynn
Affiliation:
Department of Operations ResearchStanford University Stanford, California 94305-4022
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Abstract

We show that natural estimators occurring in certain simulation settings have convergence rates less than the canonical rate usually associated with simulation. These natural estimators use replication schemes that attenuate bias. For some important examples, we find alternative estimators that converge at the canonical rate. The implications of these asymptotic comparisons for choosing good strategies when the computer-time budget is modest are discussed.

Type
Articles
Information
Probability in the Engineering and Informational Sciences , Volume 3 , Issue 3 , July 1989 , pp. 299 - 318
Copyright
Copyright © Cambridge University Press 1989

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