Decomposition of Some Well-Known Variance Reduction Techniques

Barry L. Nelson

doi:10.1080/00949658608810871

Decomposition of Some Well-Known Variance Reduction Techniques

Barry L. Nelson

Industrial Engineering and Management Sciences

Research output: Contribution to journal › Article › peer-review

18 Scopus citations

Abstract

Proliferation of techniques and lack of unifying structure have hindred both study and application of variance reduction. We view any variance reduction technique (VRT) as a transformation from one experiment to another, which leads to an exhaustive taxonomy of VRTs. In this paper, seven familiar VRTs are expressed in our taxonomy as compositions of elemental transformations from six basic classes. Our objective is to use the reader’s knowledge of these well-known techniques to illustrate the taxonomy.

Original language	English (US)
Pages (from-to)	183-209
Number of pages	27
Journal	Journal of Statistical Computation and Simulation
Volume	23
Issue number	3
DOIs	https://doi.org/10.1080/00949658608810871
State	Published - Jan 1 1986

Keywords

Antithetic variates
Monte Carlo
common random numbers
conditional expectations
control variates
importance sampling
poststratified sampling
simulation
swindles
variance reduction

ASJC Scopus subject areas

Statistics and Probability
Modeling and Simulation
Statistics, Probability and Uncertainty
Applied Mathematics

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abstract = "Proliferation of techniques and lack of unifying structure have hindred both study and application of variance reduction. We view any variance reduction technique (VRT) as a transformation from one experiment to another, which leads to an exhaustive taxonomy of VRTs. In this paper, seven familiar VRTs are expressed in our taxonomy as compositions of elemental transformations from six basic classes. Our objective is to use the reader{\textquoteright}s knowledge of these well-known techniques to illustrate the taxonomy.",

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note = "Funding Information: The Office of Naval Research provided partial support via contract N00014-79-C-0832. We thank James R. Wilson for both general discussions and specific suggestions that have improved this paper and clarified our thoughts. Funding Information: tResearch partially supported by Ofice of Naval Research contract N00014-79-C-0832. Copyright: Copyright 2015 Elsevier B.V., All rights reserved.",

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Decomposition of Some Well-Known Variance Reduction Techniques

Abstract

Keywords

ASJC Scopus subject areas

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