A reflection-based variance reduction technique for sum of random variables

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)Not applicablepeer-review

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Detail(s)

Original languageEnglish
Title of host publicationProceedings - Winter Simulation Conference
Pages3790-3799
Publication statusPublished - 2011

Publication series

Name
ISSN (Print)0891-7736

Conference

Title2011 Winter Simulation Conference, WSC 2011
PlaceUnited States
CityPhoenix, AZ
Period11 - 14 December 2011

Abstract

Monte Carlo simulation has been widely used as a standard tool for estimating expectations. In this paper we develop a variance reduction technique for a particular case when the expectation is taken under a constraint that a sum of random variables is larger than a threshold. The proposed technique is based on a reflection argument on the sample space and requires knowing the joint density of the random variables. It turns out the technique can always guarantee a variance reduction. More importantly, the technique sheds light on how observations violating the constraint can be used more efficiently in estimation, compared to crude Monte Carlo. © 2011 IEEE.

Citation Format(s)

A reflection-based variance reduction technique for sum of random variables. / Liu, Guangwu.

Proceedings - Winter Simulation Conference. 2011. p. 3790-3799 6148071.

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)Not applicablepeer-review