DECOMPOSITION APPROACH TO VARIANCE REDUCTION.

Barry L. Nelson*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

For analyzing stochastic models, simulation trades the tractability problems of analytical techniques for the problem of sampling variability. Variance reduction techniques (VRTs) attack this problem by transforming the simulation experiment in a way that makes it more statistically efficient. Unfortunately, VRTs are infrequently used, even though significant reductions are possible in practical problems. The author introduces some basic concepts of variance reduction, and uses a new taxonomy of VRTs as the basis for an algorithm to select appropriate VRTs for general simulation experiments.

Original languageEnglish (US)
Title of host publicationWinter Simulation Conference Proceedings
EditorsDonald T. Gantz, Gerard C. Blais, Susan L. Solomon
PublisherIEEE
Pages23-32
Number of pages10
ISBN (Print)0911801073
StatePublished - Dec 1 1985

ASJC Scopus subject areas

  • Chemical Health and Safety
  • Software
  • Safety, Risk, Reliability and Quality
  • Applied Mathematics
  • Modeling and Simulation

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