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Variance Reduction Techniques

  • Christiane Lemieux
Chapter
Part of the Springer Series in Statistics book series (SSS)

In Chap. 1, we said that one way of improving the Monte Carlo integration error is to try reducing the variance σ2 of the integrand f. More precisely, the goal is to find another function Ø whose integral is equal to the integral of f but whose variance is smaller than that of f. Methods that achieve this are called variance reduction techniques, and we will be describing several of them in this chapter. This topic has been widely studied and is surveyed, for example, in [45, 165, 243, 247, 321, 391], which also give several other references.

Keywords

Service Time Importance Sampling Variance Reduction Monte Carlo Estimator Interarrival Time 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag New York 2009

Authors and Affiliations

  1. 1.University of WaterlooDept. Statistics & Actuarial ScienceWaterlooCanada

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