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The Large Deviation Theory of Importance Sampling Estimators

  • James Antonio Bucklew
Part of the Springer Series in Statistics book series (SSS)

Abstract

In this section we first prove a very general theorem regarding the variance rate of importance sampling estimators. At first sight the setting may appear to be fairly abstract but we argue that the level of generality presented here will pay dividends later on. We encourage the reader to follow the problem setup given here with some care and then compare it with the first example given below to see how this framework is actually used.

Keywords

Markov Chain Importance Sampling Moment Generate Function Simulation Distribution Asymptotic Rate 
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 Science+Business Media New York 2004

Authors and Affiliations

  • James Antonio Bucklew
    • 1
  1. 1.Department of Electrical and Computer EngineeringUniversity of Wisconsin-MadisonMadisonUSA

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