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Semiparametric cross entropy for rare-event simulation
Published online by Cambridge University Press: 24 October 2016
Abstract
The cross entropy is a well-known adaptive importance sampling method which requires estimating an optimal importance sampling distribution within a parametric class. In this paper we analyze an alternative version of the cross entropy, where the importance sampling distribution is selected instead within a general semiparametric class of distributions. We show that the semiparametric cross entropy method delivers efficient estimators in a wide variety of rare-event problems. We illustrate the favourable performance of the method with numerical experiments.
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- Copyright © Applied Probability Trust 2016
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