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September 2016 Semiparametric cross entropy for rare-event simulation
Z. I. Botev, A. Ridder, L. Rojas-Nandayapa
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J. Appl. Probab. 53(3): 633-649 (September 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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Z. I. Botev. A. Ridder. L. Rojas-Nandayapa. "Semiparametric cross entropy for rare-event simulation." J. Appl. Probab. 53 (3) 633 - 649, September 2016.

Information

Published: September 2016
First available in Project Euclid: 13 October 2016

zbMATH: 1355.65022
MathSciNet: MR3570085

Subjects:
Primary: 65C05
Secondary: 62H20 , 65C40

Keywords: cross entropy method , Light-tailed , rare-event probability , regularly-varying

Rights: Copyright © 2016 Applied Probability Trust

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Vol.53 • No. 3 • September 2016
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