Semiparametric cross-entropy for rare-event simulation

A.A.N. Ridder, Z. Botev, L. Rojas-Nandayapa

Research output: Contribution to JournalArticleAcademicpeer-review


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.
Original languageEnglish
Pages (from-to)633-649
JournalJournal of Applied Probability
Issue number3
Publication statusPublished - 2016


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