Semiparametric Cross Entropy for Rare-Event Simulation

Zdravko Botev, Ad Ridder and Leonardo Rojas-Nandayapa
Additional contact information
Zdravko Botev: The University of New South Wales, Sydney, Australia
Ad Ridder: VU University Amsterdam
Leonardo Rojas-Nandayapa: The University of Queensland

No 13-127/III, Tinbergen Institute Discussion Papers from Tinbergen Institute

Abstract: The Cross Entropy method is a well-known adaptive importance sampling method for rare-event probability estimation, which requires estimating an optimal importance sampling density within a parametric class. In this article we estimate an optimal importance sampling density within a wider semiparametric class of distributions. We show that this semiparametric version of the Cross Entropy method frequently yields efficient estimators. We illustrate the excellent practical performance of the method with numerical experiments and show that for the problems we consider it typically outperforms alternative schemes by orders of magnitude.

Keywords: Light-Tailed; Regularly-Varying; Subexponential; Rare-Event Probability; Cross Entropy method, Markov Chain Monte Carlo (search for similar items in EconPapers)
JEL-codes: C61 C63 (search for similar items in EconPapers)
Date: 2013-09-02
New Economics Papers: this item is included in nep-ecm
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://papers.tinbergen.nl/13127.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:tin:wpaper:20130127

Access Statistics for this paper

More papers in Tinbergen Institute Discussion Papers from Tinbergen Institute Contact information at EDIRC.
Bibliographic data for series maintained by Tinbergen Office +31 (0)10-4088900 ().