Botev, ZI, Ridder, A and Rojas-Nandayapa, L ORCID: 0000-0001-5652-3183
(2016)
SEMIPARAMETRIC CROSS ENTROPY FOR RARE-EVENT SIMULATION.
JOURNAL OF APPLIED PROBABILITY, 53 (3).
pp. 633-649.
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1310.3596v1.pdf - Submitted version Download (230kB) |
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.
Item Type: | Article |
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Additional Information: | Source info: Tinbergen Institute Discussion Paper 13-127/III |
Uncontrolled Keywords: | Light-tailed, regularly-varying, subexponential, rare-event probability, cross entropy method |
Depositing User: | Symplectic Admin |
Date Deposited: | 04 Nov 2016 08:38 |
Last Modified: | 19 Jan 2023 07:26 |
DOI: | 10.1017/jpr.2016.31 |
Related URLs: | |
URI: | https://livrepository.liverpool.ac.uk/id/eprint/3004345 |