J. Blanchet and Y. Shi, “Efficient rare event simulation for heavy-tailed systems via cross entropy,” Proceedings of the 2011 Winter Simulation Conference (WSC), Phoenix, AZ, USA, 2011, pp. 516-527, doi: 10.1109/WSC.2011.6147781.
Abstract
The cross entropy method is a popular technique that has been used in the context of rare event simulation in order to obtain a good selection (in the sense of variance performance tested empirically) of an importance sampling distribution. This iterative method requires the selection of a suitable parametric family to start with. The selection of the parametric family is very important for the successful application of the method. Two properties must be enforced in such a selection. First, subsequent updates of the parameters in the iterations must be easily computable and, second, the parametric family should be powerful enough to approximate, in some sense, the zero-variance importance sampling distribution. We obtain parametric families for which these two properties are satisfied for a large class of heavy-tailed systems including Pareto and Weibull tails. Our estimators are shown to be strongly efficient in these …
Authors
Jose Blanchet, Yixi Shi
Publication date
2011/12/11
Conference
Proceedings of the 2011 Winter Simulation Conference (WSC)
Pages
516-527
Publisher
IEEE
