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On a Generalized Splitting Method for Sampling from a Conditional Distribution

Abstract : We study the behavior of a splitting method for sampling from a given distribution conditional on the occurrence of a rare event. The method returns a random-sized sample of points such that unconditionally on the sample size, each point is distributed exactly according to the original distribution conditional on the rare event. For a cost function which is nonzero only when the rare event occurs, the method provides an unbiased estimator of the expected cost, but if we select at random one of the returned points, its distribution differs in general from the exact conditional distribution given the rare event. However, we prove that if we repeat the algorithm n times and select one of the returned points at random, the distribution of the selected point converges to the exact one in total variation when n increases.
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Conference papers
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https://hal.inria.fr/hal-01949896
Contributor : Bruno Tuffin <>
Submitted on : Monday, December 10, 2018 - 2:33:38 PM
Last modification on : Monday, July 20, 2020 - 12:34:52 PM

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  • HAL Id : hal-01949896, version 1

Citation

Pierre l'Ecuyer, Zdravko Botev. On a Generalized Splitting Method for Sampling from a Conditional Distribution. 2018 Winter Simulation Conference, Dec 2018, Goteborg, Sweden. ⟨hal-01949896⟩

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