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Towards zero variance estimators for rare event probabilities

Abstract : Improving Importance Sampling estimators for rare event probabilities requires sharp approximations of conditional densities. This is achieved for events E_{n}:=(f(X₁)+...+f(X_{n}))∈A_{n} where the summands are i.i.d. and E_{n} is a large or moderate deviation event. The approximation of the conditional density of the real r.v's X_{i} 's , for 1≤i≤k_{n} with repect to E_{n} on long runs, when k_{n}/n→1, is handled. The maximal value of k compatible with a given accuracy is discussed; algorithms and simulated results are presented.
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Preprints, Working Papers, ...
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Contributor : Michel Broniatowski <>
Submitted on : Thursday, August 4, 2011 - 4:12:23 PM
Last modification on : Wednesday, March 21, 2018 - 6:56:47 PM
Long-term archiving on: : Saturday, November 5, 2011 - 2:21:06 AM


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  • HAL Id : hal-00613346, version 1


Michel Broniatowski, Virgile Caron. Towards zero variance estimators for rare event probabilities. 2011. ⟨hal-00613346v1⟩



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