Some Recent Results in Rare Event Estimation
ESAIM. Proceedings, Tome 44 (2014), pp. 239-259.

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This article presents several state-of-the-art Monte Carlo methods for simulating and estimating rare events. A rare event occurs with a very small probability, but its occurrence is important enough to justify an accurate study. Rare event simulation calls for specific techniques to speed up standard Monte Carlo sampling, which requires unacceptably large sample sizes to observe the event a sufficient number of times. Among these variance reduction methods, the most prominent ones are Importance Sampling (IS) and Multilevel Splitting, also known as Subset Simulation. This paper offers some recent results on both aspects, motivated by theoretical issues as well as by applied problems.
DOI : 10.1051/proc/201444015

Virgile Caron 1 ; Arnaud Guyader 2 ; Miguel Munoz Zuniga 3 ; Bruno Tuffin 4

1 LSTA, UPMC-Paris VI, France;
2 Université Rennes 2, IRMAR, Inria Rennes, Campus de Villejean, 35043 Rennes Cedex, France;
3 Institut de Radioprotection et de Sreté Nucléaire, Fontenay-aux-roses, France;
4 Inria Rennes, Campus Universitaire de Beaulieu, 35042 Rennes Cedex, France;
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Virgile Caron; Arnaud Guyader; Miguel Munoz Zuniga; Bruno Tuffin. Some Recent Results in Rare Event Estimation. ESAIM. Proceedings, Tome 44 (2014), pp. 239-259. doi : 10.1051/proc/201444015. http://geodesic.mathdoc.fr/articles/10.1051/proc/201444015/

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