Plug-in estimation of d-dimensional density minimum volume set of a rare event in a complex system

Jérôme Morio 1 Rudy Pastel 2, 1
2 ASPI - Applications of interacting particle systems to statistics
Inria Rennes – Bretagne Atlantique , IRMAR - Institut de Recherche Mathématique de Rennes
Abstract : Various reliability or hedging problems boil down to quantile estimation. However, real-life systems are usually multidimensional and thus often imply multidimensional density minimum volume set estimation which is usually done with Monte Carlo simulations. Increasing safety standards create a need for density minimum volume set estimation with low probability that crude Monte Carlo cannot fulfil. This paper proposes a new importance sampling algorithm that estimates efficiently multidimensional density minimum volume sets for extreme probability. It also presents some numerical results on a simple bidimensional Gaussian case and on a realistic launcher impact safety zone estimation.
Type de document :
Article dans une revue
Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, SAGE Publications, 2012, 226 (3), pp.337-345. 〈10.1177/1748006X11426973〉
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https://hal.inria.fr/hal-00911790
Contributeur : Francois Le Gland <>
Soumis le : vendredi 29 novembre 2013 - 20:02:55
Dernière modification le : mardi 19 juin 2018 - 11:12:07

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Jérôme Morio, Rudy Pastel. Plug-in estimation of d-dimensional density minimum volume set of a rare event in a complex system. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, SAGE Publications, 2012, 226 (3), pp.337-345. 〈10.1177/1748006X11426973〉. 〈hal-00911790〉

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