On a new class of score functions to estimate tail probabilities of some stochastic processes with Adaptive Multilevel Splitting

Abstract : We investigate the application of the Adaptive Multilevel Splitting algorithm for the estimation of tail probabilities of solutions of Stochastic Differential Equations evaluated at a given time, and of associated temporal averages. We introduce a new, very general and effective family of score functions which is designed for these problems. We illustrate its behavior on a series of numerical experiments. In particular, we demonstrate how it can be used to estimate large deviation rate functionals for the longtime limit of temporal averages.
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Chaos, American Institute of Physics, 2019, 〈10.1063/1.5081440〉
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https://hal.archives-ouvertes.fr/hal-01923385
Contributeur : Charles-Edouard Bréhier <>
Soumis le : jeudi 15 novembre 2018 - 11:22:39
Dernière modification le : mardi 19 mars 2019 - 21:09:57
Document(s) archivé(s) le : samedi 16 février 2019 - 13:34:00

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Charles-Edouard Bréhier, Tony Lelièvre. On a new class of score functions to estimate tail probabilities of some stochastic processes with Adaptive Multilevel Splitting. Chaos, American Institute of Physics, 2019, 〈10.1063/1.5081440〉. 〈hal-01923385〉

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