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Study of new rare event simulation schemes and their application to extreme scenario generation

Abstract : This is a companion paper based on our previous work [ADGL15] on rare event simulation methods. In this paper, we provide an alternative proof for the ergodicity of shaking transformation in the Gaussian case and propose two variants of the existing methods with comparisons of numerical performance. In numerical tests, we also illustrate the idea of extreme scenario generation based on the convergence of marginal distributions of the underlying Markov chains and show the impact of the discretization of continuous time models on rare event probability estimation.
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https://hal-polytechnique.archives-ouvertes.fr/hal-01249625
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Submitted on : Saturday, January 2, 2016 - 11:03:27 AM
Last modification on : Thursday, March 5, 2020 - 6:31:31 PM

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Ankush Agarwal, Stefano de Marco, Emmanuel Gobet, Gang Liu. Study of new rare event simulation schemes and their application to extreme scenario generation. 2016. ⟨hal-01249625⟩

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