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

Ankush Agarwal (1) , Stefano de Marco (1) , Emmanuel Gobet (1) , Gang Liu (1)

1 CMAP - Centre de Mathématiques Appliquées - Ecole Polytechnique

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.

Mots clés: Extreme scenario; rare event; Markov chains; ergodic properties; interacting particle systems

Domaines: Probabilités [math.PR]

Ankush Agarwal, Stefano de Marco, Emmanuel Gobet, Gang Liu. Study of new rare event simulation schemes and their application to extreme scenario generation. Mathematics and Computers in Simulation, 2018, 143, pp.89-98. ⟨10.1016/j.matcom.2017.05.004⟩. ⟨hal-01249625⟩