Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5127986 | Mathematics and Computers in Simulation | 2018 | 10 Pages |
Abstract
This is a companion paper based on our previous work 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.
Related Topics
Physical Sciences and Engineering
Engineering
Control and Systems Engineering
Authors
Ankush Agarwal, Stefano De Marco, Emmanuel Gobet, Gang Liu,