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

Authors :
Agarwal, Ankush
De Marco, Stefano
Gobet, Emmanuel
Liu, Gang
Source :
Mathematics & Computers in Simulation. Jan2018, Vol. 143, p89-98. 10p.
Publication Year :
2018

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03784754
Volume :
143
Database :
Academic Search Index
Journal :
Mathematics & Computers in Simulation
Publication Type :
Periodical
Accession number :
125175971
Full Text :
https://doi.org/10.1016/j.matcom.2017.05.004