Abstract
AbstractFor rare events described in terms of Markov processes, truly unbiased estimation of the rare event probability generally requires the avoidance of numerical approximations of the Markov process. Recent work in the exact and $$\varepsilon$$
ε
-strong simulation of diffusions, which can be used to almost surely constrain sample paths to a given tolerance, suggests one way to do this. We specify how such algorithms can be combined with the classical multilevel splitting method for rare event simulation. This provides unbiased estimations of the probability in question. We discuss the practical feasibility of the algorithm with reference to existing $$\varepsilon$$
ε
-strong methods and provide proof-of-concept numerical examples.
Funder
Engineering and Physical Sciences Research Council
Alan Turing Institute
Publisher
Springer Science and Business Media LLC
Subject
General Mathematics,Statistics and Probability
Cited by
2 articles.
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