Simulation and estimation of extreme quantiles and extreme probabilities

Abstract : Let X be a random vector with distribution μ on ℝ^d and Φ be a mapping from ℝ^d d to ℝ. That mapping acts as a black box, e.g., the result from some computer experiments for which no analytical expression is available. This paper presents an efficient algorithm to estimate a tail probability given a quantile or a quantile given a tail probability. The algorithm improves upon existing multilevel splitting methods and can be analyzed using Poisson process tools that lead to exact description of the distribution of the estimated probabilities and quantiles. The performance of the algorithm is demonstrated in a problem related to digital watermarking.
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Article dans une revue
Applied Mathematics and Optimization, Springer Verlag (Germany), 2011, 64 (2), pp.171-196. 〈10.1007/s00245-011-9135-z〉
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https://hal.inria.fr/hal-00911891
Contributeur : Francois Le Gland <>
Soumis le : dimanche 1 décembre 2013 - 01:55:27
Dernière modification le : jeudi 11 janvier 2018 - 06:20:08

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Arnaud Guyader, Nicolas W. Hengartner, Eric Matzner-Løber. Simulation and estimation of extreme quantiles and extreme probabilities. Applied Mathematics and Optimization, Springer Verlag (Germany), 2011, 64 (2), pp.171-196. 〈10.1007/s00245-011-9135-z〉. 〈hal-00911891〉

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