Efficient importance sampling for Monte Carlo evaluation of exceedance probabilities

DOI10.1214/105051606000000664zbMath1134.65005arXivmath/0703910OpenAlexW3098708189MaRDI QIDQ2455052

Hock Peng Chan, Tze Leung Lai

Publication date: 22 October 2007

Published in: The Annals of Applied Probability (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/math/0703910

zbMATH Keywords

importance samplingnumerical examplesrare eventslarge deviationstail probabilitiesregenerationMarkov additive processboundary crossing probabilityMarkov random walkMonte Carlo evaluationasymptotically optimal importance sampling measureMarkov setting

Mathematics Subject Classification ID

Computational methods in Markov chains (60J22) Monte Carlo methods (65C05) Sums of independent random variables; random walks (60G50) Discrete-time Markov processes on general state spaces (60J05) Numerical analysis or methods applied to Markov chains (65C40) Large deviations (60F10)

Related Items (7)

Random recurrence equations and ruin in a Markov-dependent stochastic economic environment ⋮ On an automatic and optimal importance sampling approach with applications in finance ⋮ The sample size required in importance sampling ⋮ A sequential Monte Carlo approach to computing tail probabilities in stochastic models ⋮ Discussion on “Sequential detection/isolation of abrupt changes” by Igor V. Nikiforov ⋮ Discussion on “Is Average Run Length to False Alarm Always an Informative Criterion?” by Yajun Mei ⋮ A Cross-Entropy Scheme for Mixtures

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