Blanchet, J., & Lam, H. (2011). State-dependent importance sampling for rare-event simulation: An overview and recent advances. Surveys in Operations Research and Management Science, 17(1), 38-59. https://doi.org/10.1016/j.sorms.2011.09.002

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Abstract

This paper surveys recent techniques that have been developed for rare-event analysis of stochastic systems via simulation. We review standard (state-independent) techniques that take advantage of large deviations results for the design of efficient importance sampling estimators. Classical examples and counter-examples are discussed to illustrate the reach and limitations of the state-independent approach. Then we move to state-dependent techniques. These techniques can be applied to both light and heavy-tailed systems and are based on subsolutions (see e.g. Dupuis and Wang (2004) [5], Dupuis and Wang (2007) [6], Dupuis and Wang (2009) [80], Dupuis et al. (2007) [7]) and Lyapunov bounds (Blanchet and Glynn (2008) [9], Blanchet et al. (2007) [11], Blanchet (2009) [12]). We briefly review the ideas behind these techniques, and provide several examples in which they are applicable.

Authors: Jose Blanchet, Henry Lam
Publication date: 2012/1/1
Source: Surveys in Operations Research and Management Science
Volume: 17
Issue: 1
Pages: 38-59
Publisher: Elsevier