Rare-Event Simulation

James L. Beck () and Konstantin M. Zuev ()
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James L. Beck: California Institute of Technology, Department of Computing and Mathematical Sciences
Konstantin M. Zuev: California Institute of Technology, Department of Computing and Mathematical Sciences

Chapter 30 in Handbook of Uncertainty Quantification, 2017, pp 1075-1100 from Springer

Abstract: Abstract Rare events are events that are expected to occur infrequently or, more technically, those that have low probabilities (say, order of 10−3 or less) of occurring according to a probability model. In the context of uncertainty quantification, the rare events often correspond to failure of systems designed for high reliability, meaning that the system performance fails to meet some design or operation specifications. As reviewed in this section, computation of such rare-event probabilities is challenging. Analytical solutions are usually not available for nontrivial problems, and standard Monte Carlo simulation is computationally inefficient. Therefore, much research effort has focused on developing advanced stochastic simulation methods that are more efficient. In this section, we address the problem of estimating rare-event probabilities by Monte Carlo simulation, importance sampling, and subset simulation for highly reliable dynamic systems.

Keywords: Rare-event simulation; Dynamic system reliability; Monte carlo simulation; Subset simulation; Importance sampling; Splitting (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-12385-1_24

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DOI: 10.1007/978-3-319-12385-1_24

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