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Rare-Event Simulation

In: Handbook of Uncertainty Quantification

Author

Listed:
  • 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)

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.

Suggested Citation

  • James L. Beck & Konstantin M. Zuev, 2017. "Rare-Event Simulation," Springer Books, in: Roger Ghanem & David Higdon & Houman Owhadi (ed.), Handbook of Uncertainty Quantification, chapter 30, pages 1075-1100, Springer.
    • Handle: RePEc:spr:sprchp:978-3-319-12385-1_24
    DOI: 10.1007/978-3-319-12385-1_24
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