Efficient suboptimal rare-event simulation

Authors:
Xiaowei Zhang;Jose Blanchet;Peter W. Glynn
Affiliations:
Stanford University, Stanford, C.A.;Harvard University, Cambridge, M.A.;Stanford University, Stanford, C.A.
Venue:
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Year:
2007

Citing 4
Cited 2

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Abstract

Much of the rare-event simulation literature is concerned with the development of asymptotically optimal algorithms. Because of the difficulties associated with applying these ideas to complex models, this paper focuses on sub-optimal procedures that can be shown to be much more efficient than conventional crude Monte Carlo. We provide two such examples, one based on "repeated acceptance/rejection" as a mean of computing tail probabilities for hitting time random variables and the other based on filtered conditional Monte Carlo.