Efficient suboptimal rare-event simulation

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Efficient suboptimal rare-event simulation
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.
Xiaowei Zhang, Jose Blanchet, Peter W. Glynn
Added 02 Oct 2010
Updated 02 Oct 2010
Type Conference
Year 2007
Where WSC
Authors Xiaowei Zhang, Jose Blanchet, Peter W. Glynn
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