Xiaowei Zhang, J. Blanchet and P. W. Glynn, “Efficient suboptimal rare-event simulation,” 2007 Winter Simulation Conference, Washington, DC, 2007, pp. 389-394, doi: 10.1109/WSC.2007.4419627.
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.
Authors
Xiaowei Zhang, Jose Blanchet, Peter W Glynn
Publication date
2007/12/9
Conference
2007 Winter Simulation Conference
Pages
389-394
Publisher
IEEE
