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.

• Type: Conference
• Year: 2007
• Where: WSC
• Authors: Xiaowei Zhang, Jose Blanchet, Peter W. Glynn
• Keywords: Conditional Monte Carlo, Crude Monte Carlo, Modeling And Simulation, Monte Carlo, WSC 2007