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.

[1]  Linus Schrage,et al.  A guide to simulation , 1983 .

[2]  Stefano Giordano,et al.  Rare event simulation , 2002, Eur. Trans. Telecommun..

[3]  Paul Glasserman,et al.  Conditioning on One-Step Survival for Barrier Option Simulations , 2001, Oper. Res..

[4]  Agnès Lagnoux,et al.  RARE EVENT SIMULATION , 2005, Probability in the Engineering and Informational Sciences.

[5]  Paul Glasserman,et al.  Filtered Monte Carlo , 1993, Math. Oper. Res..

[6]  Paul Bratley,et al.  A guide to simulation , 1983 .

[7]  P. Glynn,et al.  Efficient rare-event simulation for the maximum of heavy-tailed random walks , 2008, 0808.2731.

[8]  S. Juneja,et al.  Rare-event Simulation Techniques : An Introduction and Recent Advances , 2006 .

[9]  Ward Whitt,et al.  The Asymptotic Efficiency of Simulation Estimators , 1992, Oper. Res..

[10]  Peter W. Glynn,et al.  Fluid heuristics, Lyapunov bounds and efficient importance sampling for a heavy-tailed G/G/1 queue , 2007, Queueing Syst. Theory Appl..

[11]  Marie Manthey,et al.  A GUIDE FOR , 1967 .

[12]  Paul Bratley,et al.  A guide to simulation (2nd ed.) , 1986 .

[13]  Upendra Dave,et al.  Applied Probability and Queues , 1987 .

[14]  P. Shahabuddin,et al.  Chapter 11 Rare-Event Simulation Techniques: An Introduction and Recent Advances , 2006, Simulation.

[15]  Gerardo Rubino,et al.  Introduction to Rare Event Simulation , 2009, Rare Event Simulation using Monte Carlo Methods.