RARE-EVENT SIMULATION OF HEAVY-TAILED RANDOM WALKS BY SEQUENTIAL IMPORTANCE SAMPLING AND RESAMPLING

作者：Chan Hock Peng^*; Deng Shaojie; Lai Tze Leung

来源：Advances in Applied Probability, 2012, 44(4): 1173-1196.

• Efficient simulation
• heavy-tailed distribution
• sequential Monte Carlo
• regularly varying tail

We introduce a new approach to simulating rare events for Markov random walks with heavy-tailed increments. This approach involves sequential importance sampling and resampling, and uses a martingale representation of the corresponding estimate of the rare-event probability to show that it is unbiased and to bound its variance. By choosing the importance measures and resampling weights suitably, it is shown how this approach can yield asymptotically efficient Monte Carlo estimates.

• 出版日期2012-12
• 单位Microsoft