J. H. Blanchet and Jingchen Liu, “Path-sampling for state-dependent importance sampling,” 2007 Winter Simulation Conference, Washington, DC, USA, 2007, pp. 380-388, doi: 10.1109/WSC.2007.4419626.
Abstract
State-dependent importance sampling (SDIS) has proved to be particularly useful in simulation (specially in rare event analysis of stochastic systems). One approach for designing SDIS is to mimic the zero-variance change-of-measure by using a likelihood ratio that is proportional to an asymptotic approximation that may be available for the problem at hand. Using such approximation poses the problem of computing the corresponding normalizing constants at each step. In this paper, we propose the use of path-sampling, which allows to estimate such normalizing constants in terms of one dimensional integrals. We apply path-sampling to estimate the tail of the delay in a G/G/1 queue with regularly varying input. We argue that such tail estimation can be performed with good relative precision in quadratic complexity (in terms of the tail parameter) - assuming that path-sampling is combined with an appropriate …
Authors
Jose H Blanchet, Jingchen Liu
Publication date
2007/12/9
Conference
2007 Winter Simulation Conference
Pages
380-388
Publisher
IEEE
