R. J. Adler, J. Blanchet and J. Liu, “Efficient simulation for tail probabilities of Gaussian random fields,” 2008 Winter Simulation Conference, Miami, FL, USA, 2008, pp. 328-336, doi: 10.1109/WSC.2008.4736085.
Abstract
We are interested in computing tail probabilities for the maxima of Gaussian random fields. In this paper, we discuss two special cases: random fields defined over a finite number of distinct point and fields with finite Karhunen-Loeve expansions. For the first case we propose an importance sampling estimator which yields asymptotically zero relative error. Moreover, it yields a procedure for sampling the field conditional on it having an excursion above a high level with a complexity that is uniformly bounded as the level increases. In the second case we propose an estimator which is asymptotically optimal. These results serve as a first step analysis of rare-event simulation for Gaussian random fields.
Authors
Robert J Adler, Jose Blanchet, Jingchen Liu
Publication date
2008/12/7
Conference
2008 Winter Simulation Conference
Pages
328-336
Publisher
IEEE
