Title :
Uniformly efficient simulation for tail probabilities of Gaussian random fields
Author_Institution :
Sch. of Stat., Univ. of Minnesota, Minneapolis, MN, USA
Abstract :
In this paper, we consider rare-event simulation of the tail probabilities of Gaussian random fields. In particular, we design importance sampling estimators that are uniformly efficient for a family of Gaussian random fields with different mean and variance functions.
Keywords :
Gaussian processes; probability; simulation; Gaussian random fields; importance sampling estimators; mean functions; rare-event simulation; tail probabilities; uniformly efficient simulation; variance functions; Approximation methods; Computational modeling; Monte Carlo methods; Numerical models; Q measurement; Random variables;
Conference_Titel :
Simulation Conference (WSC), 2014 Winter
Conference_Location :
Savanah, GA
Print_ISBN :
978-1-4799-7484-9
DOI :
10.1109/WSC.2014.7019918
