Abstract
In this article, we consider a Gaussian random field f (t) living on a compact set T ⊂ Rd and the computation of the tail probabilities P(∫ T e f (t)dt > eb) as b→∞. We design asymptotically efficient importance sampling estimators for a general class of Hölder continuous Gaussian random fields. In addition to the variance control, we also analyze the bias (relative to the interesting tail probabilities) caused by the discretization.
Original language | English (US) |
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Article number | 2567892 |
Journal | ACM Transactions on Modeling and Computer Simulation |
Volume | 24 |
Issue number | 2 |
DOIs | |
State | Published - Feb 2014 |
Keywords
- Exponential integral
- Gaussian random fields
- Importance sampling