Robust Gaussian stochastic process emulation
Abstract
We consider estimation of the parameters of a Gaussian Stochastic Process (GaSP), in the context of emulation (approximation) of computer models for which the outcomes are real-valued scalars. The main focus is on estimation of the GaSP parameters through various generalized maximum likelihood methods, mostly involving finding posterior modes; this is because full Bayesian analysis in computer model emulation is typically prohibitively...
Paper Details
Title
Robust Gaussian stochastic process emulation
Published Date
Dec 1, 2018
Journal
Volume
46
Issue
6A
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