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Gibbs Reference Prior for Robust Gaussian Process Emulation

21 March 2017
Joseph Muré
ArXiv (abs)PDFHTML
Abstract

We propose an objective prior distribution on correlation kernel parameters for Simple Kriging models in the spirit of reference priors. Because it is proper and defined through its conditional densities, it and its associated posterior distribution lend themselves well to Gibbs sampling, thus making the full-Bayesian procedure tractable. Numerical examples show it has near-optimal frequentist performance in terms of prediction interval coverage

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