Propriety of the reference posterior distribution in Gaussian process modeling
The Annals of Statistics · 2021 · Volume 49 · Issue 4
Abstract
In a seminal article, Berger, De Oliveira and Sansó [J. Amer. Statist. Assoc. 96 (2001) 1361–1374] compare several objective prior distributions for the parameters of Gaussian process models with isotropic correlation kernel. The reference prior distribution stands out among them insofar as it always leads to a proper posterior. They prove this result for rough correlation kernels: Spherical, Exponential with power ρ<2, Matérn with smoothness ν<1. This paper provides a proof for smooth correlation kernels: Exponential with power ρ=2, Matérn with smoothness ν≥1, Rational Quadratic, along with tail rates of the reference prior for these kernels.
Keywords
60G15, 62F15, 62M30, correlation function, Gaussian process, integrated likelihood, Jeffreys prior, kriging, posterior propriety, reference prior
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