Lower bounds for posterior rates with Gaussian process priors

Abstract

Upper bounds for rates of convergence of posterior distributions associated to Gaussian process priors are obtained by van der Vaart and van Zanten in [14] and expressed in terms of a concentration function involving the Reproducing Kernel Hilbert Space of the Gaussian prior. Here lower-bound counterparts are obtained. As a corollary, we obtain the precise rate of convergence of posteriors for Gaussian priors in various settings. Additionally, we extend theupper-bound results of [14] about Riemann-Liouville priors to a continuous family of parameters. © 2008, Institute of Mathematical Statistics. All rights reserved.