Lower bounds for posterior rates with Gaussian process priors

被引:48
作者
Castillo, Ismael [1 ]
机构
[1] Vrije Univ Amsterdam, Dept Math, NL-1081 HV Amsterdam, Netherlands
关键词
Bayesian nonparametrics; Gaussian process priors; Lower bounds;
D O I
10.1214/08-EJS273
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
Upper bounds for rates of convergence of posterior distributions associated to Gaussian process priors are obtained by van der Vaart and van Zanten in [11] 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 the upper-bound results of [11] about Riemann-Liouville priors to a continuous family of parameters.
引用
收藏
页码:1281 / 1299
页数:19
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