JSM 2003 Online Program

Abstract #301466

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Activity Number:	199
Type:	Topic Contributed
Date/Time:	Tuesday, August 5, 2003 : 8:30 AM to 10:20 AM
Sponsor:	Section on Bayesian Stat. Sciences
Abstract - #301466
Title:	Default Spatial Priors for Gaussian Processes Having Separable Correlation Structure
Author(s):	Rui Paulo*+
Companies:	NISS
Address:	PO Box 14006, RTP, NC, 27709,
Keywords:	Gaussian process ; complex computer model ; default priors ; spatial statistics ; Bayesian analysis
Abstract:	Motivated by the statistical evaluation of complex computer models, we deal with the issue of objective prior specification for the parameters of Gaussian spatial processes. In particular, we derive the Jeffreys-rule, Jeffreys independence and reference priors for this situation, and prove that the resulting posterior distributions are proper under a quite general set of conditions. Another prior specification strategy, based on maximum likelihood estimates,is also considered, and all priors are then compared on the grounds of the frequentist properties of the ensuing Bayesian procedures.

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