JSM 2004 Online Program

Abstract #300198

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Activity Number:	208
Type:	Invited
Date/Time:	Tuesday, August 10, 2004 : 10:30 AM to 12:20 PM
Sponsor:	ENAR
Abstract - #300198
Title:	Model Approximation in Complex Bayesian Analyses
Author(s):	L. Mark Berliner*+ and Christopher K. Wikle
Companies:	Ohio State University and University of Missouri, Columbia
Address:	1958 Neil Ave., Columbus, OH, 43210,
Keywords:	environmental statistics ; hierarchical modeling ; Markov chain Monte Carlo ; physical-statistical modeling
Abstract:	While the development of modern MCMC techniques enable Bayesian analyses using realistic, hierarchical models in complex problems, some compromises in specifications of models are often necessary. The types of compromises made vary widely depending on the problem. The assessment of the impacts of model approximation is difficult, but important. Some basic notions of these issues are discussed and illustrated in selected environmental problems involving real data.

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