JSM 2004 Online Program

Abstract #301460

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Activity Number:	147
Type:	Topic Contributed
Date/Time:	Monday, August 9, 2004 : 2:00 PM to 3:50 PM
Sponsor:	Section on Bayesian Statistical Science
Abstract - #301460
Title:	Noncentered Parameterizations for Hierarchical Models
Author(s):	Omiros Papaspiliopoulos*+
Companies:	Lancaster University
Address:	Fylde College, Lancaster, LA1 4YF, United Kingdom
Keywords:	parametrization ; hierarchical models ; Levy processes ; representations ; convergence rates
Abstract:	We give an overview of noncentered parametrizations for arbitrary three-stage hierarchical models. Such parametrizations are employed to improve the convergence of MCMC algorithms which are used for Bayesian inference. We argue, mathematically and intuitively, why such parametrizations are appealing in a wide range of applications, but particularly for models that involve high-dimensional latent stochastic processes. Such models are commonly used in econometrics, spatial statistics, and Bayesian nonparametrics.

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