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Activity Number: 236
Type: Topic Contributed
Date/Time: Tuesday, August 8, 2006 : 8:30 AM to 10:20 AM
Sponsor: Section on Bayesian Statistical Science
Abstract - #307019
Title: Bayesian Model for Dependent Nonparametric Regressions
Author(s): Abel Rodriguez*+ and Alan E. Gelfand and David B. Dunson
Companies: Duke University and Duke University and National Institute of Environmental Health Sciences
Address: ISDS Box 90251, Durham, NC, 27708,
Keywords: Dirichlet process ; non-parametric regression ; dependent Dirichlet processes ; metaanalysis
Abstract:

We explore Bayesian models incorporating dependent generalizations of the Dirichlet process (DP) that allow borrowing of information among multiple nonparametric regressions. We first consider models in which different curves are assumed to be exchangeable using a hierarchical DP. Then, we generalize the model to describe spatially correlated functions using spatially dependent DPs. Applications to the analysis of multicenter studies and the estimation of temperature profiles in the ocean are presented.

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