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Abstract Details

Activity Number: 53
Type: Invited
Date/Time: Sunday, July 29, 2012 : 4:00 PM to 5:50 PM
Sponsor: General Methodology
Abstract - #303880
Title: Flexible Regression Modeling and Inference via Dependent Polya Trees
Author(s): Wesley Johnson*+ and Alejandro Jara and Fernando Andrés Quintana
Companies: University of California at Irvine and Pontificia Universidad Católica de Chile and Pontificia Universidad Católica de Chile
Address: Department of Statistics, Irvine, CA, 92697,
Keywords: Bayesian Nonparametric ; Regression ; Polya Tree

We obtain a joint model for a collection of probability distributions for data that are indexed by covariates. We allow for (i) differences in distributional characteristics across predictor combinations and (ii) dependence among distributions that correspond to similar predictors. The method is analogous to MacEachern's (1999) development the Dependent Dirichlet Process (DDP). We compare various methods using real and simulated data.

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