JSM 2003 Online Program

Abstract #300831

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Activity Number:	469
Type:	Contributed
Date/Time:	Thursday, August 7, 2003 : 10:30 AM to 12:20 PM
Sponsor:	IMS
Abstract - #300831
Title:	Nonparametric Bayesian Density Estimation with Autoregressive Priors
Author(s):	Suhwon Lee*+ and Paul L. Speckman and Dongchu Sun
Companies:	University of Missouri and University of Missouri, Columbia and University of Missouri, Columbia
Address:	222 Math Science Building, Columbia, MO, 65211-4100,
Keywords:	nonparametric density estimation ; Bayes ; intrinsic autoregressive process
Abstract:	A simple model for Bayesian density estimation is introduced. Data are first binned, and a hierarchical model is used on the log of the bin probabilities. Good results are obtained using second- and third-order intrinsic autoregression priors for the transformed bin probabilities. Bayesian computations are implemented with Gibbs sampling and adaptive rejection sampling. Applications are shown for real and simulated data sets.

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