JSM 2003 Online Program

Abstract #301109

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Activity Number:	199
Type:	Topic Contributed
Date/Time:	Tuesday, August 5, 2003 : 8:30 AM to 10:20 AM
Sponsor:	Section on Bayesian Stat. Sciences
Abstract - #301109
Title:	Bayesian Nonparametric Survival Analysis via Markov Processes
Author(s):	Luis E. Nieto-Barajas*+
Companies:	ITAM
Address:	Rio Hondo No. 1, Mexico, D.F., 01000, Mexico
Keywords:	survival analysis ; Bayes nonparametrics ; Levy processes ; Markov processes
Abstract:	In a Bayesian nonparametric context, the hazard function is modeled by a stochastic process, allowing the model to have great flexibility to cope with a larger range of possible behaviors of the true hazard function. We follow a Bayesian nonparametric approach and propose new prior distributions for the hazard function in univariate and bivariate cases. These priors are based on Markov processes in discrete and continuous time. Posterior distributions are obtained, and algorithms for their simulation are also shown. These models are illustrated with a full Bayesian analysis.

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