Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Authors: Hani J. Doss, Balasubramanian Narasimhan
Title: Dynamic Display of Changing Posterior in Bayesian Survival Analysis: The Software
Abstract: We consider the problem of estimating an unknown distribution function in the presence of censoring under the conditions that a parametric model is believed to hold approximately. We use a Bayesian approach, in which the prior on is a mixture of Dirichlet distributions. A hyperparameter of the prior determines the extent to which this prior concentrates its mass around the parametric family. A Gibbs sampling algorithm to estimate the posterior distributions of the parameters of interest is reviewed. An importance sampling scheme enables us to use the output of the Gibbs sampler to very quickly recalculate the posterior when we change the hyperparameters of the prior. The calculations can be done sufficiently fast to enable the dynamic display of the changing posterior as the prior hyperparameters are varied.

This paper provides a literate program completely documenting the code for performing the dynamic graphics.

Page views:: 5263. Submitted: 1998-07-02. Published: 1999-07-12.
Paper: Dynamic Display of Changing Posterior in Bayesian Survival Analysis: The Software     Download PDF (Downloads: 4719)
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DOI: 10.18637/jss.v004.i03

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.