Bayesian nonparametric survival analysis via Levy driven Markov processes

Nieto-Barajas, L.E. and Walker, S.G. (2004) Bayesian nonparametric survival analysis via Levy driven Markov processes. Statistica Sinica, 14 (4). pp. 1127-1146. ISSN 1017-0405. (The full text of this publication is not available from this repository)

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Abstract

In this paper we present and investigate a new class of non-parametric priors for modelling a cumulative distribution function. We take F(t) = 1 - exp{-Z(t)}; where Z(t) = integral(t)/(0) x(s) ds is continuous and x((.)) is a Markov process. This is in contrast to the widely used class of neutral to the right priors (Doksum (1974)) for which Z(.) is discrete and has independent increments. The Markov process allows the modelling of trends in Z(.), not possible with independent increments. We derive posterior distributions and present a, full Bayesian analysis.

Item Type: Article
Uncontrolled keywords: Bayes nonparametrics; consistency; Levy process; gamma process; Markov process; stationary process; Levy driven Markov process
Subjects: Q Science > QA Mathematics (inc Computing science)
Divisions: Faculties > Science Technology and Medical Studies > School of Mathematics Statistics and Actuarial Science > Statistics
Depositing User: Judith Broom
Date Deposited: 26 Sep 2008 15:01
Last Modified: 14 Jan 2010 14:40
Resource URI: http://kar.kent.ac.uk/id/eprint/10538 (The current URI for this page, for reference purposes)
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