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.
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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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