Nieto-Barajas, Luis E., Walker, Stephen G. (2002) Markov beta and gamma processes for modelling hazard rates. Scandinavian Journal of Statistics, 29 (3). pp. 413-424. ISSN 0303-6898. (doi:10.1111/1467-9469.00298) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:10566)
| The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. | |
| Official URL: http://dx.doi.org/10.1111/1467-9469.00298 |
Abstract
This paper generalizes the discrete time independent increment beta process of Hjort (1990), for modelling discrete failure times, and also generalizes the independent gamma process for modelling piecewise constant hazard rates (Walker and Mallick, 1997). The generalizations are from independent increment to Markov increment prior processes allowing the modelling of smoothness. We derive posterior distributions and undertake a full Bayesian analysis.
| Item Type: | Article |
|---|---|
| DOI/Identification number: | 10.1111/1467-9469.00298 |
| Uncontrolled keywords: | Bayes non-parametrics; beta process; gamma process; Markov process; stationary process; survival analysis |
| Subjects: | Q Science > QA Mathematics (inc Computing science) |
| Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science |
| Depositing User: | Judith Broom |
| Date Deposited: | 21 Oct 2008 16:36 UTC |
| Last Modified: | 05 Nov 2024 09:43 UTC |
| Resource URI: | https://kar.kent.ac.uk/id/eprint/10566 (The current URI for this page, for reference purposes) |
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