A Bayesian semi-parametric bivariate failure time model

Nieto-Barajas, Luis E. and Walker, Stephen G. (2007) A Bayesian semi-parametric bivariate failure time model. Computational Statistics and Data Analysis, 51 (12). pp. 6102-6113. ISSN 0167-9473 . (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)

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Official URL
http://dx.doi.org/10.1016/j.csda.2006.12.020

Abstract

In this paper we introduce a Bayesian semiparametric model for bivariate and multivariate survival data. The marginal densities are well-known nonparametric survival models and the joint density is constructed via a mixture. Our construction also defines a copula and the properties of this new copula are studied. We also consider the model in the presence of covariates and, in particular, we find a simple generalisation of the widely used frailty model, which is based on a new bivariate gamma distribution.

Item Type: Article
Uncontrolled keywords: Bayes nonparametrics; bivariate survival analysis; copula; correlated frailty model; discrete Markov gamma process; latent variables; mixture representation
Subjects: Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics
Q Science > QA Mathematics (inc Computing science) > QA273 Probabilities
Q Science > QA Mathematics (inc Computing science) > QA 75 Electronic computers. Computer science
Divisions: Faculties > Science Technology and Medical Studies > School of Mathematics Statistics and Actuarial Science > Statistics
Depositing User: Suzanne Duffy
Date Deposited: 21 Apr 2008 08:12
Last Modified: 25 Jun 2014 10:42
Resource URI: https://kar.kent.ac.uk/id/eprint/2662 (The current URI for this page, for reference purposes)
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