Bayesian analysis of multistate event history data: beta-Dirichlet process prior

Yongdai Kim, Lancelot James and Rafael Weissbach

Biometrika, 2012, vol. 99, issue 1, pages 127-140

Abstract: Bayesian analysis of a finite state Markov process, which is popularly used to model multistate event history data, is considered. A new prior process, called a beta-Dirichlet process, is introduced for the cumulative intensity functions and is proved to be conjugate. In addition, the beta-Dirichlet prior is applied to a Bayesian semiparametric regression model. To illustrate the application of the proposed model, we analyse a dataset of credit histories. Copyright 2012, Oxford University Press.

Date: 2012
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