On the posterior consistency of mixtures of Dirichlet process priors with censored data

Abstract

Mixtures of Dirichlet process priors offer a reasonable compromise between purely parametric and purely non-parametric models, and are popularly used in survival analysis and for testing problems with non-parametric alternatives. In this paper, we study large sample properties of the posterior distribution with a mixture of Dirichlet process priors. We show that the posterior distribution of the survival function is consistent with right censored data.