On the Posterior Consistency of Mixtures of Dirichlet Process Priors with Censored Data
Yongdai Kim · Scandinavian Journal of Statistics · 2003
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.