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On the Posterior Consistency of Mixtures of Dirichlet Process Priors with Censored Data
Author(s) -
Kim Yongdai
Publication year - 2003
Publication title -
scandinavian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.359
H-Index - 65
eISSN - 1467-9469
pISSN - 0303-6898
DOI - 10.1111/1467-9469.00347
Subject(s) - prior probability , dirichlet process , mathematics , dirichlet distribution , consistency (knowledge bases) , parametric statistics , concentration parameter , statistics , posterior probability , econometrics , generalized dirichlet distribution , nonparametric statistics , bayesian probability , mathematical analysis , dirichlet's principle , geometry , boundary value problem
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.