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Semi- and Non-parametric Bayesian Analysis of Duration Models with Dirichlet Priors: A Survey
Authors:J-P Florens  M Mouchart  J-M Rolin
Institution:GREMAQ and IDEI, Universitédes Sciences Sociales, Toulouse, France.;CORE and Institut de Statistique, Universitécatholique de Louvain, Louvain-la-Neuve, Belgium
Abstract:The object of this paper is to review the main results obtained in semi- and non-parametric Bayesian analysis of duration models. Standard nonparametric Bayesian models for independent and identically distributed observations are reviewed in line with Ferguson's pioneering papers. Recent results on the characterization of Dirichlet processes and on nonparametric treatment of censoring and of heterogeneity in the context of mixtures of Dirichlet processes are also discussed. The final section considers a Bayesian semiparametric version of the proportional hazards model.
Keywords:Nonparametric Bayesian statistics  Dirichlet measures  Neutral to the right processes  Beta processes  Duration data  Censored observations  Heterogeneity  Proportional hazards model
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