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Semi‐ and Non‐parametric Bayesian Analysis of Duration Models with Dirichlet Priors: A Survey
Author(s) -
Florens J.P.,
Mouchart M.,
Rolin J.M.
Publication year - 1999
Publication title -
international statistical review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.051
H-Index - 54
eISSN - 1751-5823
pISSN - 0306-7734
DOI - 10.1111/j.1751-5823.1999.tb00426.x
Subject(s) - prior probability , dirichlet distribution , statistics , bayesian probability , mathematics , dirichlet process , parametric statistics , duration (music) , econometrics , computer science , physics , mathematical analysis , acoustics , boundary value problem
Summary 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.