Discrete random probability measures: a general framework for nonparametric Bayesian inference

Andrea Ongaro and Carla Cattaneo

Statistics & Probability Letters, 2004, vol. 67, issue 1, 33-45

Abstract: A unifying framework for Bayesian analysis in discrete nonparametric settings is proposed. To this aim, a general class of nonparametric discrete prior distributions on an arbitrary sample space is introduced. The general structure of the posterior and predictive distributions and an explicit updating mechanism for the posterior are developed.

Keywords: Nonparametric; priors; Generalized; Dirichlet; process; Mixture; representation; Random; weights (search for similar items in EconPapers)
Date: 2004
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Citations: View citations in EconPapers (4)

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