Modelling heterogeneity with and without the Dirichlet process

PJ Green, S Richardson

Research output: Contribution to journalArticle (Academic Journal)peer-review

140 Citations (Scopus)

Abstract

We investigate the relationships between Dirichlet process (DP) based models and allocation models for a variable number of components, based on exchangeable distributions. It is shown that the DP partition distribution is a Limiting case of a Dirichlet-multinomial allocation model, Comparisons of posterior performance of DP and allocation models are made in the Bayesian paradigm and illustrated in the context of univariate mixture models, It is shown in particular that the unbalancedness of the allocation distribution, present in the prior DP model, persists aposteriori, Exploiting the model connections, a new MCMC sampler for general DP based models is introduced, which uses split/merge moves in a reversible jump framework. Performance of this new sampler relative to that of some traditional samplers for DP processes is teen explored.
Translated title of the contributionModelling heterogeneity with and without the Dirichlet process
Original languageEnglish
Pages (from-to)355 - 375
Number of pages21
JournalScandinavian Journal of Statistics
Volume28 (2)
DOIs
Publication statusPublished - Jun 2001

Bibliographical note

Publisher: Blackwell
Other identifier: IDS number 432KX

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