The Annals of Applied Probability

Bayesian nonparametric estimators derived from conditional Gibbs structures

Antonio Lijoi, Igor Prünster, and Stephen G. Walker

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We consider discrete nonparametric priors which induce Gibbs-type exchangeable random partitions and investigate their posterior behavior in detail. In particular, we deduce conditional distributions and the corresponding Bayesian nonparametric estimators, which can be readily exploited for predicting various features of additional samples. The results provide useful tools for genomic applications where prediction of future outcomes is required.

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Ann. Appl. Probab. Volume 18, Number 4 (2008), 1519-1547.

First available in Project Euclid: 21 July 2008

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Zentralblatt MATH identifier

Primary: 62G05: Estimation 62F15: Bayesian inference 60G57: Random measures

Bayesian nonparametrics Dirichlet process exchangeable random partitions generalized factorial coefficients generalized gamma process population genetics species sampling models two parameter Poisson–Dirichlet process


Lijoi, Antonio; Prünster, Igor; Walker, Stephen G. Bayesian nonparametric estimators derived from conditional Gibbs structures. Ann. Appl. Probab. 18 (2008), no. 4, 1519--1547. doi:10.1214/07-AAP495.

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