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August 2008 Bayesian nonparametric estimators derived from conditional Gibbs structures
Antonio Lijoi, Igor Prünster, Stephen G. Walker
Ann. Appl. Probab. 18(4): 1519-1547 (August 2008). DOI: 10.1214/07-AAP495

Abstract

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.

Citation

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Antonio Lijoi. Igor Prünster. Stephen G. Walker. "Bayesian nonparametric estimators derived from conditional Gibbs structures." Ann. Appl. Probab. 18 (4) 1519 - 1547, August 2008. https://doi.org/10.1214/07-AAP495

Information

Published: August 2008
First available in Project Euclid: 21 July 2008

zbMATH: 1142.62333
MathSciNet: MR2434179
Digital Object Identifier: 10.1214/07-AAP495

Subjects:
Primary: 60G57, 62F15, 62G05

Rights: Copyright © 2008 Institute of Mathematical Statistics

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Vol.18 • No. 4 • August 2008
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