Bayesian nonparametric estimators derived from conditional Gibbs structures

Details Bayesian nonparametric estimators derived from conditional Gibbs structures Bayesian nonparametric estimators derived from conditional Gibbs structures

2008-08-21

arxiv.org/abs/0808.2863v1

Annals of Applied Probability 2008, Vol. 18, No. 4, 1519-1547

Mathematics

Probability

Published in at http://dx.doi.org/10.1214/07-AAP495 the Annals of Applied Probability (http://www.imstat.org/aap/) by the Inst

Scientific paper

10.1214/07-AAP495

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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