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.
Publié le : 2008-08-15
Classification:
Bayesian nonparametrics,
Dirichlet process,
exchangeable random partitions,
generalized factorial coefficients,
generalized gamma process,
population genetics,
species sampling models,
two parameter Poisson–Dirichlet process,
62G05,
62F15,
60G57
@article{1216677130,
author = {Lijoi, Antonio and Pr\"unster, Igor and Walker, Stephen G.},
title = {Bayesian nonparametric estimators derived from conditional Gibbs structures},
journal = {Ann. Appl. Probab.},
volume = {18},
number = {1},
year = {2008},
pages = { 1519-1547},
language = {en},
url = {http://dml.mathdoc.fr/item/1216677130}
}
Lijoi, Antonio; Prünster, Igor; Walker, Stephen G. Bayesian nonparametric estimators derived from conditional Gibbs structures. Ann. Appl. Probab., Tome 18 (2008) no. 1, pp. 1519-1547. http://gdmltest.u-ga.fr/item/1216677130/