The consistency of posterior distributions in nonparametric problems
Barron, Andrew ; Schervish, Mark J. ; Wasserman, Larry
Ann. Statist., Tome 27 (1999) no. 4, p. 536-561 / Harvested from Project Euclid
We give conditions that guarantee that the posterior probability of every Hellinger neighborhood of the true distribution tends to 1 almost surely. The conditions are (1) a requirement that the prior not put high mass near distributions with very rough densities and (2) a requirement that the prior put positive mass in Kullback-Leibler neighborhoods of the true distribution. The results are based on the idea of approximating the set of distributions with a finite-dimensional set of distributions with sufficiently small Hellinger bracketing metric entropy. We apply the results to some examples.
Publié le : 1999-04-14
Classification:  Exponential families,  Hellinger distance,  nonparametric Bayesian inference,  Pólya trees.,  62G20
@article{1018031206,
     author = {Barron, Andrew and Schervish, Mark J. and Wasserman, Larry},
     title = {The consistency of posterior distributions in nonparametric
			 problems},
     journal = {Ann. Statist.},
     volume = {27},
     number = {4},
     year = {1999},
     pages = { 536-561},
     language = {en},
     url = {http://dml.mathdoc.fr/item/1018031206}
}
Barron, Andrew; Schervish, Mark J.; Wasserman, Larry. The consistency of posterior distributions in nonparametric
			 problems. Ann. Statist., Tome 27 (1999) no. 4, pp.  536-561. http://gdmltest.u-ga.fr/item/1018031206/