Empirical Bayes Estimation of a Distribution Function
Korwar, Ramesh M. ; Hollander, Myles
Ann. Statist., Tome 4 (1976) no. 1, p. 581-588 / Harvested from Project Euclid
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A sequence of empirical Bayes estimators is defined for estimating a distribution function. The sequence is shown to be asymptotically optimal relative to a Ferguson Dirichlet process prior. Exact risk expressions are derived and the rate, at which the overall expected loss approaches the minimum Bayes risk, is exhibited. The empirical Bayes approach, based on the Dirichlet process, is also applied to the problem of estimating the mean of a distribution.
Publié le : 1976-05-14
Classification:  Distribution function,  empirical Bayes estimator,  Dirichlet process,  62G05,  62C99 
@article{1176343463,
     author = {Korwar, Ramesh M. and Hollander, Myles},
     title = {Empirical Bayes Estimation of a Distribution Function},
     journal = {Ann. Statist.},
     volume = {4},
     number = {1},
     year = {1976},
     pages = { 581-588},
     language = {en},
     url = {http://dml.mathdoc.fr/item/1176343463}
}

Korwar, Ramesh M.; Hollander, Myles. Empirical Bayes Estimation of a Distribution Function. Ann. Statist., Tome 4 (1976) no. 1, pp.  581-588. http://gdmltest.u-ga.fr/item/1176343463/