Empirical Bayes procedures are commonly used based on the supposed asymptotic equivalence with fully Bayesian procedures, which, however, has not so far received full theoretical support in terms of uncertainty quantification. In this note, we provide some results on contraction rates of empirical Bayes posterior distributions which are illustrated in nonparametric curve estimation using Dirichlet process mixture models.

On convergence rates of empirical Bayes procedures

Scricciolo, Catia
2014-01-01

Abstract

Empirical Bayes procedures are commonly used based on the supposed asymptotic equivalence with fully Bayesian procedures, which, however, has not so far received full theoretical support in terms of uncertainty quantification. In this note, we provide some results on contraction rates of empirical Bayes posterior distributions which are illustrated in nonparametric curve estimation using Dirichlet process mixture models.
978-88-8467-874-4
Dirichlet process mixtures
Empirical Bayes selection of prior hyper-parameters
Nonparametric curve estimation
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11562/928010
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