ASYMPTOTIC BEHAVIOUR OF THE EMPIRICAL BAYES POSTERIORS ASSOCIATED TO MAXIMUM MARGINAL LIKELIHOOD ESTIMATOR

被引:22
|
作者
Rousseau, Judith [1 ,2 ]
Szabo, Botond [3 ,4 ]
机构
[1] Univ Paris 09, CEREMADE, Pl Marechal Delattre De Tassigny, F-75016 Paris, France
[2] ENSAE, CREST, Paris, France
[3] Tech Univ Budapest, Budapest, Hungary
[4] Leiden Univ, Math Inst, Niels Bohrweg 1, NL-2333 CA Leiden, Netherlands
来源
ANNALS OF STATISTICS | 2017年 / 45卷 / 02期
基金
欧洲研究理事会;
关键词
Posterior contraction rates; adaptation; empirical Bayes; hierarchical Bayes; nonparametric regression; density estimation; Gaussian prior; truncation prior; DIMENSIONAL EXPONENTIAL-FAMILIES; GAUSSIAN PROCESS PRIORS; VON MISES THEOREM; INVERSE PROBLEMS; CONVERGENCE-RATES; CREDIBLE SETS; DISTRIBUTIONS; REGRESSION; CONTRACTION; FUNCTIONALS;
D O I
10.1214/16-AOS1469
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
We consider the asymptotic behaviour of the marginal maximum likelihood empirical Bayes,posterior distribution in general setting. First, we characterize the set where the maximum marginal likelihood estimator is located with high probability. Then we provide oracle type of upper and lower bounds for the contraction rates of the empirical Bayes posterior. We also show that the hierarchical Bayes posterior achieves the same contraction rate as the maximum marginal likelihood empirical Bayes posterior. We demonstrate the applicability of our general results for various models and prior distributions by deriving upper and lower bounds for the contraction rates of the corresponding empirical and hierarchical Bayes posterior distributions.
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页码:833 / 865
页数:33
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