On adaptive minimax density estimation on Rd

被引:71
作者
Goldenshluger, A. [1 ]
Lepski, O. [2 ]
机构
[1] Univ Haifa, Dept Stat, IL-31905 Haifa, Israel
[2] Univ Aix Marseille, Lab Anal, F-13453 Marseille, France
关键词
Density estimation; Oracle inequality; Adaptive estimation; Kernel estimators; L-p-risk; NONLINEAR ESTIMATION;
D O I
10.1007/s00440-013-0512-1
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 address the problem of adaptive minimax density estimation on with -loss on the anisotropic Nikol'skii classes. We fully characterize behavior of the minimax risk for different relationships between regularity parameters and norm indexes in definitions of the functional class and of the risk. In particular, we show that there are four different regimes with respect to the behavior of the minimax risk. We develop a single estimator which is (nearly) optimal in order over the complete scale of the anisotropic Nikol'skii classes. Our estimation procedure is based on a data-driven selection of an estimator from a fixed family of kernel estimators.
引用
收藏
页码:479 / 543
页数:65
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