Bandwidth Selection for High-Dimensional Covariance Matrix Estimation

被引:11
|
作者
Qiu, Yumou [1 ]
Chen, Song Xi [2 ,3 ,4 ]
机构
[1] Univ Nebraska, Dept Stat, Lincoln, NE 68583 USA
[2] Peking Univ, Dept Business Stat & Econometr, Guanghua Sch Management, Beijing 100651, Peoples R China
[3] Peking Univ, Ctr Stat Sci, Beijing 100651, Peoples R China
[4] Iowa State Univ, Dept Stat, Ames, IA 50011 USA
基金
中国国家自然科学基金;
关键词
Banding estimator; Large p; small n; Ratio-consistency; Tapering estimator; Thresholding estimator; REGULARIZATION;
D O I
10.1080/01621459.2014.950375
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
The banding estimator of Bickel and Levina and its tapering version of Cai, Zhang, and Zhou are important high-dimensional covariance estimators. Both estimators require a bandwidth parameter. We propose a bandwidth selector for the banding estimator by minimizing an empirical estimate of the expected squared Frobenius norms of the estimation error matrix. The ratio consistency of the bandwidth selector is established. We provide a lower bound for the coverage probability of the underlying bandwidth being contained in an interval around the bandwidth estimate Extensions to the bandwidth selection for the tapering estimator and threshold level selection for the thresholding covariance estimator are made. Numerical simulations and a case study on sonar spectrum data are conducted to demonstrate the proposed approaches. Supplementary materials for this article are available online.
引用
收藏
页码:1160 / 1174
页数:15
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