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	TEST FOR BANDEDNESS OF HIGH-DIMENSIONAL COVARIANCE MATRICES AND BANDWIDTH ESTIMATION
	Qiu, Yumou ; Chen, Song Xi
	2012
关键词	Banded covariance matrix bandwidth estimation high data dimension large p small n nonparametric LARGEST EIGENVALUE REGULARIZATION DISTRIBUTIONS INDEPENDENCE LASSO
英文摘要	Motivated by the latest effort to employ banded matrices to estimate a high-dimensional covariance Sigma, we propose a test for Sigma being banded with possible diverging bandwidth. The test is adaptive to the "large p, small n" situations without assuming a specific parametric distribution for the data. We also formulate a consistent estimator for the bandwidth of a banded high-dimensional covariance matrix. The properties of the test and the bandwidth estimator are investigated by theoretical evaluations and simulation studies, as well as an empirical analysis on a protein mass spectroscopy data.; Statistics & Probability; SCI(E); 0; ARTICLE; 3; 1285-1314; 40
语种	英语
出处	SCI
出版者	统计学纪事
内容类型	其他
源URL	[http://hdl.handle.net/20.500.11897/393350]
专题	数学科学学院
推荐引用方式 GB/T 7714	Qiu, Yumou,Chen, Song Xi. TEST FOR BANDEDNESS OF HIGH-DIMENSIONAL COVARIANCE MATRICES AND BANDWIDTH ESTIMATION. 2012-01-01.

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