Covariance Selection by Thresholding the Sample Correlation Matrix

This article shows that when the nonzero coefficients of the population correlation matrix are all greater in absolute value than (C1logp/n)1/2 for some constant C1, we can obtain covariance selection consistency by thresholding the sample correlation matrix. Furthermore, the rate (logp/n)1/2 is sho...

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Main Author:	JIANG, Binyan
Format:	text
Language:	English
Published:	Institutional Knowledge at Singapore Management University 2013
Subjects:	Bernstein type inequality Covariance selection Large correlation matrix Large covariance matrix Thresholding Databases and Information Systems Numerical Analysis and Scientific Computing
Online Access:	https://ink.library.smu.edu.sg/sis_research/2049 https://ink.library.smu.edu.sg/context/sis_research/article/3048/viewcontent/JiangBY2013SPLCovariance_AFV.pdf
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Institution:	Singapore Management University
Language:	English

id	sg-smu-ink.sis_research-3048
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spelling	sg-smu-ink.sis_research-30482014-02-21T03:50:39Z Covariance Selection by Thresholding the Sample Correlation Matrix JIANG, Binyan This article shows that when the nonzero coefficients of the population correlation matrix are all greater in absolute value than (C1logp/n)1/2 for some constant C1, we can obtain covariance selection consistency by thresholding the sample correlation matrix. Furthermore, the rate (logp/n)1/2 is shown to be optimal. 2013-11-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/2049 info:doi/10.1016/j.spl.2013.07.008 https://ink.library.smu.edu.sg/context/sis_research/article/3048/viewcontent/JiangBY2013SPLCovariance_AFV.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Bernstein type inequality Covariance selection Large correlation matrix Large covariance matrix Thresholding Databases and Information Systems Numerical Analysis and Scientific Computing
institution	Singapore Management University
building	SMU Libraries
continent	Asia
country	Singapore Singapore
content_provider	SMU Libraries
collection	InK@SMU
language	English
topic	Bernstein type inequality Covariance selection Large correlation matrix Large covariance matrix Thresholding Databases and Information Systems Numerical Analysis and Scientific Computing
spellingShingle	Bernstein type inequality Covariance selection Large correlation matrix Large covariance matrix Thresholding Databases and Information Systems Numerical Analysis and Scientific Computing JIANG, Binyan Covariance Selection by Thresholding the Sample Correlation Matrix
description	This article shows that when the nonzero coefficients of the population correlation matrix are all greater in absolute value than (C1logp/n)1/2 for some constant C1, we can obtain covariance selection consistency by thresholding the sample correlation matrix. Furthermore, the rate (logp/n)1/2 is shown to be optimal.
format	text
author	JIANG, Binyan
author_facet	JIANG, Binyan
author_sort	JIANG, Binyan
title	Covariance Selection by Thresholding the Sample Correlation Matrix
title_short	Covariance Selection by Thresholding the Sample Correlation Matrix
title_full	Covariance Selection by Thresholding the Sample Correlation Matrix
title_fullStr	Covariance Selection by Thresholding the Sample Correlation Matrix
title_full_unstemmed	Covariance Selection by Thresholding the Sample Correlation Matrix
title_sort	covariance selection by thresholding the sample correlation matrix
publisher	Institutional Knowledge at Singapore Management University
publishDate	2013
url	https://ink.library.smu.edu.sg/sis_research/2049 https://ink.library.smu.edu.sg/context/sis_research/article/3048/viewcontent/JiangBY2013SPLCovariance_AFV.pdf
_version_	1770571780795138048

Covariance Selection by Thresholding the Sample Correlation Matrix

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