Covariance Selection by Thresholding the Sample Correlation Matrix

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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Bibliographic Details
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
Description
Summary: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.

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