Covariance Selection by Thresholding the Sample Correlation Matrix

Author

Binyan JIANG, Singapore Management University LARCFollow

Publication Type

Journal Article

Version

submittedVersion

Publication Date

11-2013

Abstract

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.

Keywords

Bernstein type inequality, Covariance selection, Large correlation matrix, Large covariance matrix, Thresholding

Discipline

Databases and Information Systems | Numerical Analysis and Scientific Computing

Publication

Statistics and Probability Letters

Volume

83

Issue

11

First Page

2492

Last Page

2498

ISSN

0167-7152

Identifier

10.1016/j.spl.2013.07.008

Publisher

Elsevier

Embargo Period

2-20-2014

Citation

JIANG, Binyan. Covariance Selection by Thresholding the Sample Correlation Matrix. (2013). Statistics and Probability Letters. 83, (11), 2492-2498.
Available at: https://ink.library.smu.edu.sg/sis_research/2049

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.

Additional URL

http://dx.doi.org/10.1016/j.spl.2013.07.008