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
Included in
Databases and Information Systems Commons, Numerical Analysis and Scientific Computing Commons