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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Institutional Knowledge at Singapore Management University
2013
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| الوصول للمادة أونلاين: | 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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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 |
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Singapore Management University |
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SMU Libraries |
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Asia |
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Singapore Singapore |
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SMU Libraries |
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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 |
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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 |