Covariance Regularization by Thresholding
Covariance Regularization by Thresholding
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Publisher
Hayward: Institute of Mathematical Statistics
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Language
English
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Publisher
Hayward: Institute of Mathematical Statistics
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Contents
This paper considers regularizing a covariance matrix of p variables estimated from n observations, by hard thresholding. We show that the thresholded estimate is consistent in the operator norm as long as the true covariance matrix is sparse in a suitable sense, the variables are Gaussian or sub-Gaussian, and (log p) / n → 0, and obtain explicit r...
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Full title
Covariance Regularization by Thresholding
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TN_cdi_projecteuclid_primary_oai_CULeuclid_euclid_aos_1231165180
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_projecteuclid_primary_oai_CULeuclid_euclid_aos_1231165180
Other Identifiers
ISSN
0090-5364
E-ISSN
2168-8966
DOI
10.1214/08-AOS600
