Regularization for high-dimensional covariance matrix
In many applications, high-dimensional problem may occur often for various reasons, for example, when the number of variables under consideration is much bigger than the sample size, i.e., p >> n. For highdimensional data, the underlying structures of certain covariance matrix estimates are us...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
De Gruyter
2016-04-01
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| Series: | Special Matrices |
| Subjects: | |
| Online Access: | http://www.degruyter.com/view/j/spma.2016.4.issue-1/spma-2016-0018/spma-2016-0018.xml?format=INT |