The minimum regularized covariance determinant estimator
Abstract
The minimum covariance determinant (MCD) approach estimates the location and scatter matrix using the subset of given size with lowest sample covariance determinant. Its main drawback is that it cannot be applied when the dimension exceeds the subset size. We propose the minimum regularized covariance determinant (MRCD) approach, which differs from the MCD in that the scatter matrix is a convex combination of a target matrix and the sample...
Paper Details
Title
The minimum regularized covariance determinant estimator
Published Date
Feb 1, 2020
Journal
Volume
30
Issue
1
Pages
113 - 128
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