shrinkcovmat.equal-deprecated | R Documentation |
Provides a nonparametric Stein-type shrinkage estimator of the covariance matrix that is a linear combination of the sample covariance matrix and of a diagonal matrix with the average of the sample variances on the diagonal and zeros elsewhere.
shrinkcovmat.equal(data, centered)
data |
a numeric matrix containing the data. |
centered |
a logical indicating if the mean vector is the zero vector. |
The rows of the data matrix data
correspond to variables and the
columns to subjects.
Returns an object of the class 'shrinkcovmathat' that has components:
SigmaHat |
The Stein-type shrinkage estimator of the covariance matrix. |
lambdahat |
The estimated optimal shrinkage intensity. |
sigmasample |
The sample covariance matrix. |
Target |
The target covariance matrix. |
centered |
If the data are centered around their mean vector. |
Anestis Touloumis
Touloumis, A. (2015) nonparametric Stein-type Shrinkage Covariance Matrix Estimators in High-Dimensional Settings. Computational Statistics & Data Analysis 83, 251–261.
shrinkcovmat.unequal
and
shrinkcovmat.identity
.
ShrinkCovMat-deprecated
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