shrinkcovmat.identity {ShrinkCovMat} | 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 the identity matrix.
shrinkcovmat.identity(data, centered = FALSE)
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.equal
and
shrinkcovmat.unequal
.
data(colon) normal_group <- colon[, 1:40] tumor_group <- colon[, 41:62] sigma_hat_normal_group <- shrinkcovmat.identity(normal_group) sigma_hat_normal_group sigma_hat_tumor_group <- shrinkcovmat.identity(tumor_group) sigma_hat_tumor_group