linearShrinkEst {cvCovEst}R Documentation

Linear Shrinkage Estimator


linearShrinkEst() computes the linear shrinkage estimate of the covariance matrix for a given value of alpha. The linear shrinkage estimator is defined as the convex combination of the sample covariance matrix and the identity matrix. The choice of alpha determines the bias-variance tradeoff of the estimators in this class: values near 1 are more likely to exhibit high variance but low bias, and values near 0 are more likely to be be very biased but have low variance.


linearShrinkEst(dat, alpha)



A numeric data.frame, matrix, or similar object.


A numeric between 0 and 1 defining convex combinations of the sample covariance matrix and the identity. alpha = 1 produces the sample covariance matrix, and alpha = 0 returns the identity.


A matrix corresponding to the estimate of the covariance matrix.


linearShrinkEst(dat = mtcars, alpha = 0.1)

[Package cvCovEst version 1.1.0 Index]