linearShrinkEst {cvCovEst}R Documentation

Linear Shrinkage Estimator

Description

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.

Usage

linearShrinkEst(dat, alpha)

Arguments

dat

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

alpha

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.

Value

A matrix corresponding to the estimate of the covariance matrix.

Examples

linearShrinkEst(dat = mtcars, alpha = 0.1)

[Package cvCovEst version 1.0.0 Index]