adaptiveLassoEst: Adaptive LASSO Estimator

In cvCovEst: Cross-Validated Covariance Matrix Estimation

Adaptive LASSO Estimator

Description

adaptiveLassoEst() applied the adaptive LASSO to the entries of the sample covariance matrix. The thresholding function is inspired by the penalized regression introduced by \insertCitezou2006;textualcvCovEst. The thresholding function assigns a weight to each entry of the sample covariance matrix based on its initial value. This weight then determines the relative size of the penalty resulting in larger values being penalized less and reducing bias \insertCiterothman2009cvCovEst.

Usage

adaptiveLassoEst(dat, lambda, n)

Arguments

dat	A numeric data.frame, matrix, or similar object.
lambda	A non-negative numeric defining the amount of thresholding applied to each element of dat's sample covariance matrix.
n	A non-negative numeric defining the exponent of the adaptive weight applied to each element of dat's sample covariance matrix.

Value

A matrix corresponding to the estimate of the covariance matrix.

References

\insertAllCited

Examples

adaptiveLassoEst(dat = mtcars, lambda = 0.9, n = 0.9)

cvCovEst documentation built on May 29, 2024, 5:51 a.m.