R: Lasso Penalty

lasso {lqa}

R Documentation

Lasso Penalty

Object of the penalty class to handle the lasso penalty (Tibshirani, 1996).

lasso (lambda = NULL, ...)

lambda

regularization parameter. This must be a nonnegative real number.

...

further arguments

The ‘classic’ penalty that incorporates variables selection. As introduced in Tibshirani (1996) the lasso penalty is defined as

P_\lambda^r (\boldsymbol{\beta}) = \lambda \sum_{i=1}^p |\beta_j|.

An object of the class penalty. This is a list with elements

penalty

character: the penalty name.

lambda

double: the (nonnegative) regularization parameter.

getpenmat

function: computes the diagonal penalty matrix.

Jan Ulbricht

Tibshirani, R. (1996) Regression shrinkage and selection via the lasso. Journal of the Royal Statistical Society B 58, 267–288.