mxPenaltyLASSO {OpenMx}

mxPenaltyLASSO

Description

Least Absolute Selection and Shrinkage Operator regularization

Usage

mxPenaltyLASSO(
  what,
  name,
  lambda = 0,
  lambda.step = 0.01,
  lambda.max = NA,
  lambda.min = NA,
  epsilon = 1e-05,
  scale = 1,
  ...,
  hyperparams = c("lambda")
)

Arguments

what

A character vector of parameters to regularize

name

Name of the regularizer object

lambda

strength of the penalty to be applied at starting values (default 0)

lambda.step

step function for lambda step (default .01)

lambda.max

end of lambda range (default .4)

lambda.min

minimum lambda value (default lambda)

epsilon

how close to zero is zero?

scale

a given parameter is divided by scale before comparison with epsilon

...

Not used. Forces remaining arguments to be specified by name

hyperparams

a character vector of hyperparameter names