mxPenaltyRidge {OpenMx}

mxPenaltyRidge

Description

Ridge regression regularization

Usage

mxPenaltyRidge(
  what,
  name,
  lambda = 0,
  lambda.step = 0.01,
  lambda.max = 0.4,
  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 start (default 0)

lambda.step

lambda step during penalty search (default 0.01)

lambda.max

when to end the lambda search (default 0.4)

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