control_rwl {polle}

Control arguments for Residual Weighted Learning

Description

control_rwl sets the default control arguments for residual learning , type = "rwl". The arguments are passed directly to DynTxRegime::rwl() if not specified otherwise.

Usage

control_rwl(
  moPropen,
  moMain,
  regime,
  fSet = NULL,
  lambdas = 2,
  cvFolds = 0L,
  kernel = "linear",
  kparam = NULL,
  responseType = "continuous",
  verbose = 2L
)

Arguments

moPropen

Propensity model of class "ModelObj", see modelObj::modelObj.

moMain

Main effects outcome model of class "ModelObj".

regime

An object of class formula specifying the design of the policy/regime.

fSet

A function or NULL defining subset structure.

lambdas

Numeric or numeric vector. Penalty parameter.

cvFolds

Integer. Number of folds for cross-validation of the parameters. "logit", "exp", "hinge", "sqhinge", "huber".

kernel

The options are "linear", "poly", "radial".

kparam

Numeric. Kernel parameter

responseType

Character string. Options are "continuous", "binary", "count".

verbose

Integer.

Value

list of (default) control arguments.