cmdSuperLearner.control: Control parameters for the conditional mixed density Super...

In tedwestling/ctsCausal: Methods for Causal Inference with Continuous Exposures

Control parameters for the conditional mixed density Super Learner

Description

This function initiates control parameters for the cmdSuperLearner function.

Usage

cmdSuperLearner.control(
  n.bins = 2:floor(length(unique(A))/50),
  SL.library = c("SL.mean", "SL.glm", "SL.gam", "SL.earth"),
  saveFitLibrary = TRUE,
  verbose = FALSE
)

Arguments

n.bins	Vector of integers >= 2 indicating the number of bins to use for discretization. Defaults to 2:floor(n/100).
SL.library	Library to use for bin-specific SuperLearners. Defaults to c("SL.mean", "SL.glm", "SL.gam", "SL.earth").
saveFitLibrary	Logical indicating whether to save the fit library on the full data. Defaults to TRUE. If FALSE, cannot obtain predicted values on new data later.
verbose	Logical indicating whether to report progress of the estimation process.

Value

Returns a named list with control parameters.

tedwestling/ctsCausal documentation built on Dec. 7, 2022, 3:33 p.m.