SuperLearner wrapper for GAM with Gamma family and log link

A SuperLearner wrapper that implements generalized additive models using the Gamma family with a log link.

Usage

SL.gam.gamma.log(Y, X, newX, obsWeights, deg.gam = 2, cts.num = 4, ...)

Arguments

Y

A numeric vector of outcome values.

X

A numeric matrix or data.frame of covariates and treatment.

newX

A numeric matrix or data.frame of predictors.

obsWeights

Not used.

deg.gam

A numeric representing the degrees of the GAM. Defaults to 2.

cts.num

A numeric indicating the minimum number of unique values a numeric covariate requires to be considered as a continuous variable. Defaults to 4.

...

Any additional arguments.

Value

A list with components:

• pred: A numeric vector of predictions on newX.

• fit: A list containing the fitted model object.

Details

A copy of [SuperLearner::SL.gam] but using the Gammma family.