SL.lm: Wrapper for lm

In SuperLearner: Super Learner Prediction

Wrapper for lm

Description

Wrapper for OLS via lm(), which may be faster than glm().

Usage

SL.lm(Y, X, newX, family, obsWeights, model = TRUE, ...)

Arguments

Y	Outcome variable
X	Training dataframe
newX	Test dataframe
family	Gaussian or binomial
obsWeights	Observation-level weights
model	Whether to save model.matrix of data in fit object. Set to FALSE to save memory.
...	Any remaining arguments, not used.

References

Fox, J. (2015). Applied regression analysis and generalized linear models. Sage Publications.

See Also

predict.SL.lm lm predict.lm SL.speedlm

Examples

data(Boston, package = "MASS")
Y = Boston$medv
# Remove outcome from covariate dataframe.
X = Boston[, -14]

set.seed(1)

sl = SuperLearner(Y, X, family = gaussian(),
                  SL.library = c("SL.mean", "SL.lm"))

print(sl)

SuperLearner documentation built on May 29, 2024, 5:25 a.m.