SL.speedglm: Wrapper for speedglm

In SuperLearner: Super Learner Prediction

Wrapper for speedglm

Description

Speedglm is a fast version of glm()

Usage

SL.speedglm(Y, X, newX, family, obsWeights, maxit = 25, k = 2, ...)

Arguments

Y	Outcome variable
X	Training dataframe
newX	Test dataframe
family	Gaussian or binomial
obsWeights	Observation-level weights
maxit	Maximum number of iterations before stopping.
k	numeric, the penalty per parameter to be used; the default k = 2 is the classical AIC.
...	Any remaining arguments, not used.

References

Enea, M. A. R. C. O. (2013). Fitting linear models and generalized linear models with large data sets in R. Statistical Methods for the Analysis of Large Datasets: book of short papers, 411-414.

See Also

predict.SL.speedglm speedglm predict.speedglm

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