SL.speedglm {SuperLearner}

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