stepwise: Stepwise Model Selection

Description Usage Arguments Value Author(s) References See Also Examples

Description

This function is a front end to the stepAIC function in the MASS package.

Usage

1
2
3
stepwise(mod, 
    direction = c("backward/forward", "forward/backward", "backward", "forward"), 
    criterion = c("BIC", "AIC"), ...)

Arguments

mod

a model object of a class that can be handled by stepAIC.

direction

if "backward/forward" (the default), selection starts with the full model and eliminates predictors one at a time, at each step considering whether the criterion will be improved by adding back in a variable removed at a previous step; if "forward/backwards", selection starts with a model including only a constant, and adds predictors one at a time, at each step considering whether the criterion will be improved by removing a previously added variable; "backwards" and "forward" are similar without the reconsideration at each step.

criterion

for selection. Either "BIC" (the default) or "AIC". Note that stepAIC labels the criterion in the output as "AIC" regardless of which criterion is employed.

...

arguments to be passed to stepAIC.

Value

The model selected by stepAIC.

Author(s)

John Fox jfox@mcmaster.ca

References

W. N. Venables and B. D. Ripley Modern Applied Statistics Statistics with S, Fourth Edition Springer, 2002.

See Also

stepAIC

Examples

1
2
3
4
5
6
# adapted from ?stepAIC in MASS
require(MASS)
example(birthwt)
birthwt.glm <- glm(low ~ ., family = binomial, data = bwt)
stepwise(birthwt.glm, trace = FALSE)
stepwise(birthwt.glm, direction="forward/backward")


Search within the Rcmdr2 package
Search all R packages, documentation and source code

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.