Stepwise Model Selection
This function is a front end to the
stepAIC function in the
stepwise(mod, direction = c("backward/forward", "forward/backward", "backward", "forward"), criterion = c("BIC", "AIC"), ...)
- a model object of a class that can be handled by
"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 st
- for selection. Either
"BIC"(the default) or
"AIC". Note that
stepAIClabels the criterion in the output as
"AIC"regardless of which criterion is employed.
- arguments to be passed to
- The model selected by
W. N. Venables and B. D. Ripley Modern Applied Statistics Statistics with S, Fourth Edition Springer, 2002.
# 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")
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