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FullModel<- (lm(Fubar~.-Foo-Bar,data=BarFoo)) NullModel<-(lm(Fubar~1)) step(NullModel,scope=formula(FullModel),direction="forward",k=log(nrow(BarFoo)))

When doing the above forward stepwise regression, the forward steps halt before certain variables are added in. does this mean that they do not improve the AIC score or does it mean that the inputs are in error?

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That means that they do not improve AIC.

But forward selection isn't great (no automatic method is).

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