I’m torn between AIC and R-squared. I know AIC is often used in model selection, but I can't recall if it specifically applies to forward selection in GLMSELECT.
Ah, I remember now! The forward selection method in GLMSELECT uses the R-squared statistic to determine which variables to add to the model at each step. Option C is the correct answer.
The selection criterion is definitely not MSE, that's used for other model selection methods. I think it's either R-squared or AIC, but I'm leaning more towards R-squared since that's a common metric used in forward selection.
Hmm, I'm a bit confused on this one. I know forward selection is a stepwise regression technique, but I can't remember the exact selection criterion they use. I'll have to think this through carefully.
Loren
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