, you get a perfect fit: 8
> coefficients fit to 8 cases with 0 df for error.
>
> This is of course nonsense: You don't have enough data to fit a model of
> this complexity. In fact, you might not have enough data to reasonably fit
> a model with just 1 predictor.
>
> I'
Hello. I'm trying to use the function vif from package car in a lm. However
it returns the following error:
"Error in vif.default(lm(MDescores.sitescores ~ hidroperiodo + localizacao
+ : there are aliased coefficients in the model"
When I exclude any predictor from the model, it returns this warn
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