Fix predict for drop_intercept models #76
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- add tests that used to fail but now pass
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Cc: @piever |
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LGTM! At the time I forgot to test |
nalimilan
approved these changes
Oct 1, 2018
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This has been reviewed a long time ago. Why not merge it? |
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On the one hand, everything is going to change once #71 is merged (which should be soon, inshallah) in a way that will make this redundant. On the other hand, it might make sense to merge this one now in order to fix an obvious bug instead of having to backport it... thoughts @nalimilan ? |
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I'd say merge, unless it creates conflicts that are too costly for you to fix (unlikely). |
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Agreed. |
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Thanks for the fix, and sorry for the delay in merging! |
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No worries. Thanks for merging. I look forward to #71 |
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For models M that specify drop_intercept(M) = true, the fit(M,Formula,df) function adds back and then drops the intercept just before creating the model frame. This same idiom also needs to be applied to predict() otherwise contrast variables are mishandled, resulting in a dimension mismatch error.
This PR: