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It'd be nice to be able to fit GLMs without covariates. It's usually trivial, except when offsets are involved...
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What should the interface look like? fit is pretty straightforward, but I'm not sure about predict.
fit
predict
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I found a way to phrase the obvious, which worked for me using the formula interface: formula = "Y~ {np.ones_like(Y)}", fit_intercept=True
formula = "Y~ {np.ones_like(Y)}", fit_intercept=True
The more obvious approach "Y~1" throws errors with "fit_intercept=True" and with "fit_intercept=False"
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It'd be nice to be able to fit GLMs without covariates. It's usually trivial, except when offsets are involved...
The text was updated successfully, but these errors were encountered: