Enrique Cardenas III
Enrique Cardenas III
Looking at glum, I don't currently see a way to generate confidence intervals for predictions on an input dataset, although I want to check here. By this, I mean something...
I have an issue regarding obtaining a p-value of a single categorical field in my model. I can see that obtaining p-values for numeric fields is simple using a `model.coef_table()['p_value']`...
Hello all, I'm interested in the elastic net parameter selection method used by [GeneralizedLinearRegressorCV](https://glum.readthedocs.io/en/latest/glm.html#glum.GeneralizedLinearRegressorCV). I know it selects the alpha and l1_ratio parameters that give the [lowest model deviance](https://github.com/Quantco/glum/blob/511b2dff9354328851ae377ad9a89efe752aa581/src/glum/_glm_cv.py#L648-L650) thanks...
When modeling with `glum` using a dataset containing both categorical and numeric features, I want to manually set base levels for the categorical fields. This can be done in `statsmodels`...