I have created a generalized linear model with sklearn with the following code
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.3)
clf_hard = GammaRegressor(alpha = 0)
clf_hard.fit(X_train, y_train)
X_train and y_train are simply pandas dataframes. Now, I want to infer significance of the coefficients from this model. Especially, I want to use F-test and chi-square tests if it is possible.
My question is therefore simple.
Are there any ways to perform this in sklearn or not? If no, where can I read about the significance in such kind of models? Maybe it is possible to write custom function in python to perform these tests?