Refactor GEE margins, improve test coverage

This refactor does a few things, prompted by #2156:

1. Removes instance methods for mean_deriv and mean_deriv_exog in favor of methods that are overridden for the GEE nominal model.

2. Simplified the derivative calculations for the nominal model so that the scipy sparse matrix library is not needed.

3. Add GEEMargins to the api

4. Add tests against Stata for marginal effects

5. Add a test of the 2-class nominal model against logistic GLM

6. Change the handling of the Poisson scale parameter to agree with GLM (fix scale=1)



Is this a change in behavior?
I guess the robust cov_params are not affected by this, are they? 

I haven't worked my way through the `scale` part of the code yet.

related: I haven't finished my review and haven't started refactoring the scale estimates yet. But, for the final results this will have to become an option as part of `cov_type`, in GLM and discrete.