def _derivative_exog(self, params, exog=None, transform="dydx",
            dummy_idx=None, count_idx=None):
        # group 3 poisson, nbreg, zip, zinb
        if exog is None:
            exog = self.exog
        margeff = self.predict(params, exog)[:,None] * params[None,:]
        if 'ex' in transform:
            margeff *= exog
        if 'ey' in transform:
            margeff /= self.predict(params, exog)[:,None]

        if count_idx is not None:
            from statsmodels.discrete.discrete_margins import (
                    _get_count_effects)
            margeff = _get_count_effects(margeff, exog, count_idx, transform,
                    self, params)
        if dummy_idx is not None:
            from statsmodels.discrete.discrete_margins import (
                    _get_dummy_effects)
            margeff = _get_dummy_effects(margeff, exog, dummy_idx, transform,
                    self, params)
        return margeff
[<channel>]
dataset/ETHPy150Open statsmodels/statsmodels/statsmodels/discrete/discrete_model.py/CountModel._derivative_exog--crossover with--dataset/ETHPy150Open ProgVal/Limnoria/plugins/Topic/plugin.py/Topic.refresh