Method fit

examples/python/generic_mle.py:132–143

(self, start_params=None, maxiter=10000, maxfun=5000, **kwds)

        return -ll

    def fit(self, start_params=None, maxiter=10000, maxfun=5000, **kwds):
        # we have one additional parameter and we need to add it for summary
        self.exog_names.append('alpha')
        if start_params == None:
            # Reasonable starting values
            start_params = np.append(np.zeros(self.exog.shape[1]), .5)
            # intercept
            start_params[-2] = np.log(self.endog.mean())
        return super(NBin, self).fit(start_params=start_params,
                                     maxiter=maxiter,
                                     maxfun=maxfun,
                                     **kwds)


# Two important things to notice: