0d294ab613b7b6fff9bab00d2e8e94d531908d2e,statsmodels/tsa/exponential_smoothing/ets.py,ETSModel,fit,#ETSModel#Any#Any#Any#Any#Any#Any#,655

Before Change

            kwargs["bounds"] = bounds

            with self.use_internal_loglike():
                mlefit = super().fit(
                    start_params,
                    fargs=(yhat, xhat),
                    method="lbfgs",

After Change

            start_params = self.start_params

        if self._has_fixed_params and len(self._free_params_index) == 0:
            final_params = np.asarray(list(self._fixed_params.values()))
            mlefit = Bunch(
                params=start_params, mle_retvals=None, mle_settings=None
            )
        else:

Instances