def fit(self, maxiter=60, ctol=1e-6, start_params=None,
            params_niter=1, first_dep_update=0,
            cov_type='robust'):

        rslt = super(NominalGEE, self).fit(maxiter, ctol, start_params,
                                           params_niter, first_dep_update,
                                           cov_type=cov_type)
        if rslt is None:
            warnings.warn("GEE updates did not converge",
                          ConvergenceWarning)
            return None

        rslt = rslt._results   # use unwrapped instance
        res_kwds = dict(((k, getattr(rslt, k)) for k in rslt._props))
        # Convert the GEEResults to a NominalGEEResults
        nom_rslt = NominalGEEResults(self, rslt.params,
                                     rslt.scale / rslt.cov_params(),
                                     rslt.scale,
                                     cov_type=cov_type,
                                     attr_kwds=res_kwds)
        #for k in rslt._props:
        #    setattr(nom_rslt, k, getattr(rslt, k))

        return NominalGEEResultsWrapper(nom_rslt)
dataset/ETHPy150Open statsmodels/statsmodels/statsmodels/genmod/generalized_estimating_equations.py/NominalGEE.fit/swapped operands of `/`