def get_packed(self, use_sqrt, has_fe=False):

        if self.k_re > 0:
            if use_sqrt:
                L = np.linalg.cholesky(self.cov_re)
                cpa = L[self._ix]
            else:
                cpa = self.cov_re[self._ix]
        else:
            cpa = np.zeros(0)

        if use_sqrt:
            vcomp = np.sqrt(self.vcomp)
        else:
            vcomp = self.vcomp

        if has_fe:
            pa = np.concatenate((self.fe_params, cpa, vcomp))
        else:
            pa = np.concatenate((cpa, vcomp))

        return pa
Return the model parameters packed into a single vector.
dataset/ETHPy150Open statsmodels/statsmodels/statsmodels/regression/mixed_linear_model.py/MixedLMParams.get_packed