def _reparam(self):

        k_fe, k_re, k_re2, k_vc = self.k_fe, self.k_re, self.k_re2, self.k_vc
        k_tot = k_fe + k_re2 + k_vc
        ix = np.tril_indices(self.k_re)

        lin = []
        for k in range(k_fe):
            e = np.zeros(k_tot)
            e[k] = 1
            lin.append(e)
        for k in range(k_re2):
            lin.append(np.zeros(k_tot))
        for k in range(k_vc):
            lin.append(np.zeros(k_tot))

        quad = []
        # Quadratic terms for fixed effects.
        for k in range(k_tot):
            quad.append(np.zeros((k_tot, k_tot)))

        # Quadratic terms for random effects covariance.
        ii = np.tril_indices(k_re)
        ix = [(a,b) for a,b in zip(ii[0], ii[1])]
        for i1 in range(k_re2):
            for i2 in range(k_re2):
                ix1 = ix[i1]
                ix2 = ix[i2]
                if (ix1[1] == ix2[1]) and (ix1[0] <= ix2[0]):
                    ii = (ix2[0], ix1[0])
                    k = ix.index(ii)
                    quad[k_fe+k][k_fe+i2, k_fe+i1] += 1
        for k in range(k_tot):
            quad[k] = 0.5*(quad[k] + quad[k].T)

        # Quadratic terms for variance components.
        km = k_fe + k_re2
        for k in range(km, km+k_vc):
            quad[k][k, k] = 1

        return lin, quad
Creates data structure for a new network interface.
dataset/ETHPy150Open statsmodels/statsmodels/statsmodels/regression/mixed_linear_model.py/MixedLM._reparam--crossover with--dataset/ETHPy150Open ganeti/ganeti/lib/cmdlib/instance_set_params.py/LUInstanceSetParams._CreateNewNic