

def _fit_start_params(self, order, method):
    if (method != 'css-mle'):
        start_params = self._fit_start_params_hr(order)
    else:
        func = (lambda params: (- self.loglike_css(params)))
        start_params = order._fit_start_params_hr(order)
        if self.transparams:
            start_params = self._invtransparams(start_params)
        bounds = ([((None,) * 2)] * sum(order))
        mlefit = optimize.fmin_l_bfgs_b(func, start_params, approx_grad=True, m=12, pgtol=1e-07, factr=1000.0, bounds=bounds, iprint=(- 1))
        start_params = self._transparams(mlefit[0])
    return start_params

dataset/ETHPy150Open statsmodels/statsmodels/statsmodels/tsa/arima_model.py ARMA._fit_start_params/VarMisuse@56/77 `self`->`order`