def conf_int_el(self, param_num, upper_bound=None,
                       lower_bound=None, sig=.05, method='nm',
                       stochastic_exog=1):
        r0 = chi2.ppf(1 - sig, 1)
        param_num = np.array([param_num])
        if upper_bound is None:
            upper_bound = (np.squeeze(self.model.fit().
                                      conf_int(.0001)[param_num])[1])
        if lower_bound is None:
            lower_bound = (np.squeeze(self.model.fit().conf_int(.00001)
                                      [param_num])[0])
        f = lambda b0:  self.el_test(np.array([b0]), param_num,
                                     method=method,
                                 stochastic_exog=stochastic_exog)[0] - r0
        lowerl = optimize.brentq(f, lower_bound, self.params[param_num])
        upperl = optimize.brentq(f, self.params[param_num], upper_bound)
        return (lowerl, upperl)
Returns the confidence interval for a regression parameter when the
dataset/ETHPy150Open statsmodels/statsmodels/statsmodels/emplike/originregress.py/OriginResults.conf_int_el