def conf_int(self, method='endpoint', alpha=0.05, **kwds):
        tmp = np.linspace(0, 1, 6)
        is_linear = (self.link.inverse(tmp) == tmp).all()
        if method == 'endpoint' and not is_linear:
            ci_linear = self.linpred.conf_int(alpha=alpha, obs=False)
            ci = self.link.inverse(ci_linear)
        elif method == 'delta' or is_linear:
            se = self.se_mean
            q = self.dist.ppf(1 - alpha / 2., *self.dist_args)
            lower = self.predicted_mean - q * se
            upper = self.predicted_mean + q * se
            ci = np.column_stack((lower, upper))
            # if we want to stack at a new last axis, for lower.ndim > 1
            # np.concatenate((lower[..., None], upper[..., None]), axis=-1)

        return ci
Return True if port has as a security group and it's value
dataset/ETHPy150Open statsmodels/statsmodels/statsmodels/genmod/_prediction.py/PredictionResults.conf_int--crossover with--dataset/ETHPy150Open openstack/neutron/neutron/db/securitygroups_db.py/SecurityGroupDbMixin._check_update_deletes_security_groups