def conf_int(self, alpha=.05, cols=None, cov_type=None):
        """
        Returns confidence intervals for the fitted parameters.

        Parameters
        ----------
        alpha : float, optional
             The `alpha` level for the confidence interval.  i.e., The
             default `alpha` = .05 returns a 95% confidence interval.
        cols : array-like, optional
             `cols` specifies which confidence intervals to return
        cov_type : string
             The covariance type used for computing standard errors;
             must be one of 'robust', 'naive', and 'bias reduced'.
             See `GEE` for details.

        Notes
        -----
        The confidence interval is based on the Gaussian distribution.
        """
        # super doesn't allow to specify cov_type and method is not
        # implemented,
        # FIXME: remove this method here
        if cov_type is None:
            bse = self.bse
        else:
            bse = self.standard_errors(cov_type=cov_type)
        params = self.params
        dist = stats.norm
        q = dist.ppf(1 - alpha / 2)

        if cols is None:
            lower = self.params - q * bse
            upper = self.params + q * bse
        else:
            cols = np.asarray(cols)
            lower = params[cols] - q * bse[cols]
            upper = params[cols] + q * bse[cols]
        return np.asarray(lzip(lower, upper))
dataset/ETHPy150Open statsmodels/statsmodels/statsmodels/genmod/generalized_estimating_equations.py/GEEResults.conf_int/original