'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.'

def conf_int(self, alpha=0.05, cols=None, cov_type=None):

    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))
