'Summarize the Regression Results
Parameters
yname : string, optional
Default is `y`
xname : list of strings, optional
Default is `var_##` for ## in p the number of regressors
title : string, optional
Title for the top table. If not None, then this replaces the
default title
alpha : float
significance level for the confidence intervals
Returns
smry : Summary instance
this holds the summary tables and text, which can be printed or
converted to various output formats.
See Also
statsmodels.iolib.summary.Summary : class to hold summary
results'

def summary(self, yname=None, xname=None, title=None, alpha=0.05, yname_list=None):

    top_left = [('Dep.    Variable:', None), ('Model:', [self.model.__class__.__name__]), ('Method:', ['MLE']), ('Date:', None), ('Time:', None), ('converged:', [('%s' % self.mle_retvals['converged'])])]
    top_right = [('No.    Observations:', None), ('Df    Residuals:', None), ('Df    Model:', None), ('Pseudo    R-squ.:', [('%#6.4g' % self.prsquared)]), ('Log-Likelihood:', None), ('LL-Null:', [('%#8.5g' % self.llnull)]), ('LLR    p-value:', [('%#6.4g' % self.llr_pvalue)])]
    if (title is None):
        title = ((self.model.__class__.__name__ + '    ') + 'Regression    Results')
    from statsmodels.iolib.summary import Summary
    smry = Summary()
    (yname, yname_list) = self._get_endog_name(yname, yname_list)
    smry.add_table_2cols(self, gleft=top_left, gright=top_right, yname=yname, xname=xname, title=title)
    smry.add_table_params(self, yname=yname_list, xname=xname, alpha=alpha, use_t=self.use_t)
    if hasattr(self, 'constraints'):
        smry.add_extra_txt(['Model    has    been    estimated    subject    to    linear    equality    constraints.'])
    return smry
