'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):

    top_left = [('Dep.    Variable:', None), ('Model:', None), ('Model    Family:', [self.family.__class__.__name__]), ('Link    Function:', [self.family.link.__class__.__name__]), ('Method:', [self.method]), ('Date:', None), ('Time:', None), ('No.    Iterations:', [('%d' % self.fit_history['iteration'])])]
    top_right = [('No.    Observations:', None), ('Df    Residuals:', None), ('Df    Model:', None), ('Scale:', [self.scale]), ('Log-Likelihood:', None), ('Deviance:', [('%#8.5g' % self.deviance)]), ('Pearson    chi2:', [('%#6.3g' % self.pearson_chi2)])]
    if (title is None):
        title = 'Generalized    Linear    Model    Regression    Results'
    from statsmodels.iolib.summary import Summary
    smry = Summary()
    smry.add_table_2cols(self, gleft=top_left, gright=top_right, yname=yname, xname=xname, title=title)
    smry.add_table_params(self, yname=yname, 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
