docstr: Summarize the fitted model.
  
  Parameters
  ----------
  yname : str, optional
      Default is `y`
  xname : list[str], optional
      Names for the exogenous variables, default is "var_xx".
      Must match the number of parameters in the model
  title : str, 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
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code: def summary(self, yname=None, xname=None, title=None, alpha=0.05):
      """
      Summarize the fitted model.
  
      Parameters
      ----------
      yname : str, optional
          Default is `y`
      xname : list[str], optional
          Names for the exogenous variables, default is "var_xx".
          Must match the number of parameters in the model
      title : str, 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
      """
  
      top_left = [
          ("Dep. Variable:", None),
          ("Model:", None),
          ("Log-Likelihood:", None),
          ("Method:", [self.method]),
          ("Date:", None),
          ("Time:", None),
      ]
  
      top_right = [
          ("No. Observations:", None),
          ("No. groups:", [self.n_groups]),
          ("Min group size:", [self._group_stats[0]]),
          ("Max group size:", [self._group_stats[1]]),
          ("Mean group size:", [self._group_stats[2]]),
      ]
  
      if title is None:
          title = "Conditional Logit Model Regression Results"
  
      # create summary tables
      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
      )
  
      return smry
  
imports: import numpy
  import statsmodels.base.model
  import statsmodels.regression.linear_model
  import statsmodels.base.wrapper
  from statsmodels.discrete.discrete_model import MultinomialResults, MultinomialResultsWrapper
  import collections
  import warnings
  import itertools
label_desc: Use image node_id 2 for calling the ConditionalResults obj's underlying member method code with example usage: obj.summary(yname, xname, title, alpha) and returns: smry