class_docstr: Results for rank comparison
  
  This is a subclass of HolderTuple that includes results from intermediate
  computations, as well as methods for hypothesis tests, confidence intervals
  and summary.
class_docstr_tok: ["Results","for","rank","comparison","This","is","a","subclass","of","HolderTuple","that","includes","results","from","intermediate","computations",",","as","well","as","methods","for","hypothesis","tests",",","confidence","intervals","and","summary","."]
docstr: summary table for probability that random draw x1 is larger than x2
  
  Parameters
  ----------
  alpha : float
      Significance level for confidence intervals. Coverage is 1 - alpha
  xname : None or list of str
      If None, then each row has a name column with generic names.
      If xname is a list of strings, then it will be included as part
      of those names.
  
  Returns
  -------
  SimpleTable instance with methods to convert to different output
  formats.
docstr_tok: ["summary","table","for","probability","that","random","draw","x1","is","larger","than","x2","Parameters","--","--","--","--","--","alpha",":","float","Significance","level","for","confidence","intervals",".","Coverage","is","1","-","alpha","xname",":","None","or","list","of","str","If","None",",","then","each","row","has","a","name","column","with","generic","names",".","If","xname","is","a","list","of","strings",",","then","it","will","be","included","as","part","of","those","names",".","Returns","--","--","--","-","SimpleTable","instance","with","methods","to","convert","to","different","output","formats","."]
code: def summary(self, alpha=0.05, xname=None):
      """summary table for probability that random draw x1 is larger than x2
  
      Parameters
      ----------
      alpha : float
          Significance level for confidence intervals. Coverage is 1 - alpha
      xname : None or list of str
          If None, then each row has a name column with generic names.
          If xname is a list of strings, then it will be included as part
          of those names.
  
      Returns
      -------
      SimpleTable instance with methods to convert to different output
      formats.
      """
  
      yname = "None"
      effect = np.atleast_1d(self.prob1)
      if self.pvalue is None:
          statistic, pvalue = self.test_prob_superior()
      else:
          pvalue = self.pvalue
          statistic = self.statistic
      pvalues = np.atleast_1d(pvalue)
      ci = np.atleast_2d(self.conf_int(alpha=alpha))
      if ci.shape[0] > 1:
          ci = ci.T
      use_t = self.use_t
      sd = np.atleast_1d(np.sqrt(self.var_prob))
      statistic = np.atleast_1d(statistic)
      if xname is None:
          xname = ["c%d" % ii for ii in range(len(effect))]
  
      xname2 = ["prob(x1>x2) %s" % ii for ii in xname]
  
      title = "Probability sample 1 is stochastically larger"
      from statsmodels.iolib.summary import summary_params
  
      summ = summary_params(
          (self, effect, sd, statistic, pvalues, ci),
          yname=yname,
          xname=xname2,
          use_t=use_t,
          title=title,
          alpha=alpha,
      )
      return summ
  
file_path: statsmodels/statsmodels/stats/nonparametric.py
imports: import numpy
  from scipy import stats
  from scipy.stats import rankdata
  from statsmodels.stats.base import HolderTuple
  from statsmodels.stats.weightstats import _tconfint_generic, _tstat_generic, _zconfint_generic, _zstat_generic
label_desc: Use image node_id 6 for calling the RankCompareResult obj's underlying member method code with example usage: obj.summary(alpha, xname) and returns: summ