code: def _asymptotic_pvalue(stats):
      r"""Calculate the p-value based on an approximation of the distribution of
      the test statistic under the null.
  
      Parameters
      ----------
      stats: namedtuple
          The result obtained from calling ``distance_statistics(x, y)``.
  
      Returns
      -------
      test_statistic : float
          The test statistic.
      pval : float
          The asymptotic p-value.
  
      """
      test_statistic = np.sqrt(stats.test_statistic / stats.S)
      pval = (1 - norm.cdf(test_statistic)) * 2
  
      return test_statistic, pval
  
file_path: statsmodels/statsmodels/stats/dist_dependence_measures.py
imports: from collections import namedtuple
  import warnings
  import numpy
  from scipy.spatial.distance import pdist, squareform
  from scipy.stats import norm
  from statsmodels.tools.sm_exceptions import HypothesisTestWarning
label_desc: Use image node_id 4 for calling a global function with example usage: _asymptotic_pvalue(stats) and returns: test_statistic,  pval