code: def _select_sigma(x, percentile=25):
      """
      Returns the smaller of std(X, ddof=1) or normalized IQR(X) over axis 0.
  
      References
      ----------
      Silverman (1986) p.47
      """
      # normalize = norm.ppf(.75) - norm.ppf(.25)
      normalize = 1.349
      IQR = (
          scoreatpercentile(x, 75) - scoreatpercentile(x, 25)
      ) / normalize
      std_dev = np.std(x, axis=0, ddof=1)
      if IQR > 0:
          return np.minimum(std_dev, IQR)
      else:
          return std_dev
  
file_path: statsmodels/statsmodels/nonparametric/bandwidths.py
imports: import numpy
  from scipy.stats import scoreatpercentile
  from statsmodels.compat.pandas import Substitution
  from statsmodels.sandbox.nonparametric import kernels
label_desc: Use image node_id 1 for calling a global function with example usage: _select_sigma(x, percentile) and returns: np, std_dev