code: def logmps(params, xsorted, dist):
      """calculate negative log of Product-of-Spacings
  
      Parameters
      ----------
      params : array_like, tuple ?
          parameters of the distribution funciton
      xsorted : array_like
          data that is already sorted
      dist : instance of a distribution class
          only cdf method is used
  
      Returns
      -------
      mps : float
          negative log of Product-of-Spacings
  
  
      Notes
      -----
      MPS definiton from JKB page 233
      """
      xcdf = np.r_[0.0, dist.cdf(xsorted, *params), 1.0]
      D = np.diff(xcdf)
      return -np.log(D).mean()
  
file_path: statsmodels/statsmodels/sandbox/distributions/estimators.py
imports: import numpy
  from scipy import stats, optimize, special
label_desc: Use image node_id 10 for calling a global function with example usage: logmps(params, xsorted, dist) and returns: unknown