code: def mvsk2mnc(args):
      """convert mean, variance, skew, kurtosis to non-central moments"""
      X = _convert_to_multidim(args)
  
      def _local_counts(args):
          mc, mc2, skew, kurt = args
          mnc = mc
          mnc2 = mc2 + mc * mc
          mc3 = skew * (mc2**1.5)  # 3rd central moment
          mnc3 = mc3 + 3 * mc * mc2 + mc**3  # 3rd non-central moment
          mc4 = (kurt + 3.0) * (mc2**2.0)  # 4th central moment
          mnc4 = mc4 + 4 * mc * mc3 + 6 * mc * mc * mc2 + mc**4
          return (mnc, mnc2, mnc3, mnc4)
  
      res = np.apply_along_axis(_local_counts, 0, X)
      # for backward compatibility convert 1-dim output to list/tuple
      return _convert_from_multidim(res, tuple)
  
file_path: statsmodels/statsmodels/stats/moment_helpers.py
imports: import numpy
  from scipy.special import comb
label_desc: Use image node_id 9 for calling a global function with example usage: mvsk2mnc(args) and returns: _convert_from_multidim, mnc,  mnc2,  mnc3,  mnc4