code: def Rpp(v):
      """Hessian"""
      result = (
          2
          * (A - R(v) * B - outer(B * v, Rp(v)) - outer(Rp(v), B * v))
          / dot(v.T, B * v)
      )
      # print "Rpp: ", result
      return result
  
file_path: statsmodels/statsmodels/sandbox/mle.py
imports: import numpy
  from numpy import dot, outer, random
  from scipy import io, linalg, optimize
  from scipy.sparse import eye
  import matplotlib.pyplot
label_desc: Use image node_id 3 for calling a global function with example usage: Rpp(v) and returns: result