class_docstr: Maximum Likelihood Estimation pareto distribution
  
  first version: iid case, with constant parameters
code: def initialize(self):  # TODO needed or not
      super().initialize()
      extra_params_names = ["shape", "loc", "scale"]
      self._set_extra_params_names(extra_params_names)
  
      # start_params needs to be attribute
      self.start_params = np.array([1.5, self.endog.min() - 1.5, 1.0])
  
imports: import numpy
  from scipy import stats
  from statsmodels.base.model import GenericLikelihoodModel
  from numpy.testing import assert_array_less, assert_almost_equal, assert_allclose
label_desc: Use image node_id 1 for calling the MyPareto obj's underlying member method code with example usage: obj.initialize() without return types