code: def setup_class(cls):
      cls.d_offset = 0
      cls.ddistr = stats.lomax  # instead of pareto to avoid p(y=0) = 0
      cls.paramg = (2, 0, 1.5)  # include constant so we can use args
      cls.paramd = (
          2,
          1.5,
      )
      cls.shapes = "c, s"
  
      cls.start_params = (0.5, 0.5)
  
imports: import numpy
  from numpy.testing import assert_allclose, assert_equal
  from scipy import stats
  from scipy.stats import poisson, nbinom
  from statsmodels.tools.tools import Bunch
  from statsmodels.distributions.discrete import genpoisson_p, truncatedpoisson, truncatednegbin, zipoisson, zinegbin, zigenpoisson, DiscretizedCount, DiscretizedModel
label_desc: Use image node_id 1 for calling the TestDiscretizedLomax obj's underlying member method code with example usage: obj.setup_class(cls) without return types