code: def setup_class(cls):
      data = datasets.randhie.load()
      exog = add_constant(np.asarray(data.exog)[:, :4], prepend=False)
      mod = TruncatedLFPoisson(data.endog, exog, truncation=5)
      cls.res1 = mod.fit(method="newton", maxiter=500)
      res2 = RandHIE()
      res2.truncated_poisson()
      cls.res2 = res2
  
imports: import warnings
  import numpy
  from numpy.testing import assert_allclose, assert_equal
  from statsmodels import datasets
  from statsmodels.tools.tools import add_constant
  from statsmodels.tools.testing import Holder
  from statsmodels.tools.sm_exceptions import ConvergenceWarning
  from statsmodels.distributions.discrete import truncatedpoisson, truncatednegbin
  from statsmodels.discrete.truncated_model import TruncatedLFPoisson, TruncatedLFNegativeBinomialP, HurdleCountModel
  from statsmodels.sandbox.regression.tests.test_gmm_poisson import DATA
  from .results.results_discrete import RandHIE
  from .results import results_truncated
  from .results import results_truncated_st
label_desc: Use image node_id 1 for calling the TestTruncatedLFPoissonModel obj's underlying member method code with example usage: obj.setup_class(cls) without return types