code: def setup_class(cls):
      endog = DATA["docvis"]
      exog_names = ["aget", "totchr", "const"]
      exog = DATA[exog_names]
      cls.res1 = TruncatedLFPoisson(endog, exog).fit(
          method="bfgs", maxiter=300
      )
      cls.res2 = results_ts.results_trunc_poisson
  
      mod_offset = TruncatedLFPoisson(endog, exog, offset=DATA["aget"])
      cls.res_offset = mod_offset.fit(method="bfgs", maxiter=300)
  
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 TestTruncatedLFPoissonSt obj's underlying member method code with example usage: obj.setup_class(cls) without return types