code: def setup_class(cls):
      nobs = 2000
      exog = np.column_stack((np.ones(nobs), np.linspace(0, 3, nobs)))
      y_fake = np.arange(nobs) // (
          nobs / 3
      )  # need some zeros and non-zeros
  
      # get predicted probabilities for model
      mod = HurdleCountModel(
          y_fake, exog, dist="negbin", zerodist="negbin"
      )
      p_dgp = np.array([-0.4, 2, 0.5, 0.2, 0.5, 0.5])
      probs = mod.predict(p_dgp, which="prob", y_values=np.arange(50))
      cdf = probs.cumsum(1)
      n = cdf.shape[0]
      cdf = np.column_stack((cdf, np.ones(n)))
  
      # simulate data,
      # cooked example that doesn't have identification problems
      rng = np.random.default_rng(987456348)
      u = rng.random((n, 1))
      endog = np.argmin(cdf < u, axis=1)
  
      mod_hnb = HurdleCountModel(
          endog, exog, dist="negbin", zerodist="negbin"
      )
      cls.res1 = mod_hnb.fit(maxiter=300)
  
      df_null = 4
      cls.res2 = Holder(
          nobs=nobs,
          k_params=6,
          df_model=2,
          df_null=df_null,
          df_resid=nobs - 6,
          k_extra=df_null - 1,
          exog_names=[
              "zm_const",
              "zm_x1",
              "zm_alpha",
              "const",
              "x1",
              "alpha",
          ],
      )
  
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 TestHurdleNegbinSimulated obj's underlying member method code with example usage: obj.setup_class(cls) without return types