code: def test_var(self):
      v = self.res.predict(which="var").mean()
      assert_allclose(v, self.endog.var(), atol=2e-1, rtol=2e-1)
      return
      assert_allclose(
          (
              self.res.predict().mean()
              * self.res._dispersion_factor.mean()
          ),
          self.endog.var(),
          atol=5e-2,
          rtol=5e-2,
      )
  
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 3 for calling the TestTruncatedLFPoisson_predict obj's underlying member method code with example usage: obj.test_var() without return types