code: def test_pdf_continuous(self):
      # Hardcode here the bw that will be calculated is we had used
      # ``bw='cv_ml'``.  That calculation is slow, and tested in other tests.
      bw_cv_ml = np.array(
          [0.010043, 12095254.7]
      )  # TODO: odd numbers (?!)
      dens = nparam.KDEMultivariateConditional(
          endog=[self.growth],
          exog=[self.Italy_gdp],
          dep_type="c",
          indep_type="c",
          bw=bw_cv_ml,
      )
      sm_result = np.squeeze(dens.pdf()[0:5])
      R_result = [11.97964, 12.73290, 13.23037, 13.46438, 12.22779]
      npt.assert_allclose(sm_result, R_result, atol=1e-3)
  
imports: import numpy
  import numpy.testing
  import pytest
  from numpy.testing import assert_allclose, assert_equal
  import statsmodels.api
label_desc: Use image node_id 4 for calling the TestKDEMultivariateConditional obj's underlying member method code with example usage: obj.test_pdf_continuous() without return types