code: def test_continuous_normal_ref(self):
      # test for normal reference rule of thumb with continuous data
      dens_nm = nparam.KDEMultivariateConditional(
          endog=[self.Italy_gdp],
          exog=[self.growth],
          dep_type="c",
          indep_type="c",
          bw="normal_reference",
      )
      sm_result = dens_nm.bw
      R_result = [1.283532, 0.01535401]
      # TODO: here we need a smaller tolerance.check!
      npt.assert_allclose(sm_result, R_result, atol=1e-1)
  
      # test default bandwidth method, should be normal_reference
      dens_nm2 = nparam.KDEMultivariateConditional(
          endog=[self.Italy_gdp],
          exog=[self.growth],
          dep_type="c",
          indep_type="c",
          bw=None,
      )
      assert_allclose(dens_nm2.bw, dens_nm.bw, rtol=1e-10)
      assert_equal(dens_nm2._bw_method, "normal_reference")
      # check repr works #3125
      repr(dens_nm2)
  
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 6 for calling the TestKDEMultivariateConditional obj's underlying member method code with example usage: obj.test_continuous_normal_ref() without return types