code: def test_pdf_mixeddata(self):
      dens = nparam.KDEMultivariateConditional(
          endog=[self.Italy_gdp],
          exog=[self.Italy_year],
          dep_type="c",
          indep_type="o",
          bw="cv_ls",
      )
      sm_result = np.squeeze(dens.pdf()[0:5])
      # R_result = [0.08469226, 0.01737731, 0.05679909, 0.09744726, 0.15086674]
      expected = [
          0.08592089,
          0.0193275,
          0.05310327,
          0.09642667,
          0.171954,
      ]
  
      ## CODE TO REPRODUCE IN R
      ## library(np)
      ## data (Italy)
      ## bw <- npcdensbw(formula =
      ## Italy$gdp[1:50]~ordered(Italy$year[1:50]),bwmethod='cv.ls')
      ## fhat <- fitted(npcdens(bws=bw))
      ## fhat[1:5]
      npt.assert_allclose(sm_result, expected, atol=0, rtol=1e-5)
  
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 5 for calling the TestKDEMultivariateConditional obj's underlying member method code with example usage: obj.test_pdf_mixeddata() without return types