code: def test_continuous_cvml_efficient(self):
      nobs = 400
      np.random.seed(12345)
      C1 = np.random.normal(size=(nobs,))
      C2 = np.random.normal(2, 1, size=(nobs,))
      Y = 0.3 + 1.2 * C1 - 0.9 * C2
  
      dens_efficient = nparam.KDEMultivariate(
          data=[Y, C1],
          var_type="cc",
          bw="cv_ml",
          defaults=nparam.EstimatorSettings(efficient=True, n_sub=100),
      )
      # dens = nparam.KDEMultivariate(data=[Y, C1], var_type='cc', bw='cv_ml',
      #                  defaults=nparam.EstimatorSettings(efficient=False))
      # bw = dens.bw
      bw = np.array([0.4471, 0.2861])
      npt.assert_allclose(bw, dens_efficient.bw, atol=0.1, rtol=0.2)
  
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 10 for calling the TestKDEMultivariate obj's underlying member method code with example usage: obj.test_continuous_cvml_efficient() without return types