code: def test_continuous_lc_aic(self):
      nobs = 200
      np.random.seed(1234)
      C1 = np.random.normal(size=(nobs,))
      C2 = np.random.normal(2, 1, size=(nobs,))
      noise = np.random.normal(size=(nobs,))
      Y = 0.3 + 1.2 * C1 - 0.9 * C2 + noise
      # self.write2file('RegData.csv', (Y, C1, C2))
  
      # CODE TO PRODUCE BANDWIDTH ESTIMATION IN R
      # library(np)
      # data <- read.csv('RegData.csv', header=FALSE)
      # bw <- npregbw(formula=data$V1 ~ data$V2 + data$V3,
      #                bwmethod='cv.aic', regtype='lc')
      model = nparam.KernelReg(
          endog=[Y],
          exog=[C1, C2],
          reg_type="lc",
          var_type="cc",
          bw="aic",
      )
      # R_bw = [0.4017893, 0.4943397]  # Bandwidth obtained in R
      bw_expected = [0.3987821, 0.50933458]
      npt.assert_allclose(model.bw, bw_expected, rtol=1e-3)
  
imports: import pytest
  import numpy
  import numpy.testing
  import statsmodels.api
label_desc: Use image node_id 9 for calling the TestKernelReg obj's underlying member method code with example usage: obj.test_continuous_lc_aic() without return types