code: def test_vcomp_2(self):
      # Simulated data comparison to R
  
      np.random.seed(6241)
      n = 1600
      exog = np.random.normal(size=(n, 2))
      groups = np.kron(np.arange(n / 16), np.ones(16))
  
      # Build up the random error vector
      errors = 0
  
      # The random effects
      exog_re = np.random.normal(size=(n, 2))
      slopes = np.random.normal(size=(n // 16, 2))
      slopes = np.kron(slopes, np.ones((16, 1))) * exog_re
      errors += slopes.sum(1)
  
      # First variance component
      subgroups1 = np.kron(np.arange(n / 4), np.ones(4))
      errors += np.kron(2 * np.random.normal(size=n // 4), np.ones(4))
  
      # Second variance component
      subgroups2 = np.kron(np.arange(n / 2), np.ones(2))
      errors += np.kron(2 * np.random.normal(size=n // 2), np.ones(2))
  
      # iid errors
      errors += np.random.normal(size=n)
  
      endog = exog.sum(1) + errors
  
      df = pd.DataFrame(index=range(n))
      df["y"] = endog
      df["groups"] = groups
      df["x1"] = exog[:, 0]
      df["x2"] = exog[:, 1]
      df["z1"] = exog_re[:, 0]
      df["z2"] = exog_re[:, 1]
      df["v1"] = subgroups1
      df["v2"] = subgroups2
  
      # Equivalent model in R:
      # df.to_csv("tst.csv")
      # model = lmer(y ~ x1 + x2 + (0 + z1 + z2 | groups) + (1 | v1) + (1 |
      # v2), df)
  
      vcf = {"a": "0 + C(v1)", "b": "0 + C(v2)"}
      model1 = MixedLM.from_formula(
          "y ~ x1 + x2",
          groups=groups,
          re_formula="0+z1+z2",
          vc_formula=vcf,
          data=df,
      )
      result1 = model1.fit()
  
      # Compare to R
      assert_allclose(
          result1.fe_params, [0.16527, 0.99911, 0.96217], rtol=1e-4
      )
      assert_allclose(
          result1.cov_re, [[1.244, 0.146], [0.146, 1.371]], rtol=1e-3
      )
      assert_allclose(result1.vcomp, [4.024, 3.997], rtol=1e-3)
      assert_allclose(
          result1.bse.iloc[0:3], [0.12610, 0.03938, 0.03848], rtol=1e-3
      )
  
imports: from statsmodels.compat.platform import PLATFORM_OSX
  import os
  import csv
  import warnings
  import numpy
  import pandas
  from scipy import sparse
  import pytest
  from statsmodels.regression.mixed_linear_model import MixedLM, MixedLMParams, _smw_solver, _smw_logdet
  from numpy.testing import assert_almost_equal, assert_equal, assert_allclose, assert_
  from statsmodels.base import _penalties
  import statsmodels.tools.numdiff
  from .results import lme_r_results
label_desc: Use image node_id 6 for calling the TestMixedLM obj's underlying member method code with example usage: obj.test_vcomp_2() without return types