code: def test_basic(self):
      pt = self.res2.params_table[:, :6].T
      params2, bse2, tvalues2, pvalues2, ci_low, ci_upp = pt
      assert_allclose(self.res1.params, params2, rtol=2e-6)
  
      # TODO tgmixed seems to use scale from initial OLS, not from final res
      # np.sqrt(res.scale / res_ols.scale)
      # see below mse_resid which is equal to scale
      corr_fact = 0.9836026210570028
      corr_fact = 0.97376865041463734
      corr_fact = 1
      assert_allclose(self.res1.bse / corr_fact, bse2, rtol=2e-6)
      assert_allclose(
          self.res1.tvalues * corr_fact, tvalues2, rtol=2e-6
      )
      # pvalues are very small
      # assert_allclose(self.res1.pvalues, pvalues2, atol=2e-6)
      # assert_allclose(self.res1.pvalues, pvalues2, rtol=0.7)
      ci = self.res1.conf_int()
      # not scale corrected
      assert_allclose(ci[:, 0], ci_low, rtol=0.01)
      assert_allclose(ci[:, 1], ci_upp, rtol=0.01)
      assert_allclose(self.res1.rsquared, self.res2.r2, rtol=2e-6)
  
      # Note: tgmixed is using k_exog for df_resid
      corr_fact = self.res1.df_resid / self.res2.df_r
      assert_allclose(
          np.sqrt(self.res1.mse_resid * corr_fact),
          self.res2.rmse,
          rtol=2e-6,
      )
  
      assert_allclose(
          self.res1.fittedvalues,
          self.res_predict["fittedvalues"],
          atol=5e7,
      )
  
imports: import os
  import numpy
  import pandas
  import pytest
  from numpy.testing import assert_allclose
  from statsmodels.regression.linear_model import OLS, GLS
  from statsmodels.sandbox.regression.penalized import TheilGLS
label_desc: Use image node_id 2 for calling the TestTheilTextile obj's underlying member method code with example usage: obj.test_basic() without return types