code: def setup_class(cls):
      path = os.path.join(
          current_path, "results", "results_predict_rgnp.csv"
      )
      results = pd.read_csv(path)
  
      true = {
          "params": np.r_[
              0.3812383,
              0.3564492,
              -0.0055216,
              1.195482,
              0.6677098**2,
              0.3710719,
              0.4621503,
              0.7002937,
              -0.3206652,
          ],
          "llf": -179.32354,
          "llf_fit": -179.38684,
          "llf_fit_em": -184.99606,
          "bse_oim": np.r_[
              0.1424841,
              0.0994742,
              0.2057086,
              0.1225987,
              np.nan,
              0.1754383,
              0.1652473,
              0.187409,
              0.1295937,
          ],
          "smoothed0": results.iloc[3:]["switchar2_sm1"],
          "smoothed1": results.iloc[3:]["switchar2_sm2"],
          "predict0": results.iloc[3:]["switchar2_yhat1"],
          "predict1": results.iloc[3:]["switchar2_yhat2"],
          "predict_predicted": results.iloc[3:]["switchar2_pyhat"],
          "predict_filtered": results.iloc[3:]["switchar2_fyhat"],
          "predict_smoothed": results.iloc[3:]["switchar2_syhat"],
      }
      super().setup_class(true, rgnp, k_regimes=2, order=2)
  
imports: import warnings
  import os
  import numpy
  from numpy.testing import assert_equal, assert_allclose
  import pandas
  import pytest
  from statsmodels.tools import add_constant
  from statsmodels.tsa.regime_switching import markov_autoregression
label_desc: Use image node_id 1 for calling the TestHamiltonAR2Switch obj's underlying member method code with example usage: obj.setup_class(cls) without return types