code: def test_var_ct_as_exog1():
      test = "ct"
  
      # VAR(2), no built-in trend, constant and time trend as exog
      # Here we start the time-trend at 1 and so we can compare to the built-in
      # trend results "res_ct"
      results = results_var_R.res_ct
      mod = varmax.VARMAX(
          endog,
          order=(2, 0),
          exog=exog1[:, :2],
          trend="n",
          loglikelihood_burn=2,
      )
      # Since the params were given for the built-in trend case, we need to
      # re-order them
      params = results["params"]
      params = np.r_[params[6:-6], params[:6], params[-6:]]
      res = mod.smooth(params)
  
      assert_allclose(res.llf, results["llf"])
  
      # Forecast
      columns = [
          "{}.fcast.{}.fcst".format(test, name)
          for name in endog.columns
      ]
      assert_allclose(
          res.forecast(10, exog=exog1_fcast[:, :2]),
          results_var_R_output[columns].iloc[:10],
      )
  
      # IRF
      check_irf(test, mod, results, params)
  
file_path: statsmodels/statsmodels/tsa/statespace/tests/test_var.py
imports: import os
  import numpy
  from numpy.testing import assert_allclose
  import pandas
  from statsmodels.tsa.statespace import varmax
  from .results import results_var_R
label_desc: Use image node_id 6 for calling a global function with example usage: test_var_ct_as_exog1() without return types