code: def test_uecm_ci_repr(use_numpy, use_t):
      y = dane_data.lrm
      x = dane_data[["lry", "ibo", "ide"]]
      if use_numpy:
          y = np.asarray(y)
          x = np.asarray(x)
      mod = UECM(y, 3, x, 3)
      res = mod.fit(use_t=use_t)
      if use_numpy:
          ci_params = res.params[:5].copy()
          ci_params /= ci_params[1]
      else:
          ci_params = res.params.iloc[:5].copy()
          ci_params /= ci_params["lrm.L1"]
      assert_allclose(res.ci_params, ci_params)
      assert res.ci_bse.shape == (5,)
      assert res.ci_tvalues.shape == (5,)
      assert res.ci_pvalues.shape == (5,)
      assert "Cointegrating Vector" in str(res.ci_summary())
      assert res.ci_conf_int().shape == (5, 2)
      assert res.ci_cov_params().shape == (5, 5)
      assert res.ci_resids.shape == dane_data.lrm.shape
  
imports: from typing import NamedTuple
  import numpy
  from numpy.testing import assert_allclose
  import pandas
  from pandas.testing import assert_index_equal
  import pytest
  from statsmodels.datasets import danish_data
  from statsmodels.iolib.summary import Summary
  from statsmodels.tools.sm_exceptions import SpecificationWarning
  from statsmodels.tsa.ar_model import AutoReg
  from statsmodels.tsa.ardl.model import ARDL, UECM, ARDLResults, ardl_select_order
  from statsmodels.tsa.deterministic import DeterministicProcess
label_desc: Use image node_id 50 for calling a global function with example usage: test_uecm_ci_repr(use_numpy, use_t) without return types