code: def test_insuficient_oos(data):
      x = np.asarray(data.x)
      res = ARDL(data.y, 4, fixed=x).fit()
      with pytest.raises(
          ValueError, match="fixed_oos must be provided"
      ):
          res.forecast(12)
      with pytest.raises(
          ValueError, match="fixed_oos must have at least"
      ):
          res.forecast(12, fixed=x[:11])
      res = ARDL(data.y, 4, data.x, 3, causal=True).fit()
      with pytest.raises(ValueError, match="exog_oos must be provided"):
          res.forecast(12)
      with pytest.raises(
          ValueError, match="exog_oos must have at least"
      ):
          res.forecast(12, exog=data.x.iloc[-10:])
  
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 41 for calling a global function with example usage: test_insuficient_oos(data) without return types