code: def test_prediction_intervals_no_exog(
      alpha, coverage, fh_length, y_airlines
  ):
      """Test prediction intervals when no exogenous regressors are present."""
      fh = np.arange(fh_length) + 1
      forecaster = UnobservedComponents()
      forecaster.fit(y_airlines)
      quantiles_df = forecaster.predict_quantiles(fh=fh, alpha=alpha)
      intervals_df = forecaster.predict_interval(
          fh=fh, coverage=coverage
      )
      if isinstance(alpha, list):
          assert quantiles_df.shape == (fh_length, len(alpha))
      else:
          assert quantiles_df.shape == (fh_length, 1)
  
      if isinstance(coverage, list):
          assert intervals_df.shape == (fh_length, 2 * len(coverage))
      else:
          intervals_np = intervals_df.to_numpy().flatten()
          assert intervals_df.shape == (fh_length, 2)
          assert intervals_np[0] < intervals_np[1]
  
imports: import numpy
  import pandas
  import pytest
  from pandas.testing import assert_series_equal
  from sktime.datasets import load_airline, load_longley
  from sktime.forecasting.model_evaluation import evaluate
  from sktime.forecasting.structural import UnobservedComponents
  from sktime.split import SlidingWindowSplitter
  from sktime.utils.validation._dependencies import _check_soft_dependencies
label_desc: Use image node_id 6 for calling a global function with example usage: test_prediction_intervals_no_exog(alpha, coverage, fh_length, y_airlines) without return types