code: def test_SARIMAX_multiple_intervals_against_statsmodels():
      """Compares Sktime's and Statsmodel's SARIMAX.
  
      Notes
      -----
      * Predict confidence intervals using underlying estimator and the wrapper.
      * Predicts for multiple coverage values, viz. 70% and 80%.
      """
      from statsmodels.tsa.api import SARIMAX as _SARIMAX
  
      df = make_forecasting_problem()
  
      sktime_model = SARIMAX(
          order=(1, 0, 0), trend="t", seasonal_order=(1, 0, 0, 6)
      )
      sktime_model.fit(df)
      sktime_pred_int = sktime_model.predict_interval(
          df.index, coverage=[0.70, 0.80]
      )
      sktime_pred_int_70 = sktime_pred_int.xs((0, 0.70), axis="columns")
      sktime_pred_int_80 = sktime_pred_int.xs((0, 0.80), axis="columns")
  
      stats = _SARIMAX(
          endog=df,
          order=(1, 0, 0),
          trend="t",
          seasonal_order=(1, 0, 0, 6),
      )
      stats_fit = stats.fit()
      stats_pred_int_70 = stats_fit.get_prediction(
          df.index[0]
      ).conf_int(alpha=0.30)
      stats_pred_int_70.columns = ["lower", "upper"]
      stats_pred_int_80 = stats_fit.get_prediction(
          df.index[0]
      ).conf_int(alpha=0.20)
      stats_pred_int_80.columns = ["lower", "upper"]
  
      assert_frame_equal(sktime_pred_int_70, stats_pred_int_70)
      assert_frame_equal(sktime_pred_int_80, stats_pred_int_80)
  
file_path: sktime/sktime/forecasting/tests/test_sarimax.py
imports: import pytest
  from numpy.testing import assert_allclose
  from pandas.testing import assert_frame_equal
  from sktime.forecasting.sarimax import SARIMAX
  from sktime.tests.test_switch import run_test_for_class
  from sktime.utils._testing.forecasting import make_forecasting_problem
label_desc: Use image node_id 3 for calling a global function with example usage: test_SARIMAX_multiple_intervals_against_statsmodels() without return types