code: def test_predict_interval_output_when_regressor_is_LinearRegression_with_transform_y():
      """
      Test predict output when using LinearRegression as regressor and StandardScaler.
      """
      y = pd.Series(
          np.array(
              [
                  -0.59,
                  0.02,
                  -0.9,
                  1.09,
                  -3.61,
                  0.72,
                  -0.11,
                  -0.4,
                  0.49,
                  0.67,
                  0.54,
                  -0.17,
                  0.54,
                  1.49,
                  -2.26,
                  -0.41,
                  -0.64,
                  -0.8,
                  -0.61,
                  -0.88,
              ]
          )
      )
      transformer_y = StandardScaler()
      forecaster = ForecasterAutoregCustom(
          regressor=LinearRegression(),
          fun_predictors=create_predictors,
          window_size=5,
          transformer_y=transformer_y,
      )
      forecaster.fit(y=y)
      predictions = forecaster.predict_interval(steps=5)
      expected = pd.DataFrame(
          data=np.array(
              [
                  [-0.1578203, -2.02104471, 1.55076389],
                  [-0.18459942, -1.85211385, 1.49693466],
                  [-0.13711051, -1.82918043, 1.37837389],
                  [-0.01966358, -1.7522189, 1.31940346],
                  [-0.03228613, -1.77074022, 1.56056698],
              ]
          ),
          index=pd.RangeIndex(start=20, stop=25, step=1),
          columns=["pred", "lower_bound", "upper_bound"],
      )
  
      pd.testing.assert_frame_equal(predictions, expected)
  
file_path: skforecast/skforecast/ForecasterAutoregCustom/tests/test_predict_interval.py
imports: import re
  import pytest
  import numpy
  import pandas
  from skforecast.ForecasterAutoregCustom import ForecasterAutoregCustom
  from sklearn.compose import ColumnTransformer
  from sklearn.preprocessing import StandardScaler
  from sklearn.preprocessing import OneHotEncoder
  from sklearn.linear_model import LinearRegression
label_desc: Use image node_id 6 for calling a global function with example usage: test_predict_interval_output_when_regressor_is_LinearRegression_with_transform_y() without return types