code: def test_predict_interval_output_when_forecaster_is_LinearRegression_steps_is_2_in_sample_residuals_is_True():
      """
      Test output when regressor is LinearRegression and two step ahead is predicted
      using in sample residuals.
      """
      forecaster = ForecasterAutoregCustom(
          regressor=LinearRegression(),
          fun_predictors=create_predictors,
          window_size=5,
      )
      forecaster.fit(y=pd.Series(np.arange(10)))
      forecaster.in_sample_residuals = np.full_like(
          forecaster.in_sample_residuals, fill_value=10
      )
      expected = pd.DataFrame(
          np.array([[10.0, 20.0, 20.0], [11.0, 23.0, 23.0]]),
          columns=["pred", "lower_bound", "upper_bound"],
          index=pd.RangeIndex(start=10, stop=12, step=1),
      )
      results = forecaster.predict_interval(
          steps=2, in_sample_residuals=True, n_boot=2
      )
      pd.testing.assert_frame_equal(results, 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 3 for calling a global function with example usage: test_predict_interval_output_when_forecaster_is_LinearRegression_steps_is_2_in_sample_residuals_is_True() without return types