code: def test_predict_dist_output_when_forecaster_is_LinearRegression_steps_is_2_in_sample_residuals_False_exog_and_transformer():
      """
      Test output of predict_dist when regressor is LinearRegression,
      2 steps are predicted, using out-sample residuals, exog is included and both
      inputs are transformed.
      """
      forecaster = ForecasterAutoreg(
          regressor=LinearRegression(),
          lags=3,
          transformer_y=StandardScaler(),
          transformer_exog=StandardScaler(),
      )
  
      forecaster.fit(y=y, exog=exog)
      forecaster.out_sample_residuals = forecaster.in_sample_residuals
      results = forecaster.predict_dist(
          steps=2,
          exog=exog_predict,
          distribution=norm,
          n_boot=4,
          in_sample_residuals=False,
      )
  
      expected = pd.DataFrame(
          data=np.array(
              [[0.52256427, 0.123189], [0.11121952, 0.17472563]]
          ),
          columns=["loc", "scale"],
          index=pd.RangeIndex(start=50, stop=52),
      )
  
      pd.testing.assert_frame_equal(expected, results)
  
file_path: skforecast/skforecast/ForecasterAutoreg/tests/test_predict_dist.py
imports: import numpy
  import pandas
  from skforecast.ForecasterAutoreg import ForecasterAutoreg
  from sklearn.linear_model import LinearRegression
  from sklearn.preprocessing import StandardScaler
  from scipy.stats import norm
  from .fixtures_ForecasterAutoreg import y
  from .fixtures_ForecasterAutoreg import exog
  from .fixtures_ForecasterAutoreg import exog_predict
label_desc: Use image node_id 2 for calling a global function with example usage: test_predict_dist_output_when_forecaster_is_LinearRegression_steps_is_2_in_sample_residuals_False_exog_and_transformer() without return types