code: def test_predict_dist_output_when_forecaster_is_LinearRegression_steps_is_2_in_sample_residuals_True_exog_and_transformer():
      """
      Test output of predict_dist when regressor is LinearRegression,
      2 steps are predicted, using in-sample residuals, exog is included and both
      inputs are transformed.
      """
      forecaster = ForecasterAutoregDirect(
          regressor=LinearRegression(),
          steps=2,
          lags=3,
          transformer_y=StandardScaler(),
          transformer_exog=StandardScaler(),
      )
  
      forecaster.fit(y=y, exog=exog)
      results = forecaster.predict_dist(
          steps=2,
          exog=exog_predict,
          distribution=norm,
          n_boot=4,
          in_sample_residuals=True,
      )
      expected = pd.DataFrame(
          data=np.array(
              [[0.54274594, 0.20807726], [0.50255276, 0.21780292]]
          ),
          columns=["loc", "scale"],
          index=pd.RangeIndex(start=50, stop=52),
      )
  
      pd.testing.assert_frame_equal(expected, results)
  
file_path: skforecast/skforecast/ForecasterAutoregDirect/tests/test_predict_dist.py
imports: import numpy
  import pandas
  from skforecast.ForecasterAutoregDirect import ForecasterAutoregDirect
  from sklearn.linear_model import LinearRegression
  from sklearn.preprocessing import StandardScaler
  from scipy.stats import norm
  from .fixtures_ForecasterAutoregDirect import y
  from .fixtures_ForecasterAutoregDirect import exog
  from .fixtures_ForecasterAutoregDirect import exog_predict
label_desc: Use image node_id 1 for calling a global function with example usage: test_predict_dist_output_when_forecaster_is_LinearRegression_steps_is_2_in_sample_residuals_True_exog_and_transformer() without return types