code: def test_predict_dist_output_when_forecaster_is_LinearRegression_steps_is_2_in_sample_residuals_True_exog_and_transformer(
      level,
  ):
      """
      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. Single level.
      """
      forecaster = ForecasterAutoregMultiSeries(
          regressor=LinearRegression(),
          lags=3,
          transformer_series=StandardScaler(),
          transformer_exog=transformer_exog,
      )
  
      forecaster.fit(series=series, exog=exog)
      results = forecaster.predict_dist(
          steps=2,
          distribution=norm,
          levels=level,
          exog=exog_predict,
          n_boot=4,
          in_sample_residuals=True,
      )
  
      expected = pd.DataFrame(
          data=np.array(
              [[0.38172712, 0.13932345], [0.22554853, 0.16819172]]
          ),
          columns=["1_loc", "1_scale"],
          index=pd.RangeIndex(start=50, stop=52),
      )
  
      pd.testing.assert_frame_equal(results, expected)
  
file_path: skforecast/skforecast/ForecasterAutoregMultiSeries/tests/test_predict_dist.py
imports: import pytest
  import numpy
  import pandas
  from skforecast.ForecasterAutoregMultiSeries import ForecasterAutoregMultiSeries
  from scipy.stats import norm
  from sklearn.compose import ColumnTransformer
  from sklearn.preprocessing import StandardScaler
  from sklearn.preprocessing import OneHotEncoder
  from sklearn.linear_model import LinearRegression
  from .fixtures_ForecasterAutoregMultiSeries import series
  from .fixtures_ForecasterAutoregMultiSeries import exog
  from .fixtures_ForecasterAutoregMultiSeries 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(level) without return types