code: def test_predict_likelihood_parameters_univariate_regression_ensemble(
      self,
  ):
      quantiles = [0.05, 0.5, 0.95]
      ensemble = RegressionEnsembleModel(
          [
              self.get_probabilistic_global_model(
                  lags=2, output_chunk_length=2, quantiles=quantiles
              ),
              self.get_probabilistic_global_model(
                  lags=3, output_chunk_length=3, quantiles=quantiles
              ),
          ],
          regression_train_n_points=10,
          regression_model=LinearRegressionModel(
              lags_future_covariates=[0],
              output_chunk_length=4,
              likelihood="quantile",
              quantiles=quantiles,
          ),
      )
      ensemble.fit(self.sine_series)
      pred_ens = ensemble.predict(
          n=4, predict_likelihood_parameters=True
      )
  
      assert all(
          pred_ens.components
          == ["sine_q0.05", "sine_q0.50", "sine_q0.95"]
      )
      assert all(
          pred_ens["sine_q0.05"].values()
          < pred_ens["sine_q0.50"].values()
      ) and all(
          pred_ens["sine_q0.50"].values()
          < pred_ens["sine_q0.95"].values()
      )
  
imports: from typing import List, Union
  import numpy
  import pandas
  import pytest
  from sklearn.ensemble import RandomForestRegressor
  from sklearn.linear_model import LinearRegression
  from darts import TimeSeries
  from darts.logging import get_logger
  from darts.metrics import mape, rmse
  from darts.models import LinearRegressionModel, NaiveDrift, NaiveSeasonal, RandomForest, RegressionEnsembleModel, RegressionModel, Theta
  from darts.tests.conftest import tfm_kwargs
  from darts.tests.models.forecasting.test_ensemble_models import _make_ts
  from darts.tests.models.forecasting.test_regression_models import train_test_split
  from darts.utils import timeseries_generation
label_desc: Use image node_id 24 for calling the TestRegressionEnsembleModels obj's underlying member method code with example usage: obj.test_predict_likelihood_parameters_univariate_regression_ensemble() without return types