code: def test_predict_likelihood_parameters_wrong_args(self):
      m_deterministic = LinearRegressionModel(
          lags=2, output_chunk_length=2
      )
      m_proba_quantile1 = LinearRegressionModel(
          lags=2,
          output_chunk_length=2,
          likelihood="quantile",
          quantiles=[0.05, 0.5, 0.95],
      )
      m_proba_quantile2 = LinearRegressionModel(
          lags=3,
          output_chunk_length=3,
          likelihood="quantile",
          quantiles=[0.05, 0.5, 0.95],
      )
      m_proba_poisson = LinearRegressionModel(
          lags=2, output_chunk_length=2, likelihood="poisson"
      )
      # one model is not probabilistic
      naive_ensemble = NaiveEnsembleModel(
          [m_deterministic, m_proba_quantile1]
      )
      naive_ensemble.fit(self.series1 + self.series2)
      with pytest.raises(ValueError):
          naive_ensemble.predict(
              n=1, predict_likelihood_parameters=True
          )
  
      # one model has a different likelihood
      naive_ensemble = NaiveEnsembleModel(
          [m_proba_quantile1.untrained_model(), m_proba_poisson]
      )
      naive_ensemble.fit(self.series1 + self.series2)
      with pytest.raises(ValueError):
          naive_ensemble.predict(
              n=1, predict_likelihood_parameters=True
          )
  
      # n > shortest output_chunk_length
      naive_ensemble = NaiveEnsembleModel(
          [m_proba_quantile1.untrained_model(), m_proba_quantile2]
      )
      naive_ensemble.fit(self.series1 + self.series2)
      with pytest.raises(ValueError):
          naive_ensemble.predict(
              n=4, predict_likelihood_parameters=True
          )
  
imports: import numpy
  import pandas
  import pytest
  from darts import TimeSeries
  from darts.logging import get_logger
  from darts.models import ExponentialSmoothing, LinearRegressionModel, NaiveDrift, NaiveEnsembleModel, NaiveSeasonal, StatsForecastAutoARIMA, Theta
  from darts.tests.conftest import tfm_kwargs
  from darts.utils import timeseries_generation
label_desc: Use image node_id 10 for calling the TestEnsembleModels obj's underlying member method code with example usage: obj.test_predict_likelihood_parameters_wrong_args() without return types