code: def _return_model_names_for_plots_stats():
      """Returns models to be used for testing plots. Needs
      - 1 model that has prediction interval ("theta")
      - 1 model that does not have prediction interval ("lr_cds_dt")
      - 1 model that has in-sample forecasts ("theta")
      - 1 model that does not have in-sample forecasts ("lr_cds_dt")
      """
      model_names = ["theta", "lr_cds_dt"]
      return model_names
  
imports: import random
  import numpy
  import pandas
  from pandas.testing import assert_frame_equal
  from sktime.forecasting.base import ForecastingHorizon
  from pycaret.containers.models.time_series import get_all_model_containers
  from pycaret.datasets import get_data
  from pycaret.time_series import TSForecastingExperiment
  from pycaret.utils.time_series import SeasonalPeriod
label_desc: Use image node_id 15 for calling a global function with example usage: _return_model_names_for_plots_stats() and returns: model_names