code: def test_get_prediction(sunspots):
      # GH7309
      stlf_model = STLForecast(
          sunspots,
          model=ARIMA,
          model_kwargs={"order": (2, 2, 0)},
          period=11,
      )
      stlf_res = stlf_model.fit()
      pred = stlf_res.get_prediction()
      assert pred.predicted_mean.shape == (309,)
      assert pred.var_pred_mean.shape == (309,)
  
imports: from statsmodels.compat.pandas import MONTH_END
  import numpy
  from numpy.testing import assert_allclose
  import pandas
  import pytest
  import statsmodels.datasets
  from statsmodels.tsa.ar_model import AutoReg
  from statsmodels.tsa.arima.model import ARIMA
  from statsmodels.tsa.base.prediction import PredictionResults
  from statsmodels.tsa.deterministic import Fourier
  from statsmodels.tsa.exponential_smoothing.ets import ETSModel
  from statsmodels.tsa.forecasting.stl import STLForecast
  from statsmodels.tsa.seasonal import STL, DecomposeResult
  from statsmodels.tsa.statespace.exponential_smoothing import ExponentialSmoothing
label_desc: Use image node_id 7 for calling a global function with example usage: test_get_prediction(sunspots) without return types