code: def test_exact_prediction_intervals(austourists_model_fit):
      fit = austourists_model_fit._results
  
      class DummyModel:
          def __init__(self, short_name):
              self.short_name = short_name
  
      # compare AAdN with AAN
      fit.damping_trend = 1 - 1e-3
      fit.model = DummyModel("AAdN")
      steps = 5
      s_AAdN = fit._relative_forecast_variance(steps)
      fit.model = DummyModel("AAN")
      s_AAN = fit._relative_forecast_variance(steps)
      assert_almost_equal(s_AAdN, s_AAN, 2)
  
      # compare AAdA with AAA
      fit.damping_trend = 1 - 1e-3
      fit.model = DummyModel("AAdA")
      steps = 5
      s_AAdA = fit._relative_forecast_variance(steps)
      fit.model = DummyModel("AAA")
      s_AAA = fit._relative_forecast_variance(steps)
      assert_almost_equal(s_AAdA, s_AAA, 2)
  
imports: from statsmodels.compat.pandas import QUARTER_END
  from statsmodels.compat.platform import PLATFORM_LINUX32, PLATFORM_WIN
  from itertools import product
  import json
  import pathlib
  import numpy
  from numpy.testing import assert_allclose, assert_almost_equal
  import pandas
  import pytest
  import scipy.stats
  from statsmodels.tsa.exponential_smoothing.ets import ETSModel
  import statsmodels.tsa.holtwinters
  import statsmodels.tsa.statespace.exponential_smoothing
label_desc: Use image node_id 39 for calling a global function with example usage: test_exact_prediction_intervals(austourists_model_fit) without return types