code: def test_low_memory():
      # Basic test that the low_memory option is working
      endog = dta["infl"].iloc[:50]
  
      mod = ARIMA(endog, order=(1, 0, 0), concentrate_scale=True)
      res1 = mod.fit()
      res2 = mod.fit(low_memory=True)
  
      # Check that the models produce the same results
      assert_allclose(res2.params, res1.params)
      assert_allclose(res2.llf, res1.llf)
  
      # Check that the model's basic memory conservation option was not changed
      assert_equal(mod.ssm.memory_conserve, 0)
  
      # Check that low memory was actually used (just check a couple)
      assert_(res2.llf_obs is None)
      assert_(res2.predicted_state is None)
      assert_(res2.filtered_state is None)
      assert_(res2.smoothed_state is None)
  
imports: from statsmodels.compat.platform import PLATFORM_WIN32
  import io
  import numpy
  import pandas
  import pytest
  from numpy.testing import assert_equal, assert_allclose, assert_raises, assert_
  from statsmodels.datasets import macrodata
  from statsmodels.tsa.arima.model import ARIMA
  from statsmodels.tsa.arima.estimators.yule_walker import yule_walker
  from statsmodels.tsa.arima.estimators.burg import burg
  from statsmodels.tsa.arima.estimators.hannan_rissanen import hannan_rissanen
  from statsmodels.tsa.arima.estimators.innovations import innovations, innovations_mle
  from statsmodels.tsa.arima.estimators.statespace import statespace
label_desc: Use image node_id 9 for calling a global function with example usage: test_low_memory() without return types