code: def test_hannan_rissanen():
      # Test for basic use of Hannan-Rissanen estimation
      endog = dta["infl"].diff().iloc[1:101]
  
      # ARMA(1, 1), no trend (since trend would imply GLS estimation)
      desired_p, _ = hannan_rissanen(
          endog, ar_order=1, ma_order=1, demean=False
      )
      mod = ARIMA(endog, order=(1, 0, 1), trend="n")
      res = mod.fit(method="hannan_rissanen")
      assert_allclose(res.params, desired_p.params)
  
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 5 for calling a global function with example usage: test_hannan_rissanen() without return types