code: def test_hannan_rissanen_with_fixed_params(
      ar_order, ma_order, fixed_params
  ):
      # Test for basic uses of Hannan-Rissanen estimation with fixed parameters
      endog = dta["infl"].diff().iloc[1:101]
  
      desired_p, _ = hannan_rissanen(
          endog,
          ar_order=ar_order,
          ma_order=ma_order,
          demean=False,
          fixed_params=fixed_params,
      )
      # no constant or trend (since constant or trend would imply GLS estimation)
      mod = ARIMA(
          endog,
          order=(ar_order, 0, ma_order),
          trend="n",
          enforce_stationarity=False,
          enforce_invertibility=False,
      )
      with mod.fix_params(fixed_params):
          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 21 for calling a global function with example usage: test_hannan_rissanen_with_fixed_params(ar_order, ma_order, fixed_params) without return types