code: def check_itsmr(lake):
      # Test against R itsmr::burg; see results/results_burg.R
      res, _ = burg(lake, 10, demean=True)
      desired_ar_params = [
          1.05853631096,
          -0.32639150878,
          0.04784765122,
          0.02620476111,
          0.04444511374,
          -0.04134010262,
          0.02251178970,
          -0.01427524694,
          0.22223486915,
          -0.20935524387,
      ]
      assert_allclose(res.ar_params, desired_ar_params)
  
      # itsmr always returns the innovations algorithm estimate of sigma2,
      # whereas we return Burg's estimate
      u, v = arma_innovations(
          np.array(lake) - np.mean(lake),
          ar_params=res.ar_params,
          sigma2=1,
      )
      desired_sigma2 = 0.4458956354
      assert_allclose(np.sum(u**2 / v) / len(u), desired_sigma2)
  
file_path: statsmodels/statsmodels/tsa/arima/estimators/tests/test_burg.py
imports: import numpy
  import pytest
  from numpy.testing import assert_allclose, assert_equal, assert_raises
  from statsmodels.tsa.innovations.arma_innovations import arma_innovations
  from statsmodels.tsa.arima.datasets.brockwell_davis_2002 import dowj, lake
  from statsmodels.tsa.arima.estimators.burg import burg
label_desc: Use image node_id 3 for calling a global function with example usage: check_itsmr(lake) without return types