code: def test_concentrated_predict_sarimax():
      # Note: we will not use the "concentrate_scale" option to SARIMAX for this
      # test, which is a lower-level test of the Kalman filter using the SARIMAX
      # model as an example
      nobs = 30
      np.random.seed(28953)
      endog = np.random.normal(size=nobs)
  
      # Typical model
      out = get_sarimax_models(endog)
      assert_allclose(out.res_conc.predict(), out.res_orig.predict())
      assert_allclose(
          out.res_conc.forecast(5), out.res_orig.forecast(5)
      )
      assert_allclose(
          out.res_conc.predict(start=0, end=45, dynamic=10),
          out.res_orig.predict(start=0, end=45, dynamic=10),
      )
  
file_path: statsmodels/statsmodels/tsa/statespace/tests/test_concentrated.py
imports: import numpy
  import pandas
  from statsmodels.tools.tools import Bunch
  from .results import results_varmax
  from statsmodels.tsa.statespace import sarimax, varmax
  from numpy.testing import assert_raises, assert_allclose
label_desc: Use image node_id 3 for calling a global function with example usage: test_concentrated_predict_sarimax() without return types