code: def check_results(pandas):
      mod, res = get_dummy_mod(pandas=pandas)
  
      # Test fitted values
      assert_almost_equal(res.fittedvalues[2:], mod.endog[2:].squeeze())
  
      # Test residuals
      assert_almost_equal(res.resid[2:], np.zeros(mod.nobs - 2))
  
      # Test loglikelihood_burn
      assert_equal(res.loglikelihood_burn, 0)
  
imports: from statsmodels.compat.pandas import MONTH_END
  import os
  import re
  import warnings
  import numpy
  from numpy.testing import assert_, assert_allclose, assert_almost_equal, assert_equal, assert_raises
  import pandas
  import pytest
  from statsmodels.datasets import nile
  from statsmodels.tsa.statespace import kalman_filter, kalman_smoother, sarimax, varmax
  from statsmodels.tsa.statespace.mlemodel import MLEModel, MLEResultsWrapper
  from statsmodels.tsa.statespace.tests.results import results_sarimax, results_var_misc
label_desc: Use image node_id 13 for calling a global function with example usage: check_results(pandas) without return types