code: def test_transform():
      # The transforms in MLEModel are noops
      mod = MLEModel([1, 2], **kwargs)
  
      # Test direct transform, untransform
      assert_allclose(mod.transform_params([2, 3]), [2, 3])
      assert_allclose(mod.untransform_params([2, 3]), [2, 3])
  
      # Smoke test for transformation in `filter`, `update`, `loglike`,
      # `loglikeobs`
      mod.filter([], transformed=False)
      mod.update([], transformed=False)
      mod.loglike([], transformed=False)
      mod.loglikeobs([], transformed=False)
  
      # Note that mod is an SARIMAX instance, and the two parameters are
      # variances
      mod, _ = get_dummy_mod(fit=False)
  
      # Test direct transform, untransform
      assert_allclose(mod.transform_params([2, 3]), [4, 9])
      assert_allclose(mod.untransform_params([4, 9]), [2, 3])
  
      # Test transformation in `filter`
      res = mod.filter([2, 3], transformed=True)
      assert_allclose(res.params, [2, 3])
  
      res = mod.filter([2, 3], transformed=False)
      assert_allclose(res.params, [4, 9])
  
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 10 for calling a global function with example usage: test_transform() without return types