code: def test_filter():
      endog = np.array([1.0, 2.0])
      mod = MLEModel(endog, **kwargs)
  
      # Test return of ssm object
      res = mod.filter([], return_ssm=True)
      assert_equal(isinstance(res, kalman_filter.FilterResults), True)
  
      # Test return of full results object
      res = mod.filter([])
      assert_equal(isinstance(res, MLEResultsWrapper), True)
      assert_equal(res.cov_type, "opg")
  
      # Test return of full results object, specific covariance type
      res = mod.filter([], cov_type="oim")
      assert_equal(isinstance(res, MLEResultsWrapper), True)
      assert_equal(res.cov_type, "oim")
  
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 11 for calling a global function with example usage: test_filter() without return types