code: def test_varmax(missing, periods):
      endog = np.array(
          [
              [0.5, 1.2, -0.2, 0.3, -0.1, 0.4, 1.4, 0.9],
              [-0.2, -0.3, -0.1, 0.1, 0.01, 0.05, -0.13, -0.2],
          ]
      ).T
      exog = np.ones_like(endog[:, 0])
      if missing == "init":
          endog[0:2, :] = np.nan
      elif missing == "mixed":
          endog[2:4, 0] = np.nan
          endog[3:6, 1] = np.nan
      elif missing == "all":
          endog[:] = np.nan
  
      mod = varmax.VARMAX(endog, order=(1, 0), trend="t", exog=exog)
      mod.update(
          [0.1, -0.1, 0.5, 0.1, -0.05, 0.2, 0.4, 0.25, 1.2, 0.4, 2.3]
      )
      check_filter_output(mod, periods, atol=1e-12)
      check_smoother_output(mod, periods)
  
file_path: statsmodels/statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py
imports: import numpy
  import pytest
  from statsmodels.tsa.statespace import mlemodel, sarimax, structural, varmax, dynamic_factor
  from statsmodels.tsa.statespace.tests.test_impulse_responses import TVSS
  from numpy.testing import assert_allclose
label_desc: Use image node_id 10 for calling a global function with example usage: test_varmax(missing, periods) without return types