code: def test_summary(reset_randomstate):
      # Smoke tests for summaries
      endog, _, _, _, _, _ = gen_dfm_data(k_endog=10, nobs=100)
  
      # Create the test Dynamic Factor MQ models
      mod_dfm = dynamic_factor_mq.DynamicFactorMQ(
          endog,
          factor_orders=1,
          standardize=False,
          idiosyncratic_ar1=False,
      )
      res_dfm = mod_dfm.smooth(mod_dfm.start_params)
      mod_dfm_ar1 = dynamic_factor_mq.DynamicFactorMQ(
          endog,
          factor_orders=1,
          standardize=False,
          idiosyncratic_ar1=True,
      )
      res_dfm_ar1 = mod_dfm_ar1.smooth(mod_dfm_ar1.start_params)
  
      mod_dfm.summary()
      assert_equal(str(mod_dfm), str(mod_dfm.summary()))
      res_dfm.summary()
      mod_dfm_ar1.summary()
      res_dfm_ar1.summary()
  
imports: from statsmodels.compat.pandas import MONTH_END, QUARTER_END, assert_frame_equal, assert_series_equal
  import numpy
  from numpy.testing import assert_, assert_allclose, assert_equal
  import pandas
  import pytest
  from statsmodels.regression.linear_model import OLS
  from statsmodels.tools import add_constant
  from statsmodels.tsa.statespace import dynamic_factor, dynamic_factor_mq, sarimax
  from statsmodels.tsa.statespace.tests import test_dynamic_factor_mq_monte_carlo
label_desc: Use image node_id 12 for calling a global function with example usage: test_summary(reset_randomstate) without return types