class_docstr: Tests for simulation smoothing values in a couple of special cases of
  variates. Both computed values and KFAS values are used for comparison
  against the simulation smoother output.
class_docstr_tok: ["Tests","for","simulation","smoothing","values","in","a","couple","of","special","cases","of","variates",".","Both","computed","values","and","KFAS","values","are","used","for","comparison","against","the","simulation","smoother","output","."]
code: def test_simulate_0(self):
      n = 10
  
      # Test with all inputs as zeros
      measurement_shocks = np.zeros((n, self.model.k_endog))
      state_shocks = np.zeros((n, self.model.ssm.k_posdef))
      initial_state = np.zeros(self.model.k_states)
      obs, states = self.model.ssm.simulate(
          nsimulations=n,
          measurement_shocks=measurement_shocks,
          state_shocks=state_shocks,
          initial_state=initial_state,
      )
  
      assert_allclose(obs, np.zeros((n, self.model.k_endog)))
      assert_allclose(states, np.zeros((n, self.model.k_states)))
  
imports: import os
  import numpy
  import pandas
  from numpy.testing import assert_allclose, assert_equal
  import pytest
  from statsmodels import datasets
  from statsmodels.tsa.statespace import mlemodel, sarimax, structural, varmax
  from statsmodels.tsa.statespace.simulation_smoother import SIMULATION_STATE, SIMULATION_DISTURBANCE, SIMULATION_ALL
label_desc: Use image node_id 3 for calling the MultivariateVARKnown obj's underlying member method code with example usage: obj.test_simulate_0() without return types