class_docstr: Results from applying the Kalman smoother and/or filter to a state space
  model.
  
  Parameters
  ----------
  model : Representation
      A Statespace representation
  simulation_smoother : {{prefix}}SimulationSmoother object
      The Cython simulation smoother object with which to simulation smooth.
  random_state : {None, int, Generator, RandomState}, optional
      If `seed` is None (or `np.random`), the `numpy.random.RandomState`
      singleton is used.
      If `seed` is an int, a new ``numpy.random.RandomState`` instance
      is used, seeded with `seed`.
      If `seed` is already a ``numpy.random.Generator`` or
      ``numpy.random.RandomState`` instance then that instance is used.
  
  Attributes
  ----------
  model : Representation
      A Statespace representation
  dtype : dtype
      Datatype of representation matrices
  prefix : str
      BLAS prefix of representation matrices
  simulation_output : int
      Bitmask controlling simulation output.
  simulate_state : bool
      Flag for if the state is included in simulation output.
  simulate_disturbance : bool
      Flag for if the state and observation disturbances are included in
      simulation output.
  simulate_all : bool
      Flag for if simulation output should include everything.
  generated_measurement_disturbance : ndarray
      Measurement disturbance variates used to genereate the observation
      vector.
  generated_state_disturbance : ndarray
      State disturbance variates used to genereate the state and
      observation vectors.
  generated_obs : ndarray
      Generated observation vector produced as a byproduct of simulation
      smoothing.
  generated_state : ndarray
      Generated state vector produced as a byproduct of simulation smoothing.
  simulated_state : ndarray
      Simulated state.
  simulated_measurement_disturbance : ndarray
      Simulated measurement disturbance.
  simulated_state_disturbance : ndarray
      Simulated state disturbance.
code: def simulate_state(self, value):
      if bool(value):
          self.simulation_output = (
              self.simulation_output | SIMULATION_STATE
          )
      else:
          self.simulation_output = (
              self.simulation_output & ~SIMULATION_STATE
          )
  
imports: import numbers
  import warnings
  import numpy
  from .kalman_smoother import KalmanSmoother
  from .cfa_simulation_smoother import CFASimulationSmoother
  from .None import tools
label_desc: Use image node_id 5 for calling the SimulationSmoothResults obj's underlying member method code with example usage: obj.simulate_state(value) without return types