KalmanSmoother.filter(filter_method=None, inversion_method=None, stability_method=None, conserve_memory=None, filter_timing=None, tolerance=None, loglikelihood_burn=None, complex_step=False)

Apply the Kalman filter to the statespace model.

  • filter_method (int, optional) – Determines which Kalman filter to use. Default is conventional.
  • inversion_method (int, optional) – Determines which inversion technique to use. Default is by Cholesky decomposition.
  • stability_method (int, optional) – Determines which numerical stability techniques to use. Default is to enforce symmetry of the predicted state covariance matrix.
  • conserve_memory (int, optional) – Determines what output from the filter to store. Default is to store everything.
  • filter_timing (int, optional) – Determines the timing convention of the filter. Default is that from Durbin and Koopman (2012), in which the filter is initialized with predicted values.
  • tolerance (float, optional) – The tolerance at which the Kalman filter determines convergence to steady-state. Default is 1e-19.
  • loglikelihood_burn (int, optional) – The number of initial periods during which the loglikelihood is not recorded. Default is 0.


This function by default does not compute variables required for smoothing.

© 2009–2012 Statsmodels Developers
© 2006–2008 Scipy Developers
© 2006 Jonathan E. Taylor
Licensed under the 3-clause BSD License.