# statsmodels.tsa.statespace.simulation_smoother.SimulationSmoother.filter¶

SimulationSmoother.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.

Parameters
filter_methodint, optional

Determines which Kalman filter to use. Default is conventional.

inversion_methodint, optional

Determines which inversion technique to use. Default is by Cholesky decomposition.

stability_methodint, optional

Determines which numerical stability techniques to use. Default is to enforce symmetry of the predicted state covariance matrix.

conserve_memoryint, optional

Determines what output from the filter to store. Default is to store everything.

filter_timingint, 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.

tolerancefloat, optional

The tolerance at which the Kalman filter determines convergence to steady-state. Default is 1e-19.

loglikelihood_burnint, optional

The number of initial periods during which the loglikelihood is not recorded. Default is 0.

Notes

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