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.
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.
results : class, object, or {‘loglikelihood’}, optional
If a class which is a subclass of FilterResults, then that class is
instantiated and returned with the result of filtering. Classes
must subclass FilterResults.
If an object, then that object is updated with the new filtering
results.
If the string ‘loglikelihood’, then only the loglikelihood is
returned as an ndarray.
If None, then the default results object is updated with the
result of filtering.
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