statsmodels.tsa.statespace.mlemodel.MLEModel.filter

MLEModel.filter(params, transformed=True, includes_fixed=False, complex_step=False, cov_type=None, cov_kwds=None, return_ssm=False, results_class=None, results_wrapper_class=None, low_memory=False, **kwargs)[source]

Kalman filtering

Parameters:

  • params (array_like) – Array of parameters at which to evaluate the loglikelihood function.

  • transformed (bool, optional) – Whether or not params is already transformed. Default is True.

  • return_ssm (bool,optional) – Whether or not to return only the state space output or a full results object. Default is to return a full results object.

  • cov_type (str, optional) – See MLEResults.fit for a description of covariance matrix types for results object.

  • cov_kwds (dict or None, optional) – See MLEResults.get_robustcov_results for a description required keywords for alternative covariance estimators

  • low_memory (bool, optional) – If set to True, techniques are applied to substantially reduce memory usage. If used, some features of the results object will not be available (including in-sample prediction), although out-of-sample forecasting is possible. Default is False.

  • **kwargs – Additional keyword arguments to pass to the Kalman filter. See KalmanFilter.filter for more details.