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:
- paramsarray_like
Array of parameters at which to evaluate the loglikelihood function.
- transformedbool,
optional
Whether or not params is already transformed. Default is True.
- return_ssmbool,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
orNone
,optional
See MLEResults.get_robustcov_results for a description required keywords for alternative covariance estimators
- low_memorybool,
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.