statsmodels.tsa.statespace.structural.UnobservedComponents.filter¶
-
UnobservedComponents.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)¶ 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.