DynamicFactorMQ.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.


Array of parameters at which to evaluate the loglikelihood function.

transformedbool, optional

Whether or not params is already transformed. Default is True.


Whether or not to return only the state space output or a full results object. Default is to return a full results object.

cov_typestr, optional

See for a description of covariance matrix types for results object. Default is ‘none’.

cov_kwdsdict or None, 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.


Additional keyword arguments to pass to the Kalman filter. See KalmanFilter.filter for more details.