statsmodels.tsa.regime_switching.markov_autoregression.MarkovAutoregression.smooth

MarkovAutoregression.smooth(params, transformed=True, cov_type=None, cov_kwds=None, return_raw=False, results_class=None, results_wrapper_class=None)

Apply the Kim smoother and Hamilton filter

Parameters:
  • params (array_like) – Array of parameters at which to perform filtering.
  • transformed (boolean, optional) – Whether or not params is already transformed. Default is True.
  • cov_type (str, optional) – See fit for a description of covariance matrix types for results object.
  • cov_kwds (dict or None, optional) – See fit for a description of required keywords for alternative covariance estimators
  • return_raw (boolean,optional) – Whether or not to return only the raw Hamilton filter output or a full results object. Default is to return a full results object.
  • results_class (type, optional) – A results class to instantiate rather than MarkovSwitchingResults. Usually only used internally by subclasses.
  • results_wrapper_class (type, optional) – A results wrapper class to instantiate rather than MarkovSwitchingResults. Usually only used internally by subclasses.
Returns:
Return type:

MarkovSwitchingResults