statsmodels.tsa.statespace.kalman_smoother.KalmanSmoother

class statsmodels.tsa.statespace.kalman_smoother.KalmanSmoother(k_endog, k_states, k_posdef=None, results_class=None, kalman_smoother_classes=None, **kwargs)[source]

State space representation of a time series process, with Kalman filter and smoother.

Parameters
  • k_endog (array_like or integer) – The observed time-series process \(y\) if array like or the number of variables in the process if an integer.

  • k_states (int) – The dimension of the unobserved state process.

  • k_posdef (int, optional) – The dimension of a guaranteed positive definite covariance matrix describing the shocks in the measurement equation. Must be less than or equal to k_states. Default is k_states.

  • results_class (class, optional) – Default results class to use to save filtering output. Default is SmootherResults. If specified, class must extend from SmootherResults.

  • **kwargs – Keyword arguments may be used to provide default values for state space matrices, for Kalman filtering options, or for Kalman smoothing options. See Representation for more details.

Methods

bind(endog)

Bind data to the statespace representation

filter([filter_method, inversion_method, …])

Apply the Kalman filter to the statespace model.

fixed_scale(scale)

Context manager for fixing the scale when FILTER_CONCENTRATED is set

impulse_responses([steps, impulse, …])

Impulse response function

initialize(initialization[, …])

initialize_approximate_diffuse([variance])

Initialize the statespace model with approximate diffuse values.

initialize_diffuse()

Initialize the statespace model as stationary.

initialize_known(constant, stationary_cov)

Initialize the statespace model with known distribution for initial state.

initialize_stationary()

Initialize the statespace model as stationary.

loglike(**kwargs)

Calculate the loglikelihood associated with the statespace model.

loglikeobs(**kwargs)

Calculate the loglikelihood for each observation associated with the statespace model.

set_conserve_memory([conserve_memory])

Set the memory conservation method

set_filter_method([filter_method])

Set the filtering method

set_filter_timing([alternate_timing])

Set the filter timing convention

set_inversion_method([inversion_method])

Set the inversion method

set_smooth_method([smooth_method])

Set the smoothing method

set_smoother_output([smoother_output])

Set the smoother output

set_stability_method([stability_method])

Set the numerical stability method

simulate(nsimulations[, measurement_shocks, …])

Simulate a new time series following the state space model

smooth([smoother_output, smooth_method, …])

Apply the Kalman smoother to the statespace model.

Attributes

conserve_memory

design

dtype

(dtype) Datatype of currently active representation matrices

endog

filter_augmented

filter_collapsed

filter_concentrated

filter_conventional

filter_exact_initial

filter_extended

filter_method

filter_methods

filter_square_root

filter_timing

filter_univariate

filter_unscented

inversion_method

inversion_methods

invert_cholesky

invert_lu

invert_univariate

memory_conserve

memory_no_filtered

memory_no_forecast

memory_no_gain

memory_no_likelihood

memory_no_predicted

memory_no_smoothing

memory_no_std_forecast

memory_options

memory_store_all

obs

\(y~(k\_endog \times nobs)\)

obs_cov

obs_intercept

prefix

(str) BLAS prefix of currently active representation matrices

selection

smooth_alternative

(bool) Flag for alternative (modified Bryson-Frazier) smoothing.

smooth_classical

(bool) Flag for classical (see e.g.

smooth_conventional

(bool) Flag for conventional (Durbin and Koopman, 2012) Kalman smoothing.

smooth_method

smooth_methods

smooth_univariate

(bool) Flag for univariate smoothing (uses modified Bryson-Frazier timing).

smoother_all

smoother_disturbance

smoother_disturbance_cov

smoother_output

smoother_outputs

smoother_state

smoother_state_autocov

smoother_state_cov

solve_cholesky

solve_lu

stability_force_symmetry

stability_method

stability_methods

state_cov

state_intercept

time_invariant

(bool) Whether or not currently active representation matrices are time-invariant

timing_init_filtered

timing_init_predicted

timing_options

transition