KFAS (0.4.7)

Multivariate Kalman filter and smoother, simulation smoother and forecasting of state space models. State smoothing and approximate likelihood of exponential family state space models..


Package KFAS provides functions for fast Kalman filtering, state and disturbance smoothing, forecasting and simulation of multivariate time-variant state space models. All functions can use exact diffuse initialisation when distributions of some or all elements of initial state vector are unknown. Filtering, state smoothing and simulation functions use sequential processing algorithm, which is faster than standard approach, and it also allows singularity of prediction error variance matrix. KFAS also contains function for approximation of likelihood of exponential family state space models and function for state smoothing of exponential family state space models.

Maintainer: Jouni Helske
Author(s): Jouni Helske <jouni.helske@jyu.fi>

License: GPL (>= 2)

Uses: Does not use any package
Reverse depends: MARSS, networkTomography, Peak2Trough, rucm, sspir
Reverse suggests: bssm, dlmodeler, ggfortify, MARSS, tscount

Released about 9 years ago.