KFAS: 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.
| Version: |
0.4.7 |
| Depends: |
R (≥ 2.8.0) |
| Published: |
2009-11-11 |
| Author: |
Jouni Helske |
| Maintainer: |
Jouni Helske <jouni.helske at jyu.fi> |
| License: |
GPL (≥ 2) |
| In views: |
TimeSeries |
| CRAN checks: |
KFAS results |
Downloads: