State space modelling is an efficient and flexible method for statistical inference of a broad class of time series and other data. KFAS includes fast functions for Kalman filtering, smoothing, forecasting, and simulation of multivariate exponential family state space models, with observations from Gaussian, Poisson, binomial, negative binomial, and gamma distributions.

Maintainer: Jouni Helske <jouni.helske at iki.fi>

Author(s): Jouni Helske <jouni.helske at iki.fi>

Install package and any missing dependencies by running this line in your R console:

install.packages("KFAS")

Depends R (>= 3.1.0)
Imports stats
Suggests MASS, testthat, knitr, lme4
Enhances
Linking to
Reverse
depends
rucm
Reverse
imports
dcmr, dlmodeler, MARSS, networkTomography, tsPI, TSPred
Reverse
suggests
ggfortify, KFKSDS
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enhances
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linking to

Package KFAS
Materials
URL
Task Views TimeSeries
Version 1.2.8
Published 2017-06-08
License GPL (>= 2)
BugReports https://github.com/helske/KFAS/issues
SystemRequirements
NeedsCompilation yes
Citation
CRAN checks KFAS check results
Package source KFAS_1.2.8.tar.gz