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State space modelling is an efficient and flexible framework for statistical inference of a broad class of time series and other data. KFAS includes computationally efficient 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. See the paper by Helske (2017) <doi:10.18637/jss.v078.i10> for details.
Version: | 1.5.1 |
Depends: | R (≥ 3.1.0) |
Imports: | stats |
Suggests: | knitr, lme4, MASS, Matrix, testthat |
Published: | 2023-09-05 |
DOI: | 10.32614/CRAN.package.KFAS |
Author: | Jouni Helske |
Maintainer: | Jouni Helske <jouni.helske at iki.fi> |
BugReports: | https://github.com/helske/KFAS/issues |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
URL: | https://github.com/helske/KFAS |
NeedsCompilation: | yes |
Citation: | KFAS citation info |
Materials: | ChangeLog |
In views: | TimeSeries |
CRAN checks: | KFAS results |
Reference manual: | KFAS.pdf |
Vignettes: |
KFAS: Exponential Family State Space Models in R |
Package source: | KFAS_1.5.1.tar.gz |
Windows binaries: | r-devel: KFAS_1.5.1.zip, r-release: KFAS_1.5.1.zip, r-oldrel: KFAS_1.5.1.zip |
macOS binaries: | r-release (arm64): KFAS_1.5.1.tgz, r-oldrel (arm64): KFAS_1.5.1.tgz, r-release (x86_64): KFAS_1.5.1.tgz, r-oldrel (x86_64): KFAS_1.5.1.tgz |
Old sources: | KFAS archive |
Reverse depends: | CausalMBSTS, rucm |
Reverse imports: | countSTAR, MARSS, mbsts, RGAP, sectorgap, tsPI, TSPred, tspredit, walker |
Reverse suggests: | bssm, ggfortify, sarima |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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