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KFAS
View on CRAN: Click
here
Download and install KFAS package within the R console
Install from CRAN:
install.packages("KFAS")
Install from Github:
library("remotes")
install_github("cran/KFAS") Install by package version:
library("remotes")
install_version("KFAS", "1.6.0") Attach the package and use:
library("KFAS")
Maintained by
Jouni Helske
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2009-08-19
Latest Update: 2025-05-26
Description:
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) for details.
How to cite:
Jouni Helske (2009). KFAS: Kalman Filter and Smoother for Exponential Family State Space Models. R package version 1.6.0, https://cran.r-project.org/web/packages/KFAS. Accessed 08 Oct. 2026.
Previous versions and publish date:
0.3.1 (2009-08-19 10:14), 0.3.2 (2009-08-21 09:08), 0.3.3 (2009-08-27 09:37), 0.4.1 (2009-09-18 22:16), 0.4.2 (2009-09-28 09:51), 0.4.3 (2009-09-28 15:36), 0.4.4 (2009-10-01 21:53), 0.4.5 (2009-10-19 18:16), 0.4.6 (2009-10-22 20:37), 0.4.7 (2009-11-11 14:10), 0.4.8 (2009-12-14 20:58), 0.4.9 (2009-12-29 16:04), 0.5.0 (2010-01-07 16:40), 0.5.1 (2010-01-12 14:14), 0.5.2 (2010-01-22 15:14), 0.5.3 (2010-01-25 08:49), 0.5.4 (2010-02-02 15:11), 0.5.5 (2010-02-03 16:43), 0.5.6 (2010-02-09 10:16), 0.5.7 (2010-02-09 17:30), 0.5.8 (2010-03-26 12:17), 0.5.9 (2010-04-14 12:36), 0.6.0 (2010-04-15 20:38), 0.6.1 (2011-02-23 17:18), 0.9.9 (2012-07-06 12:16), 0.9.11 (2012-07-09 11:29), 1.0.2 (2013-12-07 10:31), 1.0.3 (2014-03-26 07:27), 1.0.4-1 (2014-06-06 17:31), 1.0.4 (2014-05-27 10:59), 1.1.0 (2015-04-18 08:55), 1.1.1 (2015-04-29 16:23), 1.1.2 (2015-06-26 13:34), 1.2.0 (2016-01-31 12:22), 1.2.1 (2016-02-05 19:39), 1.2.2 (2016-03-17 13:58), 1.2.3 (2016-06-23 01:05), 1.2.4 (2016-07-29 07:48), 1.2.5 (2016-12-23 17:21), 1.2.6 (2017-04-19 02:19), 1.2.8 (2017-06-08 15:53), 1.2.9 (2017-08-21 15:29), 1.3.0 (2017-12-08 14:52), 1.3.1 (2018-01-04 15:50), 1.3.2 (2018-05-21 17:29), 1.3.3 (2018-09-19 16:00), 1.3.4 (2019-02-03 11:53), 1.3.5 (2019-04-08 12:32), 1.3.6 (2019-05-29 14:20), 1.3.7 (2019-06-10 10:50), 1.4.0 (2020-12-07 12:30), 1.4.1 (2020-12-08 19:40), 1.4.2 (2021-01-14 10:50), 1.4.4 (2021-01-21 18:40), 1.4.5 (2021-05-10 11:42), 1.4.6 (2021-06-07 12:30), 1.5.0 (2023-02-07 11:42), 1.5.1 (2023-09-05 10:20), (2026-07-09 08:07)
Other packages that cited KFAS R package
View KFAS citation profile
Other R packages that KFAS depends,
imports, suggests or enhances
Complete documentation for KFAS
Functions, R codes and Examples using
the KFAS R package
Some associated functions: Extract.SSModel . GlobalTemp . KFAS-defunct . KFAS . KFS . SSModel . alcohol . approxSSM . artransform . boat . checkModel . coef.SSModel . fitSSM . fitted.SSModel . hatvalues.KFS . importanceSSM . ldl . logLik.SSModel . mvInnovations . plot.SSModel . predict.SSModel . print.KFS . print.SSModel . rename_states . residuals.KFS . rstandard.KFS . sexratio . signal . simulateSSM . transformSSM .
Some associated R codes: KFAS-defunct.R . KFAS-package.R . KFS.R . SSMarima.R . SSMcustom.R . SSMcycle.R . SSModel.R . SSMregression.R . SSMseasonal.R . SSMtrend.R . approxSSM.R . artransform.R . checkModel.R . coef.KFS.R . extract.SSModel.R . fitSSM.R . fitted.KFS.R . hatvalues.KFS.R . importanceSSM.R . initTheta.R . internalResids.R . interval.R . ldl.R . logLik.SSModel.R . mvInnovations.R . plot.SSModel.R . predict.SSModel.R . printjects.R . rename_states.R . residuals.KFS.R . rstandard.KFS.R . signals.R . simHelper.R . simulateSSM.R . transformSSM.R . zzz.R . Full KFAS package functions and examples
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