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KFAS

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Kalman Filter and Smoother for Exponential Family State Space Models

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]

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 07 Jun. 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)

Other packages that cited KFAS R package

View KFAS citation profile

Other R packages that KFAS depends, imports, suggests or enhances

View KFAS dependency map

Complete documentation for KFAS

View documentation PDF

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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