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KFAS

1.6.0

Kalman Filter and Smoother for Exponential Family State Space Models

22packages depend
203.3Kdownloads / year
65.5%test coverage
13/13checks pass

Overview

About
Maintained by Jouni HelskeFirst published 2009-08-1966 releasesCRAN page ↗GitHub ↗

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.

Install

Health

CRAN checks
13OK
Slowest check: 5.0 min · r-devel-windows-x86_64
Code health
Yes
Tests · ratio 0.13
65.5%
Coverage · measured lines
100%
Documentation · exports
1
Dependencies · direct
Check history
  • OK2026-08-05
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • NOTE2026-08-01
    12 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • OK2026-03-10
    14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

Documentation
READMENoVignettesYes · dynamicpkgdown siteNoNEWSNoCode of conductNoContributing guideNo
Examples that run
100%
Documented parameters
93%
Return-value docs
93%
References docs
26%

Downloads

203.3K
CRAN downloads in the past year
Rank #1,385 · ~557/day · ~16.9K/mo
Daily download trend is not available in this view yet.
6.5K30 days
20.7K90 days
203.3K1 year
Compare downloads with other packages →
Also on618 r2u18 autocran3.5K conda_forge80 c2d4u

Repository

Repository
73Stars
15Forks
7Open issues
0Open PRs
3Releases
393Commits
8Contributors
rfortrantime-seriesstate-spaceexponential-familygaussian-modelsdynamic-linear-model
393 commits · Last activity 2025-05-25 · 0% stars, 30d

Stars over time

2025-07-25 · 672026-07-07 · 73

Repository practices

Upstream repositoryBeta

2 development-tooling and community-health practices detected across 2 families in the upstream repository

Checks run against github.com/helske/kfas on 2026-08-16.

Continuous integration (1)
GitHub Actions
Coverage (1)
Codecov
How this is detected·Detection ruleset v1 (2026-07-18)

Dependencies

Declared dependencies
3 external dependencies (excludes base and recommended)
Depends (1)
R >= 3.1.0
Imports (1)
stats
LinkingTo (0)
none
Suggests (5)
Enhances (0)
none

Code & Tests

Datasets

People & History

People (1)
Maintainer (1)
Author, Maintainer · added in 0.4.5
Authors (1)
Author, Maintainer · added in 0.4.5
Listed in earlier versions (1)
no longer listed · 0.3.1 to 0.4.4
Package Timeline

66 releases. Pick two to compare their code metrics. R releases are shown for context.

  • R
    R 4.6.0 released · 2026-04-24
  • 1.6.0Latest
    2025-05-26 · current release · diff ↗
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    R 4.5.0 released · 2025-04-11
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    R 4.4.0 released · 2024-04-24
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    R 4.3.0 released · 2023-04-21
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    R 4.2.0 released · 2022-04-22
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    R 4.0.0 released · 2020-04-24
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    R 3.6.0 released · 2019-04-26
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    R 3.5.0 released · 2018-04-23
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    R 3.2.0 released · 2015-04-16
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    R 3.1.0 released · 2014-04-10
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    R 3.0.0 released · 2013-04-03
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    R 2.15.0 released · 2012-03-30
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    R 2.13.0 released · 2011-04-13
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    R 2.12.0 released · 2010-10-15
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    R 2.11.0 released · 2010-04-22
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    R 2.10.0 released · 2009-10-26
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    2009-08-21 · diff ↗
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    2009-08-21 · diff ↗
  • 0.3.1
    2009-08-19
  • R
    R 2.9.0 released · 2009-04-17

Package metadata

First published
2009-08-19
Total releases
66 / 17 yrs
License
GPL (>= 2) OSI
Minimum R
≥ 3.1.0
Bundled data
5.4 KB / 4 files
Download size
471 KB
Installed size
not tracked yet
With dependencies
not tracked yet
Appears in task views

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("KFAS")
Helske, J. (2025). KFAS: Kalman Filter and Smoother for Exponential Family State Space Models (Version 1.6.0) [Computer software]. https://doi.org/10.32614/CRAN.package.KFAS

This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for KFAS version 1.6.0 [Data set]. HJJB, LLC. Data release v2026-08-21. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-21, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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