FKF: Fast Kalman Filter

This is a fast and flexible implementation of the Kalman filter and smoother, which can deal with NAs. It is entirely written in C and relies fully on linear algebra subroutines contained in BLAS and LAPACK. Due to the speed of the filter, the fitting of high-dimensional linear state space models to large datasets becomes possible. This package also contains a plot function for the visualization of the state vector and graphical diagnostics of the residuals.

Version: 0.2.2
Depends: R (≥ 2.8)
Imports: graphics
Suggests: knitr, rmarkdown, covr, pkgdown, testthat (≥ 3.0.0)
Published: 2021-10-17
Author: David Luethi [aut], Philipp Erb [aut], Simon Otziger [aut], Daniel McDonald [aut], Paul Smith ORCID iD [aut, cre]
Maintainer: Paul Smith <paul at waternumbers.co.uk>
BugReports: https://github.com/waternumbers/FKF/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://waternumbers.github.io/FKF/, https://github.com/waternumbers/FKF
NeedsCompilation: yes
Materials: README NEWS
In views: TimeSeries
CRAN checks: FKF results

Documentation:

Reference manual: FKF.pdf
Vignettes: Fast Kalman Filter

Downloads:

Package source: FKF_0.2.2.tar.gz
Windows binaries: r-devel: FKF_0.2.2.zip, r-devel-UCRT: FKF_0.2.2.zip, r-release: FKF_0.2.2.zip, r-oldrel: FKF_0.2.2.zip
macOS binaries: r-release (arm64): FKF_0.2.1.tgz, r-release (x86_64): FKF_0.2.2.tgz, r-oldrel: FKF_0.2.2.tgz
Old sources: FKF archive

Reverse dependencies:

Reverse imports: garma, sarima, tscopula
Reverse suggests: FKF.SP, highfrequency, KFKSDS

Linking:

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