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RobKF: Innovative and/or Additive Outlier Robust Kalman Filtering

Implements a series of robust Kalman filtering approaches. It implements the additive outlier robust filters of Ruckdeschel et al. (2014) <doi:10.48550/arXiv.1204.3358> and Agamennoni et al. (2018) <doi:10.1109/ICRA.2011.5979605>, the innovative outlier robust filter of Ruckdeschel et al. (2014) <doi:10.48550/arXiv.1204.3358>, as well as the innovative and additive outlier robust filter of Fisch et al. (2020) <doi:10.48550/arXiv.2007.03238>.

Version: 1.0.2
Imports: Rcpp (≥ 1.0.2), Rdpack, ggplot2, reshape2, Matrix
LinkingTo: Rcpp, RcppEigen
Published: 2021-07-15
DOI: 10.32614/CRAN.package.RobKF
Author: Alex TM Fisch [aut], Daniel Grose [aut, cre], Idris A Eckley [aut, ths], Paul Fearnhead [aut, ths], Lawrence Bardwell [aut, ctb]
Maintainer: Daniel Grose <dan.grose at lancaster.ac.uk>
License: GPL-2 | GPL-3 [expanded from: GPL]
NeedsCompilation: yes
Materials: README
In views: TimeSeries
CRAN checks: RobKF results

Documentation:

Reference manual: RobKF.pdf

Downloads:

Package source: RobKF_1.0.2.tar.gz
Windows binaries: r-devel: RobKF_1.0.2.zip, r-release: RobKF_1.0.2.zip, r-oldrel: RobKF_1.0.2.zip
macOS binaries: r-release (arm64): RobKF_1.0.2.tgz, r-oldrel (arm64): RobKF_1.0.2.tgz, r-release (x86_64): RobKF_1.0.2.tgz, r-oldrel (x86_64): RobKF_1.0.2.tgz
Old sources: RobKF archive

Linking:

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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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