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kssa: Known Sub-Sequence Algorithm

Implements the Known Sub-Sequence Algorithm <doi:10.1016/j.aaf.2021.12.013>, which helps to automatically identify and validate the best method for missing data imputation in a time series. Supports the comparison of multiple state-of-the-art algorithms.

Version: 0.0.1
Depends: R (≥ 4.0)
Imports: magrittr, ggplot2, rlang, methods, forecast, imputeTS, stats, zoo, Metrics, dplyr, missMethods
Suggests: covr, testthat (≥ 3.0.0)
Published: 2022-06-21
DOI: 10.32614/CRAN.package.kssa
Author: Iván Felipe Benavides ORCID iD [aut, cre, cph], Steffen Moritz ORCID iD [aut], Brayan-David Aroca-Gonzalez ORCID iD [aut], Jhoana Romero ORCID iD [aut], Marlon Santacruz ORCID iD [aut], John-Josephraj Selvaraj ORCID iD [aut]
Maintainer: Iván Felipe Benavides <pipeben at gmail.com>
BugReports: https://github.com/pipeben/kssa/issues
License: AGPL (≥ 3)
URL: https://github.com/pipeben/kssa
NeedsCompilation: no
Materials: README NEWS
CRAN checks: kssa results

Documentation:

Reference manual: kssa.pdf

Downloads:

Package source: kssa_0.0.1.tar.gz
Windows binaries: r-devel: kssa_0.0.1.zip, r-release: kssa_0.0.1.zip, r-oldrel: kssa_0.0.1.zip
macOS binaries: r-release (arm64): kssa_0.0.1.tgz, r-oldrel (arm64): kssa_0.0.1.tgz, r-release (x86_64): kssa_0.0.1.tgz, r-oldrel (x86_64): kssa_0.0.1.tgz

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.