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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 [aut, cre, cph], Steffen Moritz [aut], Brayan-David Aroca-Gonzalez [aut], Jhoana Romero [aut], Marlon Santacruz [aut], John-Josephraj Selvaraj [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 |
Reference manual: | kssa.pdf |
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 |
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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.