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A reliable and efficient tool for cleaning univariate time series data. It implements reliable and efficient procedures for automating the process of cleaning univariate time series data. The package provides integration with already developed and deployed tools for missing value imputation and outlier detection. It also provides a way of visualizing large time-series data in different resolutions.
Version: | 0.1.2 |
Imports: | data.table, gganimate, ggplot2, ggtext, transformr, glue, imputeTestbench, imputeTS, lubridate, shiny, stringr, tibble |
Suggests: | rmarkdown, gifski (≥ 1.4.3), timetk, spelling |
Published: | 2023-07-06 |
DOI: | 10.32614/CRAN.package.cleanTS |
Author: | Mayur Shende [aut, cre], Neeraj Bokde [aut], Andrés E. Feijóo-Lorenzo [aut] |
Maintainer: | Mayur Shende <mayur.k.shende at gmail.com> |
BugReports: | https://github.com/Mayur1009/cleanTS/issues |
License: | GPL (≥ 3) |
URL: | https://github.com/Mayur1009/cleanTS |
NeedsCompilation: | no |
Language: | en-US |
Citation: | cleanTS citation info |
Materials: | README |
CRAN checks: | cleanTS results |
Reference manual: | cleanTS.pdf |
Package source: | cleanTS_0.1.2.tar.gz |
Windows binaries: | r-devel: cleanTS_0.1.2.zip, r-release: cleanTS_0.1.2.zip, r-oldrel: cleanTS_0.1.2.zip |
macOS binaries: | r-release (arm64): cleanTS_0.1.2.tgz, r-oldrel (arm64): cleanTS_0.1.2.tgz, r-release (x86_64): cleanTS_0.1.2.tgz, r-oldrel (x86_64): cleanTS_0.1.2.tgz |
Old sources: | cleanTS archive |
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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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