An ensemble of time series outlier detection methods that can be used for compositional, multivariate and univariate data. It uses the four R packages 'forecast', 'tsoutliers', 'otsad' and 'anomalize' to detect time series outliers.
| Version: | 0.1.0 |
| Depends: | R (≥ 3.4.0) |
| Imports: | otsad, tsoutliers, forecast, anomalize, dplyr, tibble, rlang, pracma, dobin, ICS, fastICA, gridExtra, grid, ggplot2, tidyr, kableExtra |
| Suggests: | knitr, rmarkdown, tourr, stringr, broom, rgdal |
| Published: | 2020-09-30 |
| Author: | Sevvandi Kandanaarachchi
|
| Maintainer: | Sevvandi Kandanaarachchi <sevvandik at gmail.com> |
| License: | GPL-3 |
| URL: | https://sevvandi.github.io/composits/ |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | composits results |
| Reference manual: | composits.pdf |
| Vignettes: |
composits |
| Package source: | composits_0.1.0.tar.gz |
| Windows binaries: | r-devel: composits_0.1.0.zip, r-release: composits_0.1.0.zip, r-oldrel: composits_0.1.0.zip |
| macOS binaries: | r-release: composits_0.1.0.tgz, r-oldrel: composits_0.1.0.tgz |
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