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
 [aut, cre],
Patricia Menendez
[aut],
Ursula Laa [aut],
Ruben Loaiza-Maya
[aut] |
| Maintainer: |
Sevvandi Kandanaarachchi <sevvandik at gmail.com> |
| License: |
GPL-3 |
| URL: |
https://sevvandi.github.io/composits/ |
| NeedsCompilation: |
no |
| Materials: |
README |
| CRAN checks: |
composits results |