composits: Compositional, Multivariate and Univariate Time Series Outlier Ensemble

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

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