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.


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install.packages("composits")

0.1.0 by Sevvandi Kandanaarachchi, 22 days ago


https://sevvandi.github.io/composits/


Browse source code at https://github.com/cran/composits


Authors: Sevvandi Kandanaarachchi [aut, cre] , Patricia Menendez [aut] , Ursula Laa [aut] , Ruben Loaiza-Maya [aut]


Documentation:   PDF Manual  


GPL-3 license


Imports otsad, tsoutliers, forecast, anomalize, dplyr, tibble, rlang, pracma, dobin, ICS, fastICA, gridExtra, grid, ggplot2, tidyr, kableExtra

Suggests knitr, rmarkdown, tourr, stringr, broom, rgdal


See at CRAN