Package: composits
Type: Package
Title: Compositional, Multivariate and Univariate Time Series Outlier
        Ensemble
Version: 0.1.0
Authors@R: c(
  person("Sevvandi", "Kandanaarachchi", email = "sevvandik@gmail.com",
  role = c("aut", "cre"), comment = c(ORCID = "0000-0002-0337-0395")),
  person("Patricia", "Menendez", email = "Patricia.Menendez@monash.edu",
  role = c("aut"), comment = c(ORCID = "0000-0003-0701-6315")), 
  person("Ursula", "Laa", email = "Ursula.Laa@monash.edu",
  role = c("aut"), comment = c(ORCID = "0000-0002-0249-6439")),
  person("Ruben", "Loaiza-Maya", email = "Ruben.LoaizaMaya@monash.edu",
  role = c("aut"), comment = c(ORCID = "0000-0003-4132-8355"))
  )
Maintainer: Sevvandi Kandanaarachchi <sevvandik@gmail.com>
Description: 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. 
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: otsad, tsoutliers, forecast, anomalize, dplyr, tibble, rlang,
        pracma, dobin, ICS, fastICA, gridExtra, grid, ggplot2, tidyr,
        kableExtra
RoxygenNote: 7.1.1
Suggests: knitr, rmarkdown, tourr, stringr, broom, rgdal
VignetteBuilder: knitr
Depends: R (>= 3.4.0)
URL: https://sevvandi.github.io/composits/
NeedsCompilation: no
Packaged: 2020-09-28 12:29:00 UTC; Sevvandi
Author: Sevvandi Kandanaarachchi [aut, cre]
    (<https://orcid.org/0000-0002-0337-0395>),
  Patricia Menendez [aut] (<https://orcid.org/0000-0003-0701-6315>),
  Ursula Laa [aut] (<https://orcid.org/0000-0002-0249-6439>),
  Ruben Loaiza-Maya [aut] (<https://orcid.org/0000-0003-4132-8355>)
Repository: CRAN
Date/Publication: 2020-09-30 09:50:02 UTC
Built: R 4.0.5; ; 2022-04-21 15:14:32 UTC; windows
