Package: SCOUTer
Title: Simulate Controlled Outliers
Version: 1.0.0
Authors@R: 
    c(person(given = "Alba",
           family = "Gonzalez Cebrian",
           role = c("aut", "cre"),
           email = "algonceb@upv.es"),
           person(given = "Abel",
           family = "Folch-Fortuny",
           role = "aut",
           email = "Abel.Folch-Fortuny@dsm.com"),
           person(given = "Francisco",
           family = "Arteaga",
           role = c("aut"),
           email = "francisco.arteaga@ucv.es"),
           person(given = "Alberto",
           family = "Ferrer",
           role = "aut",
           email = "aferrer@eio.upv.es"))
Description: Using principal component analysis as a base model,
        'SCOUTer' offers a new approach to simulate outliers in a
        simple and precise way. The user can generate new observations
        defining them by a pair of well-known statistics: the Squared
        Prediction Error (SPE) and the Hotelling's T^2 (T^2)
        statistics. Just by introducing the target values of the SPE
        and T^2, 'SCOUTer' returns a new set of observations with the
        desired target properties. Authors: Alba González, Abel
        Folch-Fortuny, Francisco Arteaga and Alberto Ferrer (2020).
License: GPL-3
Encoding: UTF-8
LazyData: true
Maintainer: Alba Gonzalez Cebrian <algonceb@upv.es>
RoxygenNote: 7.1.1
Depends: R (>= 3.5.0), ggplot2, ggpubr, stats
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-07-05 08:10:30 UTC; root
Author: Alba Gonzalez Cebrian [aut, cre], Abel Folch-Fortuny [aut],
        Francisco Arteaga [aut], Alberto Ferrer [aut]
Repository: https://cran.r-universe.dev
Date/Publication: 2020-06-30 08:30:03 UTC
RemoteUrl: https://github.com/cran/SCOUTer
RemoteRef: HEAD
RemoteSha: e19a07eb39e2cb9e701b6e32129e7cde546b1daf