Simulate Controlled Outliers R package SCOUTer version 1.0.0 CRAN Task View: AnomalyDetection (https://CRAN.R-project.org/view=AnomalyDetection) 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). Software Depends: R (>= 3.5.0), ggplot2, ggpubr, stats Suggests: knitr, rmarkdown Alba Gonzalez Cebrian <algonceb@upv.es> Comprehensive R Archive Network (CRAN) Alba Gonzalez Cebrian [aut, cre], Abel Folch-Fortuny [aut], Francisco Arteaga [aut], Alberto Ferrer [aut] GPL-3 2020-06-30 application/tgz https://CRAN.R-project.org/package=SCOUTer doi:10.32614/CRAN.package.SCOUTer