Simulate Controlled Outliers

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).


Reference manual

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1.0.0 by Alba Gonzalez Cebrian, a year ago

Browse source code at

Authors: Alba Gonzalez Cebrian [aut, cre] , Abel Folch-Fortuny [aut] , Francisco Arteaga [aut] , Alberto Ferrer [aut]

Documentation:   PDF Manual  

GPL-3 license

Depends on ggplot2, ggpubr, stats

Suggests knitr, rmarkdown

See at CRAN