SCOUTer: 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).

Package details

AuthorAlba Gonzalez Cebrian [aut, cre], Abel Folch-Fortuny [aut], Francisco Arteaga [aut], Alberto Ferrer [aut]
MaintainerAlba Gonzalez Cebrian <algonceb@upv.es>
LicenseGPL-3
Version1.0.0
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("SCOUTer")

Try the SCOUTer package in your browser

Any scripts or data that you put into this service are public.

SCOUTer documentation built on July 1, 2020, 6:27 p.m.