CRAN/E | SCOUTer

SCOUTer

Simulate Controlled Outliers

Installation

About

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).

Key Metrics

Version 1.0.0
R ≥ 3.5.0
Published 2020-06-30 1449 days ago
Needs compilation? no
License GPL-3
CRAN checks SCOUTer results

Downloads

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Maintainer

Maintainer

Alba Gonzalez Cebrian

Authors

Alba Gonzalez Cebrian

aut / cre

Abel Folch-Fortuny

aut

Francisco Arteaga

aut

Alberto Ferrer

aut

Material

README
Reference manual
Package source

Vignettes

SCOUTer demo

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Depends

R ≥ 3.5.0
ggplot2
ggpubr
stats

Suggests

knitr
rmarkdown