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SCOUTer

Simulate Controlled Outliers

v1.0.0 · Jun 30, 2020 · GPL-3

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).

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r-oldrel-macos-arm64 OK
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r-oldrel-windows-x86_64 OK
r-patched-linux-x86_64 OK
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r-release-macos-arm64 OK
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r-release-windows-x86_64 OK
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Check History

OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 2026

Dependency Network

Dependencies Reverse dependencies ggplot2 ggpubr SCOUTer

Version History

new 1.0.0 Mar 10, 2026