devianLM: Detecting Extremal Values in a Normal Linear Model
Provides a method to detect values poorly explained by a Gaussian linear model. The procedure is based on the maximum of the absolute value of the studentized residuals, which is a parameter-free statistic. This approach generalizes several procedures used to detect abnormal values during longitudinal monitoring of biological markers. Methodological details are provided in Berthelot G., Saulière G., and Dedecker J. (2025), "DEViaN-LM An R Package for Detecting Abnormal Values in the Gaussian Linear Model", HAL Id: hal-05230549, <https://hal.science/hal-05230549>, and in Berthelot G., Gelein B., Meinadier E., Orhant E., and Dedecker J. (2026), "A guide to z-score-based methods, with illustrations from biological data sets", The Journal of Sport and Exercise Science 10, 54–70, <doi:10.36905/jses.2026.01.06>.
| Version: |
1.1.1 |
| Depends: |
R (≥ 2.10) |
| Imports: |
Rcpp |
| LinkingTo: |
Rcpp, RcppArmadillo |
| Suggests: |
testthat (≥ 3.0.0) |
| Published: |
2026-10-01 |
| DOI: |
10.32614/CRAN.package.devianLM |
| Author: |
Guillaume Sauliere
 [aut],
Geoffroy Berthelot
[aut, cre],
Jérôme Dedecker
[aut] |
| Maintainer: |
Geoffroy Berthelot <geoffroy.berthelot at insep.fr> |
| License: |
GPL-3 |
| NeedsCompilation: |
yes |
| SystemRequirements: |
OpenMP (optional, for parallel execution) |
| Materials: |
NEWS |
| CRAN checks: |
devianLM results |
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