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rrobot: Robust Outlier Detection for Diverse Distributions

Provides robust outlier detection techniques for identifying anomalies in multivariate data, with a focus on methods that remain effective under non-Gaussian distributions. For more details see Saluja, Parlak, and Mejia (2026+) <doi:10.48550/arXiv.2505.11806>.

Version: 0.1.3
Depends: R (≥ 3.6.0)
Imports: MASS, stats, cellWise, expm, robustbase, gamlss, imputeTS, isotree, ggplot2, tidyr, reshape2, rlang
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2026-03-09
DOI: 10.32614/CRAN.package.rrobot
Author: Amanda Mejia [aut, cre], Damon Pham ORCID iD [ctb], Saranjeet Singh Saluja [ctb], Fatma Parlak [ctb], Zeshawn Zahid [ctb]
Maintainer: Amanda Mejia <mandy.mejia at gmail.com>
BugReports: https://github.com/mandymejia/rrobot/issues
License: GPL-3
URL: https://github.com/mandymejia/rrobot
NeedsCompilation: no
Language: en-US
Materials: README, NEWS
CRAN checks: rrobot results

Documentation:

Reference manual: rrobot.html , rrobot.pdf
Vignettes: Robust outlier detection with 'rrobot' (source, R code)

Downloads:

Package source: rrobot_0.1.3.tar.gz
Windows binaries: r-devel: rrobot_0.1.3.zip, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): rrobot_0.1.3.tgz, r-oldrel (arm64): rrobot_0.1.3.tgz, r-release (x86_64): rrobot_0.1.3.tgz, r-oldrel (x86_64): rrobot_0.1.3.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=rrobot to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.