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Routliers
View on CRAN: Click
here
Download and install Routliers package within the R console
Install from CRAN:
install.packages("Routliers")
Install from Github:
library("remotes")
install_github("cran/Routliers")
Install by package version:
library("remotes")
install_version("Routliers", "0.0.0.3")
Attach the package and use:
library("Routliers")
Maintained by
Marie Delacre
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-04-28
Latest Update: 2019-05-23
Description:
Detecting outliers using robust methods,
i.e. the Median Absolute Deviation (MAD) for univariate outliers; Leys, Ley, Klein, Bernard, & Licata (2013)
and the Mahalanobis-Minimum Covariance Determinant (MMCD) for multivariate outliers; Leys, C., Klein, O., Dominicy, Y. & Ley, C. (2018) .
There is also the more known but less robust Mahalanobis distance method, only for comparison purposes.
How to cite:
Marie Delacre (2019). Routliers: Robust Outliers Detection. R package version 0.0.0.3, https://cran.r-project.org/web/packages/Routliers. Accessed 21 Dec. 2024.
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imports, suggests or enhances
Complete documentation for Routliers
Functions, R codes and Examples using
the Routliers R package
Some associated functions: Attacks . Intention . Morality . Routliers-package . outliers_mad . outliers_mahalanobis . outliers_mcd . plot_outliers_mad . plot_outliers_mahalanobis . plot_outliers_mcd .
Some associated R codes: Attacks.R . Intention.R . Morality.R . Routliers-package.R . outliers_mad.R . outliers_mahalanobis.R . outliers_mcd.R . plot_outliers_mad.R . plot_outliers_mahalanobis.R . plot_outliers_mcd.R . Full Routliers package functions and examples
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