Detecting outliers using robust methods, i.e. the Median Absolute Deviation (MAD) for univariate outliers; Leys, Ley, Klein, Bernard, & Licata (2013) <doi:10.1016/j.jesp.2013.03.013> and the Mahalanobis-Minimum Covariance Determinant (MMCD) for multivariate outliers; Leys, C., Klein, O., Dominicy, Y. & Ley, C. (2018) <doi:10.1016/j.jesp.2017.09.011>. There is also the more known but less robust Mahalanobis distance method, only for comparison purposes.
| Version: | 0.0.0.3 |
| Depends: | R (≥ 2.10) |
| Imports: | MASS, stats, graphics, ggplot2 |
| Suggests: | knitr, rmarkdown, testthat |
| Published: | 2019-05-23 |
| Author: | Marie Delacre [aut, cre], Olivier Klein [aut] |
| Maintainer: | Marie Delacre <marie.delacre at ulb.ac.be> |
| BugReports: | https://github.com/mdelacre/Routliers/issues |
| License: | MIT + file LICENSE |
| NeedsCompilation: | no |
| Materials: | README NEWS |
| CRAN checks: | Routliers results |
| Reference manual: | Routliers.pdf |
| Package source: | Routliers_0.0.0.3.tar.gz |
| Windows binaries: | r-devel: Routliers_0.0.0.3.zip, r-release: Routliers_0.0.0.3.zip, r-oldrel: Routliers_0.0.0.3.zip |
| macOS binaries: | r-release (arm64): Routliers_0.0.0.3.tgz, r-oldrel (arm64): Routliers_0.0.0.3.tgz, r-release (x86_64): Routliers_0.0.0.3.tgz, r-oldrel (x86_64): Routliers_0.0.0.3.tgz |
| Old sources: | Routliers archive |
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