cellWise: Analyzing Data with Cellwise Outliers

Tools for detecting cellwise outliers and robust methods to analyze data which may contain them. Contains the implementation of the algorithms described in Rousseeuw and Van den Bossche (2018) <doi:10.1080/00401706.2017.1340909>, Hubert et al. (2019) <doi:10.1080/00401706.2018.1562989>, Raymaekers and Rousseeuw (2019) <doi:10.1080/00401706.2019.1677270>.

Version: 2.1.1
Depends: R (≥ 3.2.0)
Imports: reshape2, scales, ggplot2, matrixStats, gridExtra, robustbase, rrcov, svd, Rcpp (≥
LinkingTo: Rcpp, RcppArmadillo (≥ 0.7.600.1.0)
Suggests: knitr, robustHD, MASS, ellipse
Published: 2020-04-14
Author: Jakob Raymaekers [aut, cre], Peter Rousseeuw [aut], Wannes Van den Bossche [aut], Mia Hubert [aut]
Maintainer: Jakob Raymaekers <jakob.raymaekers at kuleuven.be>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
CRAN checks: cellWise results


Reference manual: cellWise.pdf
Vignettes: DDC examples
MacroPCA examples
Wrap examples
Package source: cellWise_2.1.1.tar.gz
Windows binaries: r-devel: cellWise_2.1.1.zip, r-release: cellWise_2.1.1.zip, r-oldrel: cellWise_2.1.1.zip
macOS binaries: r-release: cellWise_2.1.1.tgz, r-oldrel: cellWise_2.1.1.tgz
Old sources: cellWise archive

Reverse dependencies:

Reverse imports: GSE, OutliersO3


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