Analyzing Data with Cellwise Outliers R package cellWise version 2.5.7 CRAN Task View: AnomalyDetection (https://CRAN.R-project.org/view=AnomalyDetection) 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> (open access) Hubert et al. (2019) <doi:10.1080/00401706.2018.1562989> (open access), Raymaekers and Rousseeuw (2021) <doi:10.1080/00401706.2019.1677270> (open access), Raymaekers and Rousseeuw (2021) <doi:10.1007/s10994-021-05960-5> (open access), Raymaekers and Rousseeuw (2021) <doi:10.52933/jdssv.v1i3.18> (open access), Raymaekers and Rousseeuw (2022) <doi:10.1080/01621459.2023.2267777> (open access) Rousseeuw (2022) <doi:10.1016/j.ecosta.2023.01.007> (open access). Examples can be found in the vignettes: "DDC_examples", "MacroPCA_examples", "wrap_examples", "transfo_examples", "DI_examples", "cellMCD_examples" , "Correspondence_analysis_examples", and "cellwise_weights_examples". Software Depends: R (>= 4.0.0) Imports: reshape2, scales, ggplot2, matrixStats, gridExtra, robustbase, rrcov, svd, stats, utils, shape, Rcpp (>= 0.12.10.14) LinkingTo: Rcpp, RcppArmadillo (>= 0.7.600.1.0) Suggests: knitr, robustHD, MASS, ellipse, markdown, rospca, GSE Jakob Raymaekers <jakob.raymaekers@uantwerpen.be> Comprehensive R Archive Network (CRAN) Jakob Raymaekers [aut, cre], Peter Rousseeuw [aut], Wannes Van den Bossche [ctb], Mia Hubert [ctb] GPL (>= 2) 2026-02-26 application/tgz https://CRAN.R-project.org/package=cellWise doi:10.32614/CRAN.package.cellWise