Introduction | Top Gear data | Comparison of cellMCD with covMCD | Aircraft data without response (n=23, d=4) | Aircraft with response (n=23, d=5) | alcohol (n=44, d=7) | Animals2 (n=65, d=2) | bushfire (n=38, d=5) | cloud (n = 19, d = 2) | delivery without response n=25, d=2 | delivery with response n=25, d=3 | exAM (n=12, d=2) | hbk without response (n=75, d=3) | hbk with response (n=75, d=4) | kootenay (n=13, d=2) | lactic (n=13, d=2) | milk (n=68, d=8) | pension (n=13, d=2) | phosphor (n=18, d=3) | pilot (n=20, d=2) | radarImage n=1573, d=5 | Salinity without response n=28, d=3 | Salinity with response (n=28, d=4) | starsCYG (n=47, d=2) | toxicity (n=38, d=10) | wood without response n=20, d=5
Package: cellWise 2.5.7
Jakob Raymaekers
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> (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".
Authors:
cellWise_2.5.7.tar.gz
cellWise_2.5.7.zip(r-4.7-x86_64)cellWise_2.5.7.zip(r-4.7-arm64)cellWise_2.5.7.zip(r-4.6-x86_64)cellWise_2.5.7.zip(r-4.6-arm64)
cellWise_2.5.7.tar.gz(r-4.7-arm64)cellWise_2.5.7.tar.gz(r-4.7-x86_64)cellWise_2.5.7.tar.gz(r-4.6-arm64)cellWise_2.5.7.tar.gz(r-4.6-x86_64)
cellWise_2.5.7.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
cellWise/json (API)
| # Install 'cellWise' in R: |
| install.packages('cellWise', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Uses libs:
Datasets:
- data_brands - The brands dataset
- data_clothes - The clothes dataset
- data_dogWalker - Dog walker dataset
- data_dposs - DPOSS dataset
- data_glass - The glass dataset
- data_mortality - The mortality dataset
- data_personality_traits - The personality traits data
- data_philips - The philips dataset
- data_VOC - VOC dataset
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:f6e62abd20. Checks:10 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 207 | ||
| linux-devel-x86_64 | OK | 176 | ||
| source / vignettes | OK | 400 | ||
| linux-release-arm64 | OK | 196 | ||
| linux-release-x86_64 | OK | 221 | ||
| windows-devel-arm64 | OK | 334 | ||
| windows-devel-x86_64 | OK | 284 | ||
| windows-release-arm64 | OK | 332 | ||
| windows-release-x86_64 | OK | 265 | ||
| wasm-release | OK | 186 |
Exports:cellHandlercellMapcellMCDcheckDataSetcwLocScatDDCDDCpredictDIestLocScalegenerateCorMatgenerateDataICPCAMacroPCAMacroPCApredictoutlierMapplot_cellMCDtransfotransfo_newdatatransfo_transformbacktruncPCunpackweightedEMwrap
Dependencies:clicpp11DEoptimRfarverggplot2gluegridExtragtableisobandlabelinglatticelifecyclemagrittrmatrixStatsmvtnormpcaPPplyrR6RColorBrewerRcppRcppArmadilloreshape2rlangrobustbaserrcovS7scalesshapestringistringrsvdvctrsviridisLitewithr
cellMCD examples
Last update: 2023-10-25
Started: 2022-08-10
cellwise weights examples
Introduction | Unpack the toy example in section 2 of the paper | Playing with the function cwLocScat | Personality traits example from section 4
Last update: 2023-10-25
Started: 2022-12-11
Correspondence analysis examples
Introduction | Clothes data | Brand perception example
Last update: 2023-10-25
Started: 2022-12-11
DDC examples
Introduction | Example with row and column selection | Small generated dataset | TopGear dataset | Analyzing new data by DDCpredict | Define the "initial" dataset as the rows not in these 17: | Define the "new" dataset, and apply DDCpredict to it: | Philips data | We also apply the rowwise method MCD to detect outlying rows: | Mortality dataset | We also apply the rowwise method ROBPCA to detect outlying rows: | Glass dataset | We will compare this with the faster approximate algorithm of DDC, obtained by the option fastDDC=TRUE:
Last update: 2023-10-25
Started: 2016-12-07
DI examples
Introduction | Artificial data | VOC data
Last update: 2023-10-25
Started: 2020-12-03
MacroPCA examples
Introduction | Small generated example | TopGear dataset | Also run ICPCA (iterative classical PCA): | TopGear dataset: prediction of new data | Glass dataset | We now compare MacroPCA with ROBPCA: | We now compare fastDDC=FALSE with fastDDC=TRUE in MacroPCA: | DPOSS dataset
Last update: 2023-10-25
Started: 2019-02-25
transfo examples
Introduction | Small toy example | Transform new data and transform back | TopGear example | Glass data example | DPOSS data example
Last update: 2023-10-25
Started: 2020-11-11
wrap examples
Introduction | Dog walker video example
Last update: 2023-10-25
Started: 2021-03-09
