Package: crmReg 1.0.4

crmReg: Cellwise Robust M-Regression and SPADIMO

Method for fitting a cellwise robust linear M-regression model (CRM, Filzmoser et al. (2020) <doi:10.1016/j.csda.2020.106944>) that yields both a map of cellwise outliers consistent with the linear model, and a vector of regression coefficients that is robust against vertical outliers and leverage points. As a by-product, the method yields an imputed data set that contains estimates of what the values in cellwise outliers would need to amount to if they had fit the model. The package also provides diagnostic tools for analyzing casewise and cellwise outliers using sparse directions of maximal outlyingness (SPADIMO, Debruyne et al. (2019) <doi:10.1007/s11222-018-9831-5>).

Authors:Peter Filzmoser [aut], Sebastiaan Hoppner [aut, cre], Irene Ortner [aut], Sven Serneels [aut], Tim Verdonck [aut]

crmReg_1.0.4.tar.gz
crmReg_1.0.4.zip(r-4.7)crmReg_1.0.4.zip(r-4.6)crmReg_1.0.4.zip(r-4.5)
crmReg_1.0.4.tgz(r-4.6-any)crmReg_1.0.4.tgz(r-4.5-any)
crmReg_1.0.4.tar.gz(r-4.7-any)crmReg_1.0.4.tar.gz(r-4.6-any)
crmReg_1.0.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
crmReg/json (API)

# Install 'crmReg' in R:
install.packages('crmReg', repos = c('https://sebastiaanhoppner.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.04 score 1 stars 11 scripts 581 downloads 5 exports 31 dependencies

Last updated from:5ecfbe43ec. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK130
source / vignettesOK150
linux-release-x86_64OK141
macos-release-arm64OK142
macos-oldrel-arm64OK172
windows-develOK106
windows-releaseOK92
windows-oldrelOK84
wasm-releaseOK97

Exports:cellwiseheatmapcrmdaprprpredict.crmspadimo

Dependencies:bitopscaToolsclicpp11DEoptimRfarverFNNggplot2gluegplotsgtablegtoolsisobandKernSmoothlabelinglatticelifecyclemvtnormpcaPPplyrR6RColorBrewerRcpprlangrobustbaserrcovS7scalesvctrsviridisLitewithr