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-any)crmReg_1.0.4.zip(r-4.6-any)crmReg_1.0.4.zip(r-4.5-any)
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✨
DESCRIPTION
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.

1.20 score 1 stars 11 scripts 1.5k downloads 5 exports 31 dependencies

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

TargetResultTimeFilesSyslog
linux-develOK143
source / vignettesOK200
linux-releaseOK110
macos-releaseOK173
macos-oldrelOK182
windows-develOK108
windows-releaseOK68
windows-oldrelOK85
wasm-releaseOK94

Exports:cellwiseheatmapcrmdaprprpredict.crmspadimo

Dependencies:bitopscaToolsclicpp11DEoptimRfarverFNNggplot2gluegplotsgtablegtoolsisobandKernSmoothlabelinglatticelifecyclemvtnormpcaPPplyrR6RColorBrewerRcpprlangrobustbaserrcovS7scalesvctrsviridisLitewithr