Package: CerioliOutlierDetection 1.1.13

CerioliOutlierDetection: Outlier Detection Using the Iterated RMCD Method of Cerioli (2010)

Implements the iterated RMCD method of Cerioli (2010) for multivariate outlier detection via robust Mahalanobis distances. Also provides the finite-sample RMCD method discussed in the paper, as well as the methods provided in Hardin and Rocke (2005) <doi:10.1198/106186005X77685> and Green and Martin (2017).

Authors:Christopher G. Green [aut, cre], R. Doug Martin [ths]

CerioliOutlierDetection_1.1.13.tar.gz
CerioliOutlierDetection_1.1.13.zip(r-4.7)CerioliOutlierDetection_1.1.13.zip(r-4.6)CerioliOutlierDetection_1.1.13.zip(r-4.5)
CerioliOutlierDetection_1.1.13.tgz(r-4.6-any)CerioliOutlierDetection_1.1.13.tgz(r-4.5-any)
CerioliOutlierDetection_1.1.13.tar.gz(r-4.6-any)
CerioliOutlierDetection_1.1.13.tgz(r-4.5-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
CerioliOutlierDetection/json (API)

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

Bug tracker:https://github.com/christopherggreen/ceriolioutlierdetection/issues

On CRAN:

Conda:

3.07 score 9 stars 13 scripts 342 downloads 6 exports 2 dependencies

Last updated from:cb1764f61f. Checks:7 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64NOTE122
source / vignettesOK155
linux-release-x86_64NOTE119
macos-release-arm64NOTE137
macos-oldrel-arm64NOTE167
windows-develNOTE92
windows-releaseNOTE56
windows-oldrelNOTE60
wasm-releaseOK84

Exports:cerioli2010.fsrmcd.testcerioli2010.irmcd.testch99AsymptoticDFhr05AdjustedDFhr05CriticalValuehr05CutoffMvnormal

Dependencies:DEoptimRrobustbase