Package: mvout 1.2

Nathaniel E. Helwig

mvout: Robust Multivariate Outlier Detection

Detection of multivariate outliers using robust estimates of location and scale. The Minimum Covariance Determinant (MCD) estimator is used to calculate robust estimates of the mean vector and covariance matrix. Outliers are determined based on robust Mahalanobis distances using either an unstructured covariance matrix, a principal components structured covariance matrix, or a factor analysis structured covariance matrix. Includes options for specifying the direction of interest for outlier detection for each variable.

Authors:Jesus E. Delgado [aut], Jed T. Elison [ctb], Nathaniel E. Helwig [aut, cre]

mvout_1.2.tar.gz
mvout_1.2.zip(r-4.7-any)mvout_1.2.zip(r-4.6-any)
mvout_1.2.tar.gz(r-4.7-any)mvout_1.2.tar.gz(r-4.6-any)
mvout_1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
mvout/json (API)

# Install 'mvout' in R:
install.packages('mvout', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • pheno - Phenotypic Risk Profiles of Toddlers

On CRAN:

Conda:

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

1.00 score 2 scripts 383 downloads 4 exports 2 dependencies

Last updated from:1a5ff126cc. Checks:6 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK126
source / vignettesOK156
linux-releaseOK160
windows-develOK60
windows-releaseOK70
wasm-releaseOK107

Exports:mvoutplot.mvoutpredict.mvoutprint.mvout

Dependencies:DEoptimRrobustbase