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:
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')) |
- pheno - Phenotypic Risk Profiles of Toddlers
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:1a5ff126cc. Checks:6 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 126 | ||
| source / vignettes | OK | 156 | ||
| linux-release | OK | 160 | ||
| windows-devel | OK | 60 | ||
| windows-release | OK | 70 | ||
| wasm-release | OK | 107 |
Exports:mvoutplot.mvoutpredict.mvoutprint.mvout
Dependencies:DEoptimRrobustbase
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Robust Multivariate Outlier Detection | mvout |
| Phenotypic Risk Profiles of Toddlers | pheno |
| Plot Method for mvout Objects | plot.mvout |
| Predict method for Robust Multivariate Outlier Detection | predict.mvout |
| Print method for Robust Multivariate Outlier Detection | print.mvout |