Package: unusualprofile 0.1.4

unusualprofile: Calculates Conditional Mahalanobis Distances
Calculates a Mahalanobis distance for every row of a set of outcome variables (Mahalanobis, 1936 <doi:10.1007/s13171-019-00164-5>). The conditional Mahalanobis distance is calculated using a conditional covariance matrix (i.e., a covariance matrix of the outcome variables after controlling for a set of predictors). Plotting the output of the cond_maha() function can help identify which elements of a profile are unusual after controlling for the predictors.
Authors:
unusualprofile_0.1.4.tar.gz
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unusualprofile_0.1.4.tgz(r-4.6-any)unusualprofile_0.1.4.tgz(r-4.5-any)
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manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
unusualprofile/json (API)
| # Install 'unusualprofile' in R: |
| install.packages('unusualprofile', repos = c('https://wjschne.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/wjschne/unusualprofile/issues
Pkgdown/docs site:https://wjschne.github.io
Last updated from:8fe3bfe829. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 153 | ||
| source / vignettes | OK | 277 | ||
| linux-release-x86_64 | OK | 160 | ||
| macos-release-arm64 | OK | 109 | ||
| macos-oldrel-arm64 | OK | 125 | ||
| windows-devel | OK | 157 | ||
| windows-release | OK | 111 | ||
| windows-oldrel | OK | 120 | ||
| wasm-release | OK | 124 |
Exports:cond_mahais_singularp2labelproportion_roundproportion2percentile
Dependencies:clicpp11dplyrfarvergenericsggnormalviolinggplot2gluegtableisobandlabelinglifecyclemagrittrpillarpkgconfigpurrrR6RColorBrewerrlangS7scalesstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithr
Last update: 2025-08-23
Started: 2025-08-17
Last update: 2025-08-23
Started: 2025-08-17
