Package: HDoutliers 1.0.4
Chris Fraley
HDoutliers: Leland Wilkinson's Algorithm for Detecting Multidimensional Outliers
An implementation of an algorithm for outlier detection that can handle a) data with a mixed categorical and continuous variables, b) many columns of data, c) many rows of data, d) outliers that mask other outliers, and e) both unidimensional and multidimensional datasets. Unlike ad hoc methods found in many machine learning papers, HDoutliers is based on a distributional model that uses probabilities to determine outliers.
Authors:
HDoutliers_1.0.4.tar.gz
HDoutliers_1.0.4.tar.gz(r-4.5-noble)HDoutliers_1.0.4.tar.gz(r-4.4-noble)
HDoutliers_1.0.4.tgz(r-4.4-emscripten)HDoutliers_1.0.4.tgz(r-4.3-emscripten)
HDoutliers.pdf |HDoutliers.html✨
HDoutliers/json (API)
| # Install 'HDoutliers' in R: |
| install.packages('HDoutliers', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 3 years agofrom:088fc14ca2. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 11 2024 |
| R-4.5-linux | OK | Nov 11 2024 |
Exports:dataTransgetHDmembersgetHDoutliersHDoutliersplotHDoutliers
Dependencies:abindbackportsbase64encbootbroombslibcachemcarcarDatacliclustercolorspacecowplotcpp11crosstalkDerivdigestdoBydplyrDTellipseemmeansestimabilityevaluateFactoMineRfansifarverfastmapflashClustFNNfontawesomeFormulafsgenericsggplot2ggrepelgluegtablehighrhtmltoolshtmlwidgetshttpuvisobandjquerylibjsonliteknitrlabelinglaterlatticelazyevalleapslifecyclelme4magrittrMASSMatrixMatrixModelsmclustmemoisemgcvmicrobenchmarkmimeminqamodelrmultcompViewmunsellmvtnormnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigpromisespurrrquantregR6rappdirsRColorBrewerRcppRcppEigenrlangrmarkdownsassscalesscatterplot3dSparseMstringistringrsurvivaltibbletidyrtidyselecttinytexutf8vctrsviridisLitewithrxfunyaml
