Package: dbrobust 1.1.1
Eva Boj
dbrobust: Robust Distance-Based Visualization and Analysis of Mixed-Type Data
Robust distance-based methods applied to matrices and data frames, producing distance matrices that can be used as input for various visualization techniques such as graphs, heatmaps, or multidimensional scaling configurations. See Boj and Grané (2024) <doi:10.1016/j.seps.2024.101992>, Boj et al. (2026) <doi:10.1007/s10260-026-00860-1>, and Grané et al. (2026) <doi:10.1007/s10182-026-00565-6>.
Authors:
dbrobust_1.1.1.tar.gz
dbrobust_1.1.1.zip(r-4.7-x86_64)dbrobust_1.1.1.zip(r-4.7-arm64)dbrobust_1.1.1.zip(r-4.6-x86_64)dbrobust_1.1.1.zip(r-4.6-arm64)
dbrobust_1.1.1.tar.gz(r-4.7-arm64)dbrobust_1.1.1.tar.gz(r-4.7-x86_64)dbrobust_1.1.1.tar.gz(r-4.6-arm64)dbrobust_1.1.1.tar.gz(r-4.6-x86_64)
dbrobust_1.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
dbrobust/json (API)
| # Install 'dbrobust' in R: |
| install.packages('dbrobust', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- Data_HC_contamination - High-correlation dataset with contamination
- Data_HC_no_contamination - High-correlation dataset without contamination
- Data_MC_contamination - Moderate-correlation dataset with contamination
- Data_MC_no_contamination - Moderate-correlation dataset without contamination
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:ebfb0d7c6e. Checks:10 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 182 | ||
| linux-devel-x86_64 | OK | 207 | ||
| source / vignettes | OK | 250 | ||
| linux-release-arm64 | OK | 208 | ||
| linux-release-x86_64 | OK | 216 | ||
| windows-devel-arm64 | OK | 272 | ||
| windows-devel-x86_64 | OK | 199 | ||
| windows-release-arm64 | OK | 264 | ||
| windows-release-x86_64 | OK | 145 | ||
| wasm-release | OK | 165 |
Exports:calculate_distancesmake_euclideanmerge_distancesrobust_distancesvisualize_distances
Dependencies:abindade4backportsbase64encbslibcachemcheckmatecliclustercolorspacecorpcorcpp11crayondata.tableDBIdbstatsdigestdplyrevaluatefarverfastmapfdrtoolfontawesomeforcatsforeignFormulafsgenericsGGallyggplot2ggstatsglassoglueGPArotationgridExtragtablegtoolshighrHmischmshtmlTablehtmltoolshtmlwidgetsigraphisobandjpegjquerylibjsonliteknitrlabelinglatticelavaanlifecyclelpSolvemagrittrMASSMatrixmemoisemgcvmimeminqamitoolsmnormtnlmennetnumDerivpatchworkpbapplypbivnormpermutepheatmappillarpixmappkgconfigplsplyrpngprettyunitsprogressproxypsychpurrrqgraphquadprogR6rappdirsrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreshape2rlangrmarkdownrpartRSpectrarstudioapiS7sassscalesspStatMatchstringistringrsurveysurvivaltibbletidyrtidyselecttinytexutf8vctrsveganviridisLitewithrxfunyaml
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Compute Distance or Similarity Matrices | calculate_distances |
| High-correlation dataset with contamination | Data_HC_contamination |
| High-correlation dataset without contamination | Data_HC_no_contamination |
| Moderate-correlation dataset with contamination | Data_MC_contamination |
| Moderate-correlation dataset without contamination | Data_MC_no_contamination |
| Force a Pairwise Squared Distance Matrix to Euclidean Form | make_euclidean |
| Multi-Source Distance Combination and Fusion via Global RelMS | merge_distances |
| Compute Robust Squared Distances for Mixed Data | robust_distances |
| Visualize Distance Matrices via MDS, Heatmap, or Network Graph | visualize_distances |