Package: DiscreteGapStatistic 1.0.1
DiscreteGapStatistic: An Extension of the Gap Statistic for Ordinal/Categorical Data
The gap statistic approach is extended to estimate the number of clusters for categorical response format data. This approach and accompanying software is designed to be used with the output of any clustering algorithm and with distances specifically designed for categorical (i.e. multiple choice) or ordinal survey response data.
Authors:
DiscreteGapStatistic_1.0.1.tar.gz
DiscreteGapStatistic_1.0.1.zip(r-4.5)DiscreteGapStatistic_1.0.1.zip(r-4.4)DiscreteGapStatistic_1.0.1.zip(r-4.3)
DiscreteGapStatistic_1.0.1.tgz(r-4.5-any)DiscreteGapStatistic_1.0.1.tgz(r-4.4-any)DiscreteGapStatistic_1.0.1.tgz(r-4.3-any)
DiscreteGapStatistic_1.0.1.tar.gz(r-4.5-noble)DiscreteGapStatistic_1.0.1.tar.gz(r-4.4-noble)
DiscreteGapStatistic_1.0.1.tgz(r-4.4-emscripten)DiscreteGapStatistic_1.0.1.tgz(r-4.3-emscripten)
DiscreteGapStatistic.pdf |DiscreteGapStatistic.html✨
DiscreteGapStatistic/json (API)
| # Install 'DiscreteGapStatistic' in R: |
| install.packages('DiscreteGapStatistic', repos = c('https://ecortesgomez.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/ecortesgomez/discretegapstatistic/issues
- concussion - Concussion Data
- mass - Mass data
Last updated 24 days agofrom:6376225e34. Checks:9 OK. Indexed: yes.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Mar 06 2025 |
| R-4.5-win | OK | Mar 06 2025 |
| R-4.5-mac | OK | Mar 06 2025 |
| R-4.5-linux | OK | Mar 06 2025 |
| R-4.4-win | OK | Mar 06 2025 |
| R-4.4-mac | OK | Mar 06 2025 |
| R-4.4-linux | OK | Mar 06 2025 |
| R-4.3-win | OK | Mar 06 2025 |
| R-4.3-mac | OK | Mar 06 2025 |
Exports:BhattacharyyaDistChisqDistclusGapDiscrclusterFunSelcramersVmodCramerVdissbhattacharyyadisschisquaredisscramervdisshammingdisshellingerdistanceHeatdistancematrixfindKHellingerDistkmodesDlikert.heat.plot2ResHeatmapSimData
Dependencies:backportsbase64encBiocGenericsbslibcachemcheckmatecirclizecliclueclustercodetoolscolorspacecombinatComplexHeatmapcpp11crayoncultevodata.tabledigestdoParalleldplyrevaluatefansifarverfastmapfontawesomeforeachforeignFormulafsgenericsGetoptLongggplot2GlobalOptionsgluegridExtragtablehighrHmischtmlTablehtmltoolshtmlwidgetsIRangesisobanditeratorsjquerylibjsonliteknitrlabelinglatticelifecyclemagrittrMASSMatrixmatrixStatsmemoisemgcvmimemunsellnlmennetpheatmappillarpkgconfigplyrpngPolychromepspearmanpurrrR6rappdirsRColorBrewerRcppreshape2rjsonrlangrmarkdownrpartrstudioapiS4Vectorssassscalesscatterplot3dshapestringistringrtibbletidyrtidyselecttinytexutf8vctrsviridisviridisLitewithrxfunyaml
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Bhattacharyya distance | BhattacharyyaDist |
| Chi-square distance | ChisqDist |
| Discrete application of clusGap | clusGapDiscr |
| Discrete application of clusGap - core function. | clusGapDiscr0 |
| Clustering generating function | clusterFunSel |
| Concussion Data | concussion |
| Cramer's V modified pairwise vector function based on the function found in lsr package | cramersVmod |
| Cramer's V distance | CramerV |
| Bhattacharyya's distance (wrapper) | dissbhattacharyya |
| Chi-square distance (wrapper) | disschisquare |
| Cramer's V distance (wrapper) | disscramerv |
| Hamming distance wrapper function | disshamming |
| Hellinger distance (wrapper) | disshellinger |
| Sample-to-sample heatmap | distanceHeat |
| Calculate categorical distance matrix for discrete data | distancematrix |
| Criteria to determine number of clusters k | findK |
| Hellinger distance | HellingerDist |
| Adapted k-modes algorithm | kmodesD |
| Summary Heatmap for categorical data | likert.heat.plot2 |
| mass data | mass |
| Discrete Data Heatmap | ResHeatmap |
| Simulate Data | SimData |
