Package: kml 2.5.0
Christophe Genolini
kml: K-Means for Longitudinal Data
An implementation of k-means specifically design to cluster longitudinal data. It provides facilities to deal with missing value, compute several quality criterion (Calinski and Harabatz, Ray and Turie, Davies and Bouldin, BIC, ...) and propose a graphical interface for choosing the 'best' number of clusters.
Authors:
kml_2.5.0.tar.gz
kml_2.5.0.tar.gz(r-4.5-noble)kml_2.5.0.tar.gz(r-4.4-noble)
kml_2.5.0.tgz(r-4.4-emscripten)kml_2.5.0.tgz(r-4.3-emscripten)
kml.pdf |kml.html✨
kml/json (API)
NEWS
| # Install 'kml' in R: |
| install.packages('kml', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- epipageShort - ~ Data: epipageShort ~
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 months agofrom:dfb9b828d7. Checks:OK: 2. Indexed: no.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 23 2024 |
| R-4.5-linux-x86_64 | OK | Nov 23 2024 |
Exports:affectFuzzyIndivaffectIndivaffectIndivCcalculTrajFuzzyMeancalculTrajMeancalculTrajMeanCchoicechoiceChangeParamcldclusterLongDatacutScreenexpandStartingCondexportPartitionfastOrSlowfuzzyKmlSlowgaldgenerateArtificialLongDatagetBestPostProbagetClusterskmlkmlFastlegendColparALGOparKmlpartPermutplotplotLegendplotMeansplotTraj
Dependencies:base64encbslibcachemclasscliclusterclvdigestevaluatefastmapfontawesomefsgluehighrhtmltoolshtmlwidgetsjquerylibjsonliteknitrlifecyclelongitudinalDatamagrittrMASSmemoisemimemisc3dR6rappdirsrglrlangrmarkdownsasstinytexxfunyaml
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| ~ Overview: K-means for Longitudinal data ~ | kml-package |
| ~ Function: affectFuzzyIndiv ~ | affectFuzzyIndiv |
| ~ Functions: affectIndiv & affectIndivC ~ | affectIndiv affectIndivC |
| ~ Function: calculTrajFuzzyMean ~ | calculTrajFuzzyMean |
| ~ Functions: calculTrajMean & calculTrajMeanC ~ | calculTrajMean calculTrajMeanC |
| ~ Function: choice ~ | choice choice,ClusterLongData-method [,ParChoice-method |
| ~ Function: clusterLongData (or cld) ~ | cld clusterLongData clusterLongData,ANY,ANY,ANY,ANY,ANY,ANY-method clusterLongData,missing,missing,missing,missing,missing,missing-method |
| ~ Class: ClusterLongData ~ | ClusterLongData-class is.na,ClusterLongData-method [,ClusterLongData-method [<-,ClusterLongData,character,missing,missing-method |
| ~ Data: epipageShort ~ | epipageShort |
| ~ Algorithm fuzzy kml: Fuzzy k-means for Longitidinal data ~ | fuzzyKmlSlow |
| ~ Function: generateArtificialLongData (or gald) ~ | gald generateArtificialLongData |
| ~ Function: getBestPostProba ~ | getBestPostProba |
| ~ Function: getClusters ~ | getClusters |
| ~ Algorithm kml: K-means for Longitidinal data ~ | kml kml,ClusterLongData-method |
| ~ Function: parKml ~ | parALGO parKml [,ParKml,ANY,ANY-method [<-,ParKml,ANY,ANY,ANY-method |
| ~ Class: "ParKml" ~ | ParKml-class [,ParKml-method [<-,ParKml-method |
| ~ Function: plot for ClusterLongData ~ | plot plot,ClusterLongData plot,ClusterLongData,ANY-method plot,ClusterLongData,missing-method plot,ClusterLongData,numeric-method plot,ClusterLongData,Partition-method |
| ~ Function: plotMeans for ClusterLongData ~ | plotMeans plotMeans,ClusterLongData plotMeans,ClusterLongData,ANY-method plotMeans,ClusterLongData,missing-method plotMeans,ClusterLongData,numeric-method plotMeans,ClusterLongData,Partition-method |
| ~ Function: plotTraj for ClusterLongData ~ | plotTraj plotTraj,ClusterLongData,ANY-method plotTraj,ClusterLongData,numeric-method |
