Package: kml 2.5.0

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:Christophe Genolini [cre, aut], Bruno Falissard [ctb], Patrice Kiener [ctb]

kml_2.5.0.tar.gz
kml_2.5.0.zip(r-4.5)kml_2.5.0.zip(r-4.4)kml_2.5.0.zip(r-4.3)
kml_2.5.0.tgz(r-4.4-x86_64)kml_2.5.0.tgz(r-4.4-arm64)kml_2.5.0.tgz(r-4.3-x86_64)kml_2.5.0.tgz(r-4.3-arm64)
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://christophe314.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

3.97 score 2 packages 78 scripts 906 downloads 13 mentions 29 exports 35 dependencies

Last updated 6 days agofrom:dfb9b828d7. Checks:OK: 3 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 24 2024
R-4.5-win-x86_64OKOct 24 2024
R-4.5-linux-x86_64OKOct 24 2024
R-4.4-win-x86_64NOTEOct 24 2024
R-4.4-mac-x86_64NOTEOct 24 2024
R-4.4-mac-aarch64NOTEOct 24 2024
R-4.3-win-x86_64NOTEOct 24 2024
R-4.3-mac-x86_64NOTEOct 24 2024
R-4.3-mac-aarch64NOTEOct 24 2024

Exports:affectFuzzyIndivaffectIndivaffectIndivCcalculTrajFuzzyMeancalculTrajMeancalculTrajMeanCchoicechoiceChangeParamcldclusterLongDatacutScreenexpandStartingCondexportPartitionfastOrSlowfuzzyKmlSlowgaldgenerateArtificialLongDatagetBestPostProbagetClusterskmlkmlFastlegendColparALGOparKmlpartPermutplotplotLegendplotMeansplotTraj

Dependencies:base64encbslibcachemclasscliclusterclvdigestevaluatefastmapfontawesomefsgluehighrhtmltoolshtmlwidgetsjquerylibjsonliteknitrlifecyclelongitudinalDatamagrittrMASSmemoisemimemisc3dR6rappdirsrglrlangrmarkdownsasstinytexxfunyaml

Readme and manuals

Help Manual

Help pageTopics
~ 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