~ Package overview: longitudinalData ~
longitudinalData package provide some tools to deal with the clusterization
of longitudinal data.
| Package: | longitudinalData |
| Type: | Package |
| Version: | 2.4.1 |
| Date: | 2016-02-02 |
| License: | GPL (>= 2) |
| LazyData: | yes |
| Depends: | methods,clv,rgl,misc3d |
| URL: | http://www.r-project.org |
longitudinalData provide some tools to deal with the clustering of longitudinal data, mainly:
Christophe Genolini
1. UMR U1027, INSERM, Université Paul Sabatier / Toulouse III / France
2. CeRSM, EA 2931, UFR STAPS, Université de Paris Ouest-Nanterre-La Défense / Nanterre / France
[1] Christophe M. Genolini and Bruno Falissard
"KmL: k-means for longitudinal data"
Computational Statistics, vol 25(2), pp 317-328, 2010
[2] Christophe M. Genolini and Bruno Falissard
"KmL: A package to cluster longitudinal data"
Computer Methods and Programs in Biomedicine, 104, pp e112-121, 2011
Classes: LongData, Partition
Methods: longData, partition, ordered
Plot: plotTrajMeans, plotTrajMeans3d
Imputation: imputation
Criterion: qualityCriterion
### Generation of artificial longData data(artificialJointLongData) myData <- longData3d(artificialJointLongData,timeInData=list(var1=2:12,var2=13:23,var3=24:34)) part <- partition(rep(1:3,each=50)) plotTrajMeans3d(myData,part) ### Quality criterion qualityCriterion(myData,part)
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