longitudinalData (version 2.4.7)

longitudinalData-package: ~ Package overview: longitudinalData ~

Description

longitudinalData package provide some tools to deal with the clusterization of longitudinal data.

Overview

longitudinalData provide some tools to deal with the clustering of longitudinal data, mainly:

1. plotTrajMeans

2. imputation

3. qualityCriterion

Author

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

Details

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

References

[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

See Also

Classes: LongData, Partition
Methods: longData, partition, ordered
Plot: plotTrajMeans, plotTrajMeans3d
Imputation: imputation
Criterion: qualityCriterion

Examples

### 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)