longitudinalData (version 2.0)

longitudinalData-package: ~ Package overview: longitudinalData ~

Description

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

Overview

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

1. plot
2. imputation
3. qualityCriterion

Author

Christophe Genolini 1. UMR U1027, INSERM, Universit� Paul Sabatier / Toulouse III / France 2. CeRSME, EA 2931, UFR STAPS, Universit� de Paris Ouest-Nanterre-La D�fense / Nanterre / France

Details

ll{ Package: longitudinalData Type: Package Version: 2.0 Date: 2012-04-01 License: GPL (>= 2) Lazyload: 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: plot(LongData), plot3d(LongData) Imputation: imputation Criterion: qualityCriterion

Examples

### Generation of artificial longData
data <- gald3d(percentOfMissing=0.3)
part <- partition(rep(1:3,each=50))
plot3d(data,part)

### Imputation
data1 <- imputation(data,method="copyMean")

### Quality criterion
# qualityCriterion(data,part)