kml3d (version 0.7)

regroup: ~ Function: regroup ~

Description

Remove duplicate Clustering present in a ClusterLongDataor in a ListClustering.

Usage

regroup(object,toOrder=TRUE)

Arguments

object

[ClusterLongData] or [ListClustering]: object that should be simplified.

toOrder

[logical]: shall the Clustering be ordered before regouped?

Value

• None (this function change internaly the field of an object, it does not return any values.)

Author(s)

Christophe Genolini INSERM U669 / PSIGIAM: Paris Sud Innovation Group in Adolescent Mental Health Modal'X / Universite Paris Ouest-Nanterre- La Defense Contact author : [e-mail]

Details

A clusterizing algorithm can find a Clustering several time. It is store several time in object ClusterLongData, encombering the memory. regroup remove the duplicate Clustering. Note that if the ClusterLongData is not ordered, then regroup sort it unless toOrder=FALSE.

References

Article "KmL: K-means for Longitudinal Data", in Computational Statistics, Volume 25, Issue 2 (2010), Page 317. Web site: http://christophe.genolini.free.fr/kml

Examples

### Some data easy to cluster
myCld <- gald(c(15,15,15),functionNoise=function(t){c(rnorm(1,0,1),rnorm(1,0,1))})

### run kml3d
kml3d(myCld,,3)
plot(myCld)

### Some clustering has been found several time
### regroup will suppress the duplicate one
regroup(myCld)
plot(myCld)