kml3d (version 0.7)

Clustering-class: ~ Class: Clustering ~

Description

An object of class Clustering is a partition of a population into subgroups. The object also contains some information like the percentage of trajectories in each group or some qualities criterion.

Objects from the Class

Objects are mainly intend to be created by some clusterization methods (like k-means, fuzzy k-means...)

Construction

Class Clustering objects are mainly constructed by some clustering methods (like k-means, fuzzy k-means,...) Neverdeless, it is also possible to construct them from scratch using the fonction clustering.

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]

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

### Building Clustering
part <- partition(rep(c("A","B","A"),time=10),nbClusters=2)
myTraj <- as.longData(array(rnorm(30*5*2),dim=c(30,5,2)))

clus <- clustering(myTraj,part)

### Get
clus["clusters"]
clus["percentEachCluster"]

### Set
clus["multiplicity"]<-2