kml3d (version 0.6)

Partition-class: ~ Class: Partition ~

Description

An object of class Partition is a list of cluster's names. Unlike a Clustering, a partition is *not* associate to a population.

Objects from the Class

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

validation rules

A class Partition object must follow some rules to be valid:

• Slots should be either all empty, or all non empty.
• nbClustershas to be lower or equal to 26 (twenty six clusters maximum).
• clustersis a factor inLETTERS[1:nbCluster].

Construction

Class Partition objects are mainly constructed by some clusterization methods (like k-means, fuzzy k-means, mixture modeling, latent class analysis,...) Neverdeless, it is also possible to construct them from scratch using the fonction partition.

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

See Also

Overview: kml3d-package Classes: LongData Methods: partition

Examples

### Building Partition
part <- partition(rep(c("A","B","A"),time=10),nbClusters=3)

### Get
part["clusters"]
part["nbClusters"]

### Set
part["nbClusters"]<-2
print(part)