longitudinalData (version 0.6.4)

Partition-class: ~ Class: Partition ~

Description

An object of class Partition is a clusterization of LongData in subgroups.

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 52 (fifty two clusters maximum).
• clustersis a factor inLETTERS[1:nbCluster]ifnbClusters<=26< code="">, inc(LETTERS,letters[1:(nbCluster-26)])otherwise).

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 PSIGIAM: Paris Sud Innovation Group in Adolescent Mental Health INSERM U669 / Maison de Solenn / Paris Contact author :

References

Article submited

See Also

Overview: longitudinalData-package Classes: LongData Methods: partition

Examples

### Building Partition
part <- partition(rep(c("A","B","C"),time=10),nbClusters=4)

### '[' and '[<-'
part["clusters"]
part["nbClusters"]

part["nbClusters"]<-3
(part)