ArtificialLongData-class {kml}R Documentation

~ Class: ArtificialLongData ~

Description

ArtificialLongData is a class design to build up artificial data set in order to explore clusterization's algorithm properties.

Slots

name
[character]: name of the data set.
nbClusters
[numeric]: number of clusters
clusterNames
[character]: names of the clusters.
nbEachClusters
[numeric]: number of trajectories that compose each cluster.
time
[numeric]: time at which the measures are made.
functionClusters
[list(function)]: function list used to generate the average trajectory of each cluster.
functionNoise
[list(function)]: function list used to generate the noise of each trajectory within its own cluster.
trajMeanTheo
[matrix]: matrix containing the theoretical trajectories of each cluster, those that individuals would follow if they were not subject to individual variations.
trajMeanReal
[matrix]: matrix containing the average trajectories of each cluster, average trajectories that the individuals pursue indeed
id
[character]: single identifier for each individual.
varName
[character]: name of the variable which is being measured.
traj
[array(numeric)]: matrix of the trajectories of individuals. Each lign refers to an id, each column refers to a time.
percentOfMissing
[numeric]: percentage (between 0 and 1) of missing data generated in each cluster.

Construction

Objects can be created by calling generateArtificialLongData (or gald in short)

Get [ and set [<-

get and set are inherited from ClusterizLongData.

Methods

All the methods are inherited from ClusterizLongData.

Author(s)

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

Contact author : <genolini@u-paris10.fr>

English translation

Raphaël Ricaud
Laboratoire "Sport & Culture" / "Sports & Culture" Laboratory
University of Paris 10 / Nanterre

References

Article submited
Web site: http://christophe.genolini.free.fr/kml

See Also

Overview: kml-package
Classes : ClusterizLongData, Clusterization
Methods : kml, generateArtificialLongData, choice
Plot : plot: overview, plot(ClusterizLongData), plot(Calinski), plotSubGroups(ClusterizLongData), plotAll(ClusterizLongData)

Examples

showClass("ArtificialLongData")
gald()

[Package kml version 0.9.2 Index]