kml (version 0.9.2)

plotAll,ClusterizLongData: ~ Function: plotAll for ClusterizLongData ~

Description

plot the trajectories, the Calinski's criterions and the subgroups of an object ClusterizLongData on a single graph.

Usage

plotAll(x, y, ...)

Arguments

x

[ClusterizLongData] Object containing the trajectories to plot.

y

[numeric] or [vector(numeric)] Give the Clusterization to represent. If y is missing, the Clusterization with the highest Calinski creterion is selected. If y is a number, the first

...

Graphical parameters to be passed to methods (see plot). For ClusterizLongData object specificly : [object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[ob

Author(s)

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

English translation

Rapha�l Ricaud Laboratoire "Sport & Culture" / "Sports & Culture" Laboratory University of Paris 10 / Nanterre

Details

For every clusterizLongData object, there is three possible graphical representation: calinski criterion, all the trajectories at once and trajectories clusters by clusters. This function combine these three graphical output (or only two, or one, accorind to the three arguments printCal, printTraj and printSub). Thus every option (like colorMean,...) are duplicate : one is for the main graph (colorMean), the second is for the sub-graphs (colorMeanSub).

References

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

See Also

Overview: kml-package Classes : ClusterizLongData, ArtificialLongData Plot : plot: overview, plot(ClusterizLongData), plot(Calinski), plotSubGroups(ClusterizLongData)

Examples

ld <- gald()
kml(ld,2:5,5)
kml(ld,16,5)
par(ask=TRUE)

### Default ploting
plotAll(ld)

### Only the calinski criterion (same effect than plotCalinski(ld))
plotAll(ld,printCal=TRUE,printTraj=FALSE,printSub=FALSE)

### Groups and sub-groups
plotAll(ld,printCal=FALSE,printTraj=TRUE,printSub=TRUE)
plotAll(ld,printCal=FALSE,printTraj=TRUE,printSub=TRUE,colorTraj="black",colorMean="no",colorMeanSub="black")

### All at once
plotAll(ld,printCal=TRUE,printTraj=TRUE,printSub=TRUE)

### To see the clusterization with only 2 clusters
plotAll(ld,2,printCal=FALSE,printTraj=TRUE,printSub=TRUE)

### To see the third clusterization with 16 clusters
plotAll(ld,c(16,3),printCal=FALSE,printTraj=TRUE,printSub=TRUE)

par(ask=FALSE)