kml (version 1.1.3)

plot,ClusterizLongData: ~ Function: plot for ClusterizLongData ~

Description

plot the trajectories of an object ClusterizLongData relativly to a Clusterization.

Usage

## S3 method for class 'ClusterizLongData,ANY':
plot(x,y,col="clusters",col.mean="clusters",main="",type="l",type.mean="",size=1,...)

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 quality criterion is selected. If y is a number, the first

col

[character], [numeric] or vector[numeric]: Specification of the ploting color of the individual trajectories. In addition to the standard possibles values, col="clusters" can be use to color the individual trajectories according to their cl

col.mean

[character], [numeric] or vector[numeric]: Specification of the ploting color of the mean trajectories. In addition to the standard possibles values, col="clusters" can be use to color each mean trajectories according to its clusters.

main

[charater]: give the title of the graph.

type

[character]: what type of plot should be drawn for the individual trajectories.

type.mean

[character]: what type of plot should be drawn for the mean trajectories ?

size

[numeric]: If some point are added on the mean trajectories, size fixe the size of the point.

...

Graphical parameters to be passed to methods, see plot(LongData) and par for details.

Author(s)

Christophe M. 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

plot the trajectories of an object ClusterizLongData relativly to a Clusterization.

References

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

See Also

Overview: kml-package Classes : ClusterizLongData Plot : plot: overview, plotCriterion), plotSubGroups(ClusterizLongData), plotAll(ClusterizLongData)

Examples

clusLd <- as.cld(gald())
kml(clusLd,,1)
par(ask=TRUE)

### Default ploting
plot(clusLd)

### Only the trajectories in black
plot(clusLd,type="n",col.mean="1",type.mean="l")

### Only the mean trajectories, with letters (for publication ?)
plot(clusLd,type="n",col.mean="1",type.mean="b",cex=2)

### All at once.
plot(clusLd,col="clusters",col.mean="clusters",type.mean="l",legend=FALSE)

par(ask=FALSE)