| plotAll,ClusterizLongData {kml} | R Documentation |
plot the trajectories, the Calinski's criterions and the
subgroups of an object ClusterizLongData on a
single graph.
plotAll(x, y, ...)
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 Clusterization of the sublist c y is
selected. If y is a couple of numeric, the y[2]th
Clusterization of the sublist c y[1] is selected. |
... |
Graphical
parameters to be passed to methods (see plot). For
ClusterizLongData object specificly :
|
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).
Christophe Genolini
PSIGIAM: Paris Sud Innovation Group in Adolescent Mental Health
INSERM U669 / Maison de Solenn / Paris
Contact author : <genolini@u-paris10.fr>
Raphaël Ricaud
Laboratoire "Sport & Culture" / "Sports & Culture" Laboratory
University of Paris 10 / Nanterre
Article submited
Web site: http://christophe.genolini.free.fr/kml
Overview: kml-package
Classes : ClusterizLongData, ArtificialLongData
Plot : plot: overview, plot(ClusterizLongData),
plot(Calinski), plotSubGroups(ClusterizLongData)
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)