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kml (version 2.4.6.1)

plotMeans,ClusterLongData: ~ Function: plotMeans for ClusterLongData ~

Description

plotMeans plots the means' trajectories of an object ClusterLongData relativly to a Partition.

Usage

# S4 method for ClusterLongData,ANY
plotMeans(x,y,parMean=parMEAN(),
   parWin=windowsCut(x['nbVar'],addLegend=TRUE),...)

Arguments

x

[ClusterLongData]: Object containing the trajectories to plotMeans.

y

[numeric] or [vector(numeric)]: Give the Partition to represent. If y is a number, the first Partition of the sublist c-y is selected. If y is a couple of numeric, the y[2]th Partition of the sublist c-y[1] is selected (so y=c(2,3) select the partition with 2 clusters, the third one).

parMean

[ParLongData]: Specification of the plotting parameters of the mean trajectories. Fields that can be changes are 'type','col','pch','pchPeriod' and 'cex'. See ParLongData for details.

parWin

[parWindows]: Set the graphical display of the windows. See ParWindows for details.

...

Some other parameters can be passed to the method.

Details

plotMeans plots the means' trajectories of an object ClusterLongData relativly to the 'best' Partition, or to the Partition define by y.

Graphical option (col, type, pch, pchPeriod and cex) can be change using parMean. For more detail on parTraj and parMean, see object of class ParLongData.

See Also

Overview: kml-package
Classes : ClusterLongData
PlotMeans : plotMeans: overview, plotCriterion

Examples

Run this code
### Move to tempdir
wd <- getwd()
setwd(tempdir()); getwd()

##################
### Construction of the data

ld <- gald(10)
kml(ld,3:4,2)

### Basic plotMeansting
plotMeans(ld,3)

### Go back to current dir
setwd(wd)

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