R: ~ Function: plotMeans for ClusterLongData ~

plotMeans,ClusterLongData {kml} | R Documentation

## ~ Function: plotMeans for ClusterLongData ~

### Description

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

### Usage

    ## S4 method for signature '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

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

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

    ### Basic plotMeansting
    plotMeans(ld,3)

[Package kml version 2.4.1 Index]