MAINT.Data (version 2.8.0)

pcoordplot-methods: Parallel coordinates plot.

Description

Method pcoordplot displays a parallel coordinates plot, representing the results stored in an IdtMclust-method object.

Usage

# S4 method for IdtMclust
pcoordplot(x,title="Parallel Coordinate Plot",
Seq=c("AllMidP_AllLogR","MidPLogR_VarbyVar"), model ="BestModel", 
legendpar=list(), Components = "All", ...)

Arguments

x

An object of type “IdtMclust” representing the the clusterig
results of an Interval-valued data set obtained by the function “IdtMclust”.

title

The title of the plot.

Seq

The ordering of the coordinates in the plot. Available options are:
“AllMidP_AllLogR”: all MidPoints followed all LogRanges, in the same variable order.
“MidPLogR_VarbyVar”: MidPoints followed by LogRanges, variable by variable.

model

A character vector specifying the the model whose solution is to be displayed.

legendpar

A named list with graphical parameters for the plot legend. Currently only the base R ‘cex.main’ and ‘cex.lab’ parameters are implemented.

...

Graphical arguments to be passed to methods

Components

The set of components to be compared

See Also

IdtMclust, Idtmclust, plotInfCrt

Examples

if (FALSE) {

# Create an Interval-Data object containing the intervals of loan data
# (from the Kaggle Data Science platform) aggregated by loan purpose

LbyPIdt <- IData(LoansbyPurpose_minmaxDt,
                 VarNames=c("ln-inc","ln-revolbal","open-acc","total-acc")) 


#Fit homoscedastic Gaussian mixtures with up to ten components

mclustres <- Idtmclust(LbyPIdt,G=1:10)
plotInfCrt(mclustres,legpos="bottomright")

#Display the results of the best mixture according to the BIC

pcoordplot(mclustres)
pcoordplot(mclustres,model="HomG6C1")
pcoordplot(mclustres,model="HomG4C1")


}