pcoordplot-methos: Parallel coordinates plot.

In MAINT.Data: Model and Analyse Interval Data

Parallel coordinates plot.

Description

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

Usage

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

Arguments

x	An object of type “IdtMclust” representing the the clusterig results of an Interval-valued data set obtainde 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

See Also

IdtMclust, Idtmclust, plotInfCrt

Examples

## Not run: 

# 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")



## End(Not run)

MAINT.Data documentation built on April 4, 2023, 9:09 a.m.