plotInterval: Plot symbolic interval-valued data on a scatterplot matrix

In clusterSim: Searching for Optimal Clustering Procedure for a Data Set

Plot symbolic interval-valued data on a scatterplot matrix

Description

Plot symbolic interval-valued data on a scatterplot matrix (optionally with clusters)

Usage

plotInterval(x, pairsofsVar=NULL, cl=NULL, clColors=NULL,...)

Arguments

x	symbolic interval-valued data
pairsofsVar	pairs of symbolic interval variables - all variables (pairsofsVar=NULL) or selected variables, e.g. pairsofsVar=c(1,3,4)
cl	cluster membership vector
clColors	The colors of clusters. The colors are given arbitrary (clColors=TRUE) or by hand, e.g. clColors=c("red","blue","green"). The number of colors equals the number of clusters
...	Arguments to be passed to methods, such as graphical parameters (see par).

Author(s)

Marek Walesiak [e-mail], Andrzej Dudek [e-mail]

Department of Econometrics and Computer Science, University of Economics, Wroclaw, Poland http://keii.ue.wroc.pl/clusterSim/

See Also

plotCategorial, colors, pairs

Examples

# Example 1
library(clusterSim)
data(data_symbolic)
plotInterval(data_symbolic, pairsofsVar=c(1,3,4,6), cl=NULL,
clColors=NULL)

# Example 2
library(clusterSim)
grnd <- cluster.Gen(60, model=5, dataType="s", numNoisyVar=1, 
numOutliers=10, rangeOutliers=c(1,5))
grnd$clusters[grnd$clusters==0] <- max(grnd$clusters)+1			
# To colour outliers
plotInterval(grnd$data, pairsofsVar=NULL, cl=grnd$clusters,
clColors=TRUE)

# Example 3
library(clusterSim)
grnd <- cluster.Gen(50, model=4, dataType="s", numNoisyVar=2, 
numOutliers=10, rangeOutliers=c(1,4))
grnd$clusters[grnd$clusters==0] <- max(grnd$clusters)+1			
# To colour outliers
plotInterval(grnd$data, pairsofsVar=NULL, cl=grnd$clusters, 
clColors=c("red","blue","green","yellow"))

clusterSim documentation built on July 9, 2023, 7:54 p.m.