| plotInterval {clusterSim} | R Documentation |
Plot symbolic interval-valued data on a scatterplot matrix (optionally with clusters)
plotInterval(x, pairsofsVar=NULL, cl=NULL, clColors=NULL,...)
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). |
Marek Walesiak Marek.Walesiak@ae.jgora.pl, Andrzej Dudek Andrzej.Dudek@ae.jgora.pl
Department of Econometrics and Computer Science, University of Economics, Wroclaw, Poland http://www.ae.jgora.pl/keii
plotCategorial,plotCategorial3d, colors, pairs
# 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"))