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@ue.wroc.pl, Andrzej Dudek andrzej.dudek@ue.wroc.pl
Department of Econometrics and Computer Science, University of Economics, Wroclaw, Poland http://keii.ue.wroc.pl/clusterSim
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"))