# illustrate hierarchical clustering for ruspini data

x1<-matrix(scan('ruspini.txt'),byrow=T,ncol=2)
plot(x1)
y1<-dist(x1,method='euclidean')
y2<-hclust(y1,method='single')

# The next command shows the dendogram (adjust print size via cex)
plot(y2,cex=0.7)

# model-based clustering (first install package mclust, then load it)
mc1<-Mclust(x1)

# sequence of plots 
plot(mc1,data=x1)