# loading of the RSDA package
library(RSDA)
# loading of the interval data set as a symbolic table
sPig<-read.sym.table("~/CSBIGS/R/sPigIEQ.txt",header=TRUE,sep='\t',dec='.',row.names=1)
sPig
# running symbolic PCA with the 'tops' method
tops_pca <- sym.pca(sPig, 'tops')
# displaying the sybolic objects ("ind" option) on the first factorial plan (F1xF2 components)
plot(res_tops,choix="ind") 
# loading of the interval data set as a standard table
Pig<-read.table("~/CSBIGS/R/PigIEQ.txt",sep='\t', header=TRUE, row.names=1)
View(Pig)
# loading of the clustering procedure
library(divclust)
# running the clustering procedure
Tree <- divclust(Pig)
# viewing the clustering results
plot(Tree)