stability: Stability of partitions from a hierarchy of variables

In ClustOfVar: Clustering of Variables

Description

Evaluates the stability of partitions obtained from a hierarchy of p variables. This hierarchy is performed with hclustvar and the stability of the partitions of 2 to p-1 clusters is evaluated with a bootstrap approach. The boostrap approch is the following: hclustvar is applied to B boostrap samples of the n rows. The partitions of 2 to p-1 clusters obtained from the B bootstrap hierarchies are compared with the partitions from the initial hierarchy . The mean of the corrected Rand indices is plotted according to the number of clusters. This graphical representation helps in the determination of a suitable numbers of clusters.

Usage

stability(tree, B = 100, graph = TRUE)

Arguments

tree	an object of class hclustvar.
B	the number of bootstrap samples.
graph	boolean, if 'TRUE' a graph is displayed.

Value

matCR	matrix of corrected Rand indices.
meanCR	vector of mean corrected Rand indices.

See Also

plot.clustab, hclustvar

Examples

data(decathlon)
tree <- hclustvar(X.quanti=decathlon[,1:10])
stab<-stability(tree,B=20)
plot(stab,nmax=7)
boxplot(stab$matCR[,1:7])

ClustOfVar documentation built on May 2, 2019, 12:37 p.m.