GDAtools (version 1.5)

medoids: Computes the medoids of clusters

Description

Computes the medoids of a cluster solution.

Usage

medoids(D, cl)

Arguments

D

square distance matrix (n rows * n columns, i.e. n individuals) or dist object

cl

vector with the clustering solution (its length should be n)

Value

Returns a numeric vector with the indexes of medoids.

Details

Medoids are representative objects of a cluster whose average dissimilarity to all the objects in the cluster is minimal. Medoids are always members of the data set (contrary to means or centroids).

References

Kaufman, L. and Rousseeuw, P.J. (1990). Finding Groups in Data: An Introduction to Cluster Analysis. Wiley, New York.

Anja Struyf, Mia Hubert & Peter J. Rousseeuw (1996). "Clustering in an Object-Oriented Environment". Journal of Statistical Software.

See Also

dist, cluster, hclust, cutree , pam

Examples

# NOT RUN {
## Performs of classification of the 'Music' example data set, 
## a clustering in 3 groups
## and then computes the medoids.
data(Music)
temp <- dichotom(Music[,1:5])
d <- dist(temp)
clus <- cutree(hclust(d),3)
medoids(d,clus)
# }