Computes the medoids of a cluster solution.

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`D` |
square distance matrix (n rows * n columns, i.e. n individuals) or |

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

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).

Returns a numeric vector with the indexes of medoids.

Nicolas Robette

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*.

`dist`

, `cluster`

, `hclust`

, `cutree`

, `pam`

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