rimle_clust {ICSClust}

Robust Improper Maximum Likelihood Clustering

Description

Wrapper for performing Robust Improper Maximum Likelihood Clustering clustering from otrimle::rimle().

Usage

rimle_clust(X, k, clusters_only = FALSE, ...)

Arguments

X

a numeric matrix or data frame of the data. It corresponds to the argument data.

k

the number of clusters searched for. It corresponds to the argument G.

clusters_only

boolean. If TRUE only the partition of the data is returned as a vector. If FALSE the usual output of the otrimle::rimle() function is returned.

...

other arguments to pass to otrimle::rimle().

Value

If clusters_only is TRUE a vector of the new partition of the data is returned, i.e a vector of integers (from 1:k) indicating the cluster to which each observation is allocated. 0 indicates trimmed observations.

Otherwise a list is returned with the following components:

clust_method

the name of the clustering method, i.e, "rimle".

clusters

the vector of the new partition of the data, i.e. a vector of integers (from 1:k) indicating the cluster to which each observation is allocated. 0 indicates outlying observations.

...

an object of class "rimle"

Author(s)

Aurore Archimbaud

See Also

otrimle::rimle()

Examples

rimle_clust(iris[,1:4], k = 3, clusters_only = TRUE)