compare.clust: Make all estimated clusters agree with a pivot allocation
In label.switching: Relabelling MCMC Outputs of Mixture Models

Description Usage Arguments Value Author(s) See Also

Given a pivot allocation vector, a set of simulated allocations and a set of permutations from different relabelling algorithms, this function relabels the permutations so that all methods maximize their similarity with the pivot. This is helpful when comparing different different label switching algorithms.

1	compare.clust(pivot.clust,perms,z,K)

`pivot.clust`	a pivot allocation vector of the n observations among the K clusters.
`perms`	a list containing f permutation arrays, as returned by `label.switching` function.
`z`	a set of simulated allocation arrays.
`K`	number of mixture components

`similarity`	(f+1) K\times (f+1) matrix containing the similarity coefficient of the resulting clusters.
`clusters`	f\times n array of single best clusterings, relabelled in order to maximize their similarity with `pivot.clust`.
`permutations`	releaballed permutations.