The silhouette score is a cluster qualiy index that assessses both cluster cohesion (how close points within the same cluster are to each other) and cluster separation (how well different clusters are separated) for a given clustering result (encoded in the group membership vector). The silhouette score is bounded by -1 (worst value) and 1 (best value). The silhouette score s of a point i is defined as: s(i)=b(i)-a(i)/max(b(i),max(i)), where a(i) is the mean distance of this point to all other points within the same cluster and b(i) is the smallest mean distance to data points in the nearest neighboring cluster. The silhouette score of the entire clustering is computed as the mean of silhouette scores across all points. This function wraps vegdist to compute distances/dissimilarities.

silhouette(abundances, groups, method = "bray")

## Arguments

abundances a matrix with taxa as rows and samples as columns vector with group memberships name of dissimilarity or distance to use. See vegdist for options