Membership estimation algorithm called mixedSCORE
mixedSCORE(A, K, verbose = F)
Arguments
A: n-by-n binary symmtric adjacency matrix.K: number of communities.verbose: whether generate message
Returns
A list containing
- R: n-by-(K-1) ratio matrix.
- L: Selected tunning parameter used for vertex hunting algorithm.
- thetas: A vector of the estimated degree heterogeniety parameters
- vertices: K-by-(K-1) K vertices of the found convex hull
- centers: L-by-(K-1) L centers by kmeans
- memberships: n-by-K membership matrix.
- purity: A vector of maximum membership of each node
- hard.cluster.labels: A vector of integers indicating hard clutering labels, by assigning the node to the cluster with max membership
Examples
library(igraphdata)
library(igraph)
data('karate')
A = get.adjacency(karate)
karate.mixed.out = mixedSCORE(A, 2)
karate.mixed.out$memberships