community_detect(): unified spectral community detection for the stochastic
block model (model = "sbm", k-means on regularized Laplacian embedding) and
the degree-corrected stochastic block model (model = "dcsbm", spherical
k-median on row-normalized embedding). Implements the algorithms of
Lei and Rinaldo (2015).
estimate_K(): Bethe--Hessian spectral estimator for the number of
communities in sparse networks. Implements the method of Hwang (2023).
simulate_sbm(), simulate_dcsbm(): simulation utilities for generating
benchmark graphs under both models.
misclustering_rate(): permutation-corrected misclustering rate (Hungarian
algorithm via clue, greedy fallback otherwise).
plot_scree(): scree plot of regularized Laplacian eigenvalues to guide
selection of K.
plot() S3 method for "sparsecommunity" objects: scatter plot of the
spectral embedding colored by detected community.
print() and summary() S3 methods for "sparsecommunity",
"sbm_sim", and "dcsbm_sim" objects.