Spectral Community Detection for Sparse Networks

Implements spectral clustering algorithms for community detection in sparse networks under the stochastic block model ('SBM') and degree-corrected stochastic block model ('DCSBM'), following the methods of Lei and Rinaldo (2015) . Provides a regularized normalized Laplacian embedding, spherical k-median clustering for 'DCSBM', standard k-means for 'SBM', simulation utilities for both models, and a misclustering rate evaluation metric. Also includes the 'NCAA' college football network of Girvan and Newman (2002) as a benchmark dataset, and the Bethe-Hessian community number estimator of Hwang (2023) .