https://neil-sps.r-universe.devRecent package updates in neil-spsR-universehttps://github.com/neil-sps.pnghttps://neil-sps.r-universe.devWed, 08 Apr 2026 15:51:46 GMTneil.hwang@bcc.cuny.edu (Neil Hwang)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) <doi:10.1214/14-AOS1274>. 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) <doi:10.1073/pnas.122653799> as a benchmark dataset, and the Bethe-Hessian community number estimator of Hwang (2023) <doi:10.1080/01621459.2023.2223793>.https://github.com/r-universe/neil-sps/actions/runs/37445323165Wed, 08 Apr 2026 15:51:46 GMTsparsecommunity0.1.1successhttps://neil-sps.r-universe.devhttps://github.com/cran/sparsecommunitysparsecommunity-intro.Rmdsparsecommunity-intro.htmlIntroduction to sparsecommunity2026-04-08 15:51:462026-04-08 15:51:46neil.hwang@bcc.cuny.edu (Neil Hwang)Implements the Changes-in-Changes (CIC) estimator of Athey and Imbens (2006) <doi:10.1111/j.1468-0262.2006.00668.x> combined with synthetic control methods. Provides nonparametric estimation of the entire counterfactual distribution of outcomes for a treated group, allowing evaluation of average, quantile, and distributional treatment effects. Synthetic control weights are constructed via elastic net regularization to handle settings with many potential control units.https://github.com/r-universe/neilhwang/actions/runs/39409919173Mon, 30 Mar 2026 15:56:58 GMTsccic0.1.0successhttps://neilhwang.r-universe.devhttps://github.com/neilhwang/sccicsccic-intro.Rmdsccic-intro.htmlIntroduction to sccic2026-03-30 15:55:472026-03-30 15:55:47