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sparsecommunity: 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) <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>.
| Version: |
0.1.1 |
| Depends: |
R (≥ 4.0.0) |
| Imports: |
graphics, Matrix, methods, RSpectra, stats |
| Suggests: |
irlba, clue, igraph, igraphdata, testthat (≥ 3.0.0), knitr, rmarkdown |
| Published: |
2026-04-08 |
| DOI: |
10.32614/CRAN.package.sparsecommunity (may not be active yet) |
| Author: |
Neil Hwang  [aut,
cre] |
| Maintainer: |
Neil Hwang <neil.hwang at bcc.cuny.edu> |
| License: |
GPL-3 |
| NeedsCompilation: |
no |
| Language: |
en-US |
| Materials: |
NEWS |
| CRAN checks: |
sparsecommunity results |
Documentation:
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.