HCD: Hierarchical Community Detection by Recursive Partitioning

Hierarchical community detection on networks by a recursive spectral partitioning strategy, which is shown to be effective and efficient in Li, Lei, Bhattacharyya, Sarkar, Bickel, and Levina (2018) <doi:10.48550/arXiv.1810.01509>. The package also includes a data generating function for a binary tree stochastic block model, a special case of stochastic block model that admits hierarchy between communities.

Version: 1.0
Imports: Matrix, stats, methods, randnet, RSpectra, irlba, data.tree, data.table, stringr, dendextend
Published: 2024-02-02
Author: Tianxi Li [aut, cre], Lihua Lei [aut], Sharmodeep Bhattacharyya [aut], Purna Sarkar [aut], Peter Bickel [aut], Elizeveta Levina [aut]
Maintainer: Tianxi Li <tianxili at umn.edu>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: HCD results

Documentation:

Reference manual: HCD.pdf

Downloads:

Package source: HCD_1.0.tar.gz
Windows binaries: r-devel: HCD_1.0.zip, r-release: HCD_1.0.zip, r-oldrel: HCD_1.0.zip
macOS binaries: r-release (arm64): not available, r-oldrel (arm64): HCD_1.0.tgz, r-release (x86_64): HCD_1.0.tgz
Old sources: HCD archive

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