Tools for spectral clustering of weighted directed networks using motif adjacency matrices. Methods perform well on large and sparse networks, and random sampling methods for generating weighted directed networks are also provided. Based on methodology detailed in Underwood, Elliott and Cucuringu (2020) <arXiv:2004.01293>.
Version: | 0.2.2 |
Depends: | R (≥ 3.6.0) |
Imports: | igraph (≥ 1.2.5), Matrix (≥ 1.2), RSpectra (≥ 0.16.0) |
Suggests: | covr (≥ 3.5.0), knitr (≥ 1.28), mclust (≥ 5.4.6), rmarkdown (≥ 2.1), testthat (≥ 2.3.2) |
Published: | 2022-08-15 |
Author: | William George Underwood [aut, cre] |
Maintainer: | William George Underwood <wgu2 at princeton.edu> |
BugReports: | https://github.com/wgunderwood/motifcluster/issues |
License: | GPL-3 |
URL: | https://github.com/wgunderwood/motifcluster |
NeedsCompilation: | no |
Language: | en-US |
Materials: | README NEWS |
CRAN checks: | motifcluster results |
Reference manual: | motifcluster.pdf |
Vignettes: |
using_the_motifcluster_package |
Package source: | motifcluster_0.2.2.tar.gz |
Windows binaries: | r-devel: motifcluster_0.2.2.zip, r-release: motifcluster_0.2.2.zip, r-oldrel: motifcluster_0.2.2.zip |
macOS binaries: | r-release (arm64): motifcluster_0.2.2.tgz, r-oldrel (arm64): motifcluster_0.2.2.tgz, r-release (x86_64): motifcluster_0.2.2.tgz, r-oldrel (x86_64): motifcluster_0.2.2.tgz |
Old sources: | motifcluster archive |
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