CommKern: Network-Based Communities and Kernel Machine Methods

Analysis of network community objects with applications to neuroimaging data. There are two main components to this package. The first is the hierarchical multimodal spinglass (HMS) algorithm, which is a novel community detection algorithm specifically tailored to the unique issues within brain connectivity. The other is a suite of semiparametric kernel machine methods that allow for statistical inference to be performed to test for potential associations between these community structures and an outcome of interest (binary or continuous).

Version: 1.0.1
Depends: R (≥ 4.0.0)
Imports: ggnewscale, ggplot2, gridExtra, Matrix, RColorBrewer, reshape2
Suggests: knitr, matrixcalc, pheatmap, rmarkdown
Published: 2022-09-23
Author: Alexandria Jensen ORCID iD [aut, cre], Peter DeWitt ORCID iD [ctb], Debashis Ghosh ORCID iD [ths]
Maintainer: Alexandria Jensen <alexandria.jensen at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Language: en-us
Materials: README NEWS
CRAN checks: CommKern results


Reference manual: CommKern.pdf
Vignettes: CommKern


Package source: CommKern_1.0.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): CommKern_1.0.1.tgz, r-oldrel (arm64): CommKern_1.0.1.tgz, r-release (x86_64): CommKern_1.0.1.tgz, r-oldrel (x86_64): CommKern_1.0.1.tgz
Old sources: CommKern archive


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