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Implementation of propensity clustering and decomposition as described in Ranola et al. (2013) <doi:10.1186/1752-0509-7-21>. Propensity decomposition can be viewed on the one hand as a generalization of the eigenvector-based approximation of correlation networks, and on the other hand as a generalization of random multigraph models and conformity-based decompositions.
Version: | 1.4-7 |
Depends: | R (≥ 3.0.0), fastcluster, dynamicTreeCut |
Imports: | stats |
Published: | 2023-10-06 |
DOI: | 10.32614/CRAN.package.PropClust |
Author: | John Michael O Ranola, Kenneth Lange, Steve Horvath, Peter Langfelder |
Maintainer: | Peter Langfelder <Peter.Langfelder at gmail.com> |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
NeedsCompilation: | yes |
Materials: | ChangeLog |
CRAN checks: | PropClust results |
Reference manual: | PropClust.pdf |
Package source: | PropClust_1.4-7.tar.gz |
Windows binaries: | r-devel: PropClust_1.4-7.zip, r-release: PropClust_1.4-7.zip, r-oldrel: PropClust_1.4-7.zip |
macOS binaries: | r-release (arm64): PropClust_1.4-7.tgz, r-oldrel (arm64): PropClust_1.4-7.tgz, r-release (x86_64): PropClust_1.4-7.tgz, r-oldrel (x86_64): PropClust_1.4-7.tgz |
Old sources: | PropClust archive |
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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.