fusedMGM: Implementation of Fused MGM to Infer 2-Class Networks

Implementation of fused Markov graphical model (FMGM; Park and Won, 2022). The functions include building mixed graphical model (MGM) objects from data, inference of networks using FMGM, stable edge-specific penalty selection (StEPS) for the determination of penalization parameters, and the visualization. For details, please refer to Park and Won (2022) <doi:10.48550/arXiv.2208.14959>.

Depends: R (≥ 2.10)
Imports: fastDummies, parallel, bigmemory, gplots
Suggests: testthat (≥ 3.0.0)
Published: 2023-04-25
DOI: 10.32614/CRAN.package.fusedMGM
Author: Jaehyun Park ORCID iD [aut, cre, cph], Sungho Won [ths]
Maintainer: Jaehyun Park <J.31.Park at gmail.com>
License: MIT + file LICENSE
NeedsCompilation: no
Materials: README
CRAN checks: fusedMGM results


Reference manual: fusedMGM.pdf


Package source: fusedMGM_0.1.0.1.tar.gz
Windows binaries: r-devel: fusedMGM_0.1.0.1.zip, r-release: fusedMGM_0.1.0.1.zip, r-oldrel: fusedMGM_0.1.0.1.zip
macOS binaries: r-release (arm64): fusedMGM_0.1.0.1.tgz, r-oldrel (arm64): fusedMGM_0.1.0.1.tgz, r-release (x86_64): fusedMGM_0.1.0.1.tgz, r-oldrel (x86_64): fusedMGM_0.1.0.1.tgz
Old sources: fusedMGM archive


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