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>.
| Version: | 0.1.2 |
| Depends: | R (≥ 2.10) |
| Imports: | fastDummies, parallel, bigmemory, gplots, bigalgebra, biganalytics |
| Suggests: | testthat (≥ 3.0.0) |
| Published: | 2024-10-17 |
| DOI: | 10.32614/CRAN.package.fusedMGM |
| Author: | Jaehyun Park 
[aut, cre, cph],
Sungho Won [ths] |
| Maintainer: | Jaehyun Park <J.31.Park at gmail.com> |
| License: | MIT + file LICENSE |
| NeedsCompilation: | no |
| CRAN checks: | fusedMGM results |
Documentation:
| Reference manual: | fusedMGM.pdf |
Downloads:
| Package source: | fusedMGM_0.1.2.tar.gz |
| Windows binaries: | r-devel: fusedMGM_0.1.2.zip, r-release: fusedMGM_0.1.2.zip, r-oldrel: fusedMGM_0.1.2.zip |
| macOS binaries: | r-release (arm64): fusedMGM_0.1.2.tgz, r-oldrel (arm64): fusedMGM_0.1.2.tgz, r-release (x86_64): fusedMGM_0.1.2.tgz, r-oldrel (x86_64): fusedMGM_0.1.2.tgz |
| Old sources: | fusedMGM archive |
Linking:
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