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) <arXiv:2208.14959>.
Version: |
0.1.0.1 |
Depends: |
R (≥ 2.10) |
Imports: |
fastDummies, parallel, bigmemory, gplots |
Suggests: |
testthat (≥ 3.0.0) |
Published: |
2023-04-25 |
Author: |
Jaehyun Park
[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 |
Documentation:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=fusedMGM
to link to this page.