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) .


Reference manual

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install.packages("fusedMGM")

0.1.2 by Jaehyun Park, 2 years ago


Browse source code at https://github.com/cran/fusedMGM


Authors: Jaehyun Park [aut, cre, cph] , Sungho Won [ths]


Documentation:   PDF Manual  


MIT + file LICENSE license


Imports fastDummies, parallel, bigmemory, gplots, bigalgebra, biganalytics

Suggests testthat


See at CRAN