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mglasso: Multiscale Graphical Lasso
Inference of Multiscale graphical models with neighborhood selection approach. The method is based on solving a convex optimization problem combining a Lasso and fused-group Lasso penalties. This allows to infer simultaneously a conditional independence graph and a clustering partition. The optimization is based on the Continuation with Nesterov smoothing in a Shrinkage-Thresholding Algorithm solver (Hadj-Selem et al. 2018) <doi:10.1109/TMI.2018.2829802> implemented in python.
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Package details |
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| Author | Edmond Sanou [aut, cre], Tung Le [ctb], Christophe Ambroise [ths], Geneviève Robin [ths] |
| Maintainer | Edmond Sanou <doedmond.sanou@univ-evry.fr> |
| License | MIT + file LICENSE |
| Version | 0.1.2 |
| URL | https://desanou.github.io/mglasso/ |
| Package repository | View on CRAN |
| Installation |
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