desanou/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.

Getting started

Package details

Maintainer
LicenseMIT + file LICENSE
Version0.1.3
URL https://desanou.github.io/mglasso/
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("desanou/mglasso")
desanou/mglasso documentation built on July 1, 2023, 6:39 a.m.