Type: Package
Package: mglasso
Title: Multiscale Graphical Lasso
Version: 0.1.3
Authors@R: c(
    person("Edmond", "Sanou", , "doedmond.sanou@univ-evry.fr", role = c("aut", "cre")),
    person("Tung", "Le", role = "ctb"),
    person("Christophe", "Ambroise", role = "ths"),
    person("Geneviève", "Robin", role = "ths")
  )
Description: 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.
License: MIT + file LICENSE
Imports: corpcor, ggplot2, ggrepel, gridExtra, Matrix, methods,
        R.utils, reticulate (>= 1.25), rstudioapi, capushe, DescTools
Suggests: knitr, mvtnorm, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
ByteCompile: true
Config/reticulate: list( packages = list( list(package = "scipy",
        version = "1.7.1"), list(package = "numpy", version =
        "1.22.4"), list(package = "matplotlib"), list(package =
        "scikit-learn"), list(package = "six"), list(package =
        "pylearn-parsimony", version = "0.3.1", pip = TRUE) ) )
Encoding: UTF-8
RoxygenNote: 7.2.3
URL: https://desanou.github.io/mglasso/
Roxygen: list(markdown = TRUE)
Config/testthat/edition: 3
Config/pak/sysreqs: cmake make libpng-dev libuv1-dev libssl-dev python3
        libx11-dev zlib1g-dev
Repository: https://desanou.r-universe.dev
Date/Publication: 2023-06-19 09:21:33 UTC
RemoteUrl: https://github.com/desanou/mglasso
RemoteRef: HEAD
RemoteSha: 0cbbafe519d84dcc75b0461e8b92e13720cc64ce
NeedsCompilation: no
Packaged: 2026-10-04 12:45:55 UTC; root
Author: Edmond Sanou [aut, cre],
  Tung Le [ctb],
  Christophe Ambroise [ths],
  Geneviève Robin [ths]
Maintainer: Edmond Sanou <doedmond.sanou@univ-evry.fr>