Package: IsingFit
Type: Package
Title: Fitting Ising Models Using the ELasso Method
Version: 0.4.1
Authors@R: c(
  person("van Borkulo", "Claudia", role = c("aut")),
  person("Sacha", "Epskamp", email = "mail@sachaepskamp.com",role = c("aut", "cre")),
  person("Alexander", "Robitzsch", role = c("ctb")),
  person("Mihai Alexandru", "Constantin", role = c("ctb")),
  person("Jesse", "Boot", role = c("ctb"))
  )
Maintainer: Sacha Epskamp <mail@sachaepskamp.com>
Depends: R (>= 3.0.0)
Imports: qgraph, Matrix, glmnet
Suggests: IsingSampler
Description: This network estimation procedure eLasso, which is based
        on the Ising model, combines l1-regularized logistic regression
        with model selection based on the Extended Bayesian Information
        Criterion (EBIC). EBIC is a fit measure that identifies
        relevant relationships between variables. The resulting network
        consists of variables as nodes and relevant relationships as
        edges. Can deal with binary data.
License: GPL-2
Config/pak/sysreqs: cmake libglpk-dev make libicu-dev libjpeg-dev
        libpng-dev libuv1-dev libxml2-dev
Repository: https://cvborkulo.r-universe.dev
Date/Publication: 2023-10-12 07:05:03 UTC
RemoteUrl: https://github.com/cvborkulo/isingfit
RemoteRef: HEAD
RemoteSha: d3977032ac85418c2bf8da5326fbc984672d9112
NeedsCompilation: no
Packaged: 2026-07-04 19:13:50 UTC; root
Author: van Borkulo Claudia [aut],
  Sacha Epskamp [aut, cre],
  Alexander Robitzsch [ctb],
  Mihai Alexandru Constantin [ctb],
  Jesse Boot [ctb]