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IsingFit: Fitting Ising Models Using the ELasso Method

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.

Version: 0.4
Depends: R (≥ 3.0.0)
Imports: qgraph, Matrix, glmnet
Suggests: IsingSampler
Published: 2023-10-03
DOI: 10.32614/CRAN.package.IsingFit
Author: Claudia van Borkulo, Sacha Epskamp; with contributions from Alexander Robitzsch and Mihai Alexandru Constantin
Maintainer: Sacha Epskamp <mail at sachaepskamp.com>
License: GPL-2
Copyright: see file COPYRIGHTS
NeedsCompilation: no
Materials: README NEWS
In views: Psychometrics
CRAN checks: IsingFit results

Documentation:

Reference manual: IsingFit.pdf

Downloads:

Package source: IsingFit_0.4.tar.gz
Windows binaries: r-devel: IsingFit_0.4.zip, r-release: IsingFit_0.4.zip, r-oldrel: IsingFit_0.4.zip
macOS binaries: r-release (arm64): IsingFit_0.4.tgz, r-oldrel (arm64): IsingFit_0.4.tgz, r-release (x86_64): IsingFit_0.4.tgz, r-oldrel (x86_64): IsingFit_0.4.tgz
Old sources: IsingFit archive

Reverse dependencies:

Reverse imports: bootnet, NetworkComparisonTest, NetworkToolbox
Reverse suggests: Isinglandr

Linking:

Please use the canonical form https://CRAN.R-project.org/package=IsingFit to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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