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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 |
Reference manual: | IsingFit.pdf |
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 imports: | bootnet, NetworkComparisonTest, NetworkToolbox |
Reverse suggests: | Isinglandr |
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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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