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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