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 |
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:
Downloads:
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