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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.
Getting started
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Package details |
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| Author | Claudia van Borkulo, Sacha Epskamp; with contributions from Alexander Robitzsch and Mihai Alexandru Constantin |
| Maintainer | Sacha Epskamp <mail@sachaepskamp.com> |
| License | GPL-2 |
| Version | 0.4 |
| Package repository | View on CRAN |
| Installation |
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