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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.

copied from cf-post-staging / r-isingfit
Type Size Name Uploaded Downloads Labels
conda 45.7 kB | noarch/r-isingfit-0.4-r44hc72bb7e_2.conda  3 days and 14 hours ago 37 main
conda 45.8 kB | noarch/r-isingfit-0.4-r45hc72bb7e_2.conda  3 days and 14 hours ago 31 main
conda 44.9 kB | noarch/r-isingfit-0.4-r43hc72bb7e_1.conda  1 year and 1 month ago 969 main
conda 44.8 kB | noarch/r-isingfit-0.4-r44hc72bb7e_1.conda  1 year and 1 month ago 942 main
conda 44.5 kB | noarch/r-isingfit-0.4-r42hc72bb7e_0.conda  1 year and 11 months ago 1249 main
conda 45.0 kB | noarch/r-isingfit-0.4-r43hc72bb7e_0.conda  1 year and 11 months ago 1303 main

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