cvborkulo/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

Package details

AuthorClaudia van Borkulo, Sacha Epskamp; with contributions from Alexander Robitzsch and Mihai Alexandru Constantin
MaintainerClaudia van Borkulo <[email protected]>
LicenseGPL-2
Version0.3.2
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("devtools")
library(devtools)
install_github("cvborkulo/IsingFit")
cvborkulo/IsingFit documentation built on June 3, 2018, 2:55 a.m.