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.

AuthorClaudia van Borkulo, Sacha Epskamp, with contributions from Alexander Robitzsch
Date of publication2016-09-07 13:01:58
MaintainerClaudia van Borkulo <cvborkulo@gmail.com>
LicenseGPL-2
Version0.3.1

View on CRAN

Files in this package

IsingFit
IsingFit/inst
IsingFit/inst/COPYING
IsingFit/inst/COPYRIGHTS
IsingFit/NAMESPACE
IsingFit/R
IsingFit/R/summary.IsingFit.R IsingFit/R/plot.IsingFit.R IsingFit/R/ComparableNetworks.R IsingFit/R/print.IsingFit.R IsingFit/R/IsingFit.R
IsingFit/MD5
IsingFit/DESCRIPTION
IsingFit/man
IsingFit/man/isingfit-package.rd
IsingFit/man/methods.Rd
IsingFit/man/isingfit.rd

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