IsingFit: Fitting Ising Models Using the ELasso Method
Version 0.3.1

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
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("IsingFit")

Popular man pages

isingfit: Network estimation using the eLasso method
isingfit-package: Network estimation using the eLasso method
methods: Methods for IsingFit objects
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Man pages

isingfit: Network estimation using the eLasso method
isingfit-package: Network estimation using the eLasso method
methods: Methods for IsingFit objects

Functions

ComparableNetworks Source code
IsingFit Man page Source code
IsingFit-package Man page
plot.IsingFit Man page Source code Source code
print.IsingFit Man page Source code Source code
summary.IsingFit Man page Source code Source code

Files

inst
inst/COPYING
inst/COPYRIGHTS
NAMESPACE
R
R/summary.IsingFit.R
R/plot.IsingFit.R
R/ComparableNetworks.R
R/print.IsingFit.R
R/IsingFit.R
MD5
DESCRIPTION
man
man/isingfit-package.rd
man/methods.Rd
man/isingfit.rd
IsingFit documentation built on May 19, 2017, 12:19 p.m.

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