<?xml version="1.0" encoding="UTF-8"?>
<oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:title>Fitting Ising Models Using the ELasso Method</dc:title>
  <dc:title>R package IsingFit version 0.4</dc:title>
  <dc:subject>CRAN Task View: Psychometrics (https://CRAN.R-project.org/view=Psychometrics)</dc:subject>
  <dc:description>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.</dc:description>
  <dc:type>Software</dc:type>
  <dc:relation>Depends: R (&gt;= 3.0.0)</dc:relation>
  <dc:relation>Imports: qgraph, Matrix, glmnet</dc:relation>
  <dc:relation>Suggests: IsingSampler</dc:relation>
  <dc:creator>Sacha Epskamp &lt;mail@sachaepskamp.com&gt;</dc:creator>
  <dc:publisher>Comprehensive R Archive Network (CRAN)</dc:publisher>
  <dc:contributor>Claudia van Borkulo, Sacha Epskamp; with contributions from Alexander Robitzsch and Mihai Alexandru Constantin</dc:contributor>
  <dc:rights>GPL-2</dc:rights>
  <dc:date>2023-10-03</dc:date>
  <dc:format>application/tgz</dc:format>
  <dc:identifier>https://CRAN.R-project.org/package=IsingFit</dc:identifier>
  <dc:identifier>doi:10.32614/CRAN.package.IsingFit</dc:identifier>
</oai_dc:dc>