<?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>Confounding Robust Independent Component Analysis for Noisy and
Grouped Data</dc:title>
  <dc:title>R package coroICA version 1.0.2</dc:title>
  <dc:description>Contains an implementation of a confounding robust independent component analysis (ICA) for noisy and grouped data. The main function coroICA() performs a blind source separation, by maximizing an independence across sources and allows to adjust for varying confounding based on user-specified groups. Additionally, the package contains the function uwedge() which can be used to approximately jointly diagonalize a list of matrices. For more details see the project website &lt;https://sweichwald.de/coroICA/&gt;.</dc:description>
  <dc:type>Software</dc:type>
  <dc:relation>Depends: R (&gt;= 3.2.3)</dc:relation>
  <dc:relation>Imports: stats, MASS</dc:relation>
  <dc:creator>Niklas Pfister &lt;np@math.ku.dk&gt;</dc:creator>
  <dc:publisher>Comprehensive R Archive Network (CRAN)</dc:publisher>
  <dc:contributor>Niklas Pfister and Sebastian Weichwald</dc:contributor>
  <dc:rights>AGPL-3</dc:rights>
  <dc:date>2020-05-15</dc:date>
  <dc:format>application/tgz</dc:format>
  <dc:identifier>https://CRAN.R-project.org/package=coroICA</dc:identifier>
  <dc:identifier>doi:10.32614/CRAN.package.coroICA</dc:identifier>
</oai_dc:dc>