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groupICA: Independent Component Analysis for Grouped Data

Contains an implementation of an independent component analysis (ICA) for grouped data. The main function groupICA() performs a blind source separation, by maximizing an independence across sources and allows to adjust for varying confounding for 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 <https://sweichwald.de/groupICA/>.

Version: 0.1.1
Depends: R (≥ 3.2.3)
Imports: stats, MASS
Published: 2018-06-19
DOI: 10.32614/CRAN.package.groupICA
Author: Niklas Pfister and Sebastian Weichwald
Maintainer: Niklas Pfister <pfister at stat.math.ethz.ch>
BugReports: https://github.com/sweichwald/groupICA-R/issues
License: AGPL-3
URL: https://github.com/sweichwald/groupICA-R
NeedsCompilation: no
CRAN checks: groupICA results

Documentation:

Reference manual: groupICA.pdf

Downloads:

Package source: groupICA_0.1.1.tar.gz
Windows binaries: r-devel: groupICA_0.1.1.zip, r-release: groupICA_0.1.1.zip, r-oldrel: groupICA_0.1.1.zip
macOS binaries: r-release (arm64): groupICA_0.1.1.tgz, r-oldrel (arm64): groupICA_0.1.1.tgz, r-release (x86_64): groupICA_0.1.1.tgz, r-oldrel (x86_64): groupICA_0.1.1.tgz

Reverse dependencies:

Reverse imports: iTensor

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.