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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