coroICA: Confounding Robust Independent Component Analysis for Noisy and Grouped Data

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 <>.

Version: 1.0.1
Depends: R (≥ 3.2.3)
Imports: stats, MASS
Published: 2018-12-30
Author: Niklas Pfister and Sebastian Weichwald
Maintainer: Niklas Pfister <pfister at>
License: AGPL-3
NeedsCompilation: no
CRAN checks: coroICA results


Reference manual: coroICA.pdf
Package source: coroICA_1.0.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X binaries: r-release: coroICA_1.0.1.tgz, r-oldrel: coroICA_1.0.1.tgz


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