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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 <https://sweichwald.de/coroICA/>.
Getting started
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Package details |
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| Author | Niklas Pfister and Sebastian Weichwald |
| Maintainer | Niklas Pfister <np@math.ku.dk> |
| License | AGPL-3 |
| Version | 1.0.2 |
| URL | https://github.com/sweichwald/coroICA-R |
| Package repository | View on CRAN |
| Installation |
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