whitening
Whitening and High-Dimensional Canonical Correlation Analysis
Implements the whitening methods (ZCA, PCA, Cholesky, ZCA-cor, and PCA-cor) discussed in Kessy, Lewin, and Strimmer (2018) "Optimal whitening and decorrelation", doi:10.1080/00031305.2016.1277159, as well as the whitening approach to canonical correlation analysis allowing negative canonical correlations described in Jendoubi and Strimmer (2019) "A whitening approach to probabilistic canonical correlation analysis for omics data integration", doi:10.1186/s12859-018-2572-9. The package also offers functions to simulate random orthogonal matrices, compute (correlation) loadings and explained variation. It also contains four example data sets (extended UCI wine data, TCGA LUSC data, nutrimouse data, extended pitprops data).
- Version1.4.0
- R versionunknown
- LicenseGPL (≥ 3)
- Needs compilation?No
- Last release06/07/2022
Documentation
Team
Korbinian Strimmer
MaintainerShow author detailsTakoua Jendoubi
Show author detailsRolesAuthorAlex Lewin
Show author detailsRolesAuthorAgnan Kessy
Show author detailsRolesAuthor
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