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whitening
View on CRAN: Click
here
Download and install whitening package within the R console
Install from CRAN:
install.packages("whitening")
Install from Github:
library("remotes")
install_github("cran/whitening")
Install by package version:
library("remotes")
install_version("whitening", "1.4.0")
Attach the package and use:
library("whitening")
Maintained by
Korbinian Strimmer
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[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-03-06
Latest Update: 2022-06-07
Description:
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).
How to cite:
Korbinian Strimmer (2018). whitening: Whitening and High-Dimensional Canonical Correlation Analysis. R package version 1.4.0, https://cran.r-project.org/web/packages/whitening. Accessed 27 Jan. 2025.
Previous versions and publish date:
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Complete documentation for whitening
Functions, R codes and Examples using
the whitening R package
Some associated functions: corplot . explainedVariation . forina1986 . lusc . nutrimouse . pitprops14 . scca . simOrtho . whiten . whitening-internal . whitening.package . whiteningLoadings . whiteningMatrix .
Some associated R codes: corplot.R . explainedVariation.R . getPhiPsiW.R . internal.R . scca.R . simOrtho.R . whiten.R . whiteningCrossCov.R . whiteningLoadings.R . whiteningMatrix.R . Full whitening package functions and examples
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