Package: whitening 1.4.0

Korbinian Strimmer

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).

Authors:Korbinian Strimmer, Takoua Jendoubi, Agnan Kessy, Alex Lewin

whitening_1.4.0.tar.gz
whitening_1.4.0.tar.gz(r-4.5-noble)whitening_1.4.0.tar.gz(r-4.4-noble)
whitening_1.4.0.tgz(r-4.4-emscripten)whitening_1.4.0.tgz(r-4.3-emscripten)
whitening.pdf |whitening.html
whitening/json (API)
NEWS

# Install 'whitening' in R:
install.packages('whitening', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/strimmerlab/software/issues

Datasets:

2.50 score 2 packages 53 scripts 412 downloads 10 exports 1 dependencies

Last updated 3 years agofrom:2bbfc878da. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 28 2024
R-4.5-linuxOKNov 28 2024

Exports:ccacorplotexplainedVariationloadplotsccasimOrthowhitenwhiteningCrossCovwhiteningLoadingswhiteningMatrix

Dependencies:corpcor