ccaPP: (Robust) Canonical Correlation Analysis via Projection Pursuit

Canonical correlation analysis and maximum correlation via projection pursuit, as well as fast implementations of correlation estimators, with a focus on robust and nonparametric methods.

Version: 0.3.4
Depends: R (≥ 3.2.0), parallel, pcaPP (≥ 1.8-1), robustbase
Imports: Rcpp (≥ 0.11.0)
LinkingTo: Rcpp (≥ 0.11.0), RcppArmadillo (≥ 0.4.100.0)
Suggests: knitr, mvtnorm
Published: 2024-09-04
DOI: 10.32614/CRAN.package.ccaPP
Author: Andreas Alfons ORCID iD [aut, cre], David Simcha [ctb] (O(n log(n)) implementation of Kendall correlation)
Maintainer: Andreas Alfons <alfons at ese.eur.nl>
BugReports: https://github.com/aalfons/ccaPP/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/aalfons/ccaPP
NeedsCompilation: yes
Citation: ccaPP citation info
Materials: README NEWS
CRAN checks: ccaPP results

Documentation:

Reference manual: ccaPP.pdf
Vignettes: Robust Maximum Association Between Data Sets: The R Package ccaPP (source, R code)

Downloads:

Package source: ccaPP_0.3.4.tar.gz
Windows binaries: r-devel: ccaPP_0.3.4.zip, r-release: ccaPP_0.3.4.zip, r-oldrel: ccaPP_0.3.4.zip
macOS binaries: r-release (arm64): ccaPP_0.3.4.tgz, r-oldrel (arm64): ccaPP_0.3.4.tgz, r-release (x86_64): ccaPP_0.3.4.tgz, r-oldrel (x86_64): ccaPP_0.3.4.tgz
Old sources: ccaPP archive

Reverse dependencies:

Reverse imports: ctsGE, nanostringr, phantasus
Reverse suggests: yaImpute

Linking:

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