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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:

Please use the canonical form https://CRAN.R-project.org/package=ccaPP to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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