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multiCCA

0.1.0

Multiple Canonical Correlation Analysis (Kernel and Functional)

0packages depend
886downloads / year
39.9%test coverage
13/13checks pass

Overview

About
Maintained by Tomasz GoreckiFirst published 2026-03-241 releasesCRAN page ↗GitHub ↗

Implements methods for multiple canonical correlation analysis (CCA) for more than two data blocks, with a focus on multivariate repeated measures and functional data. The package provides two approaches: (i) multiple kernel CCA, which embeds each data block into a reproducing kernel Hilbert space to capture nonlinear dependencies, and (ii) multiple functional CCA, which represents repeated measurements as smooth functions and performs analysis in a Hilbert space framework. Both approaches are formulated via covariance operators and solved as generalized eigenvalue problems with regularization to ensure numerical stability. The methods allow estimation of canonical variables, generalized canonical correlations, and low-dimensional representations for exploratory analysis and visualization of dependence structures across multiple feature sets. The implementation follows the framework developed in Górecki, Krzyśko, Gnettner and Kokoszka (2025) doi:10.48550/arXiv.2510.04457.

Install

Health

CRAN checks
13OK
Slowest check: 2.6 min · r-oldrel-windows-x86_64
Code health
Yes
Tests · ratio 0.13
39.9%
Coverage · measured lines
100%
Documentation · exports
4
Dependencies · direct
Check history
  • OK2026-08-05
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • NOTE2026-08-01
    12 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • OK2026-06-09
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • ERROR2026-06-08
    12 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
  • OK2026-03-24
    5 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

Documentation
READMEYes · 132 wordsVignettesNopkgdown siteNoNEWSNoCode of conductNoContributing guideNo
Examples that run
100%
Documented parameters
100%
Return-value docs
100%
References docs
0%

Downloads

886
CRAN downloads in the past year
Rank #23,690 · ~2/day · ~74/mo
Daily download trend is not available in this view yet.
9230 days
39590 days
8861 year
Compare downloads with other packages →
Also on39 r2u8 autocran

Repository

Repository
0Stars
0Forks
0Open issues
0Open PRs
0Releases
Last activity 2026-03-13

Repository practices

Upstream repositoryBeta

1 development-tooling and community-health practice detected across 1 family in the upstream repository

Checks run against github.com/halmaris/multicca on 2026-08-16.

Lint, format, editor (1)
RStudio project
How this is detected·Detection ruleset v1 (2026-07-18)

Dependencies

Declared dependencies
5 external dependencies (excludes base and recommended)
Depends (0)
none
LinkingTo (0)
none
Suggests (1)
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Code & Tests

People & History

People (1)
Maintainer (1)
Author, Maintainer
Authors (1)
Author, Maintainer
Package Timeline

1 release. R releases are shown for context.

  • R
    R 4.6.0 released · 2026-04-24
  • 0.1.0Latest
    2026-03-24 · current release
  • R
    R 4.5.0 released · 2025-04-11

Package metadata

First published
2026-03-24
Total releases
1 / 1 yrs
License
MIT + file LICENSE OSI
Download size
14 KB
Installed size
not tracked yet
With dependencies
not tracked yet

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("multiCCA")
Gorecki, T. (2026). multiCCA: Multiple Canonical Correlation Analysis (Kernel and Functional) (Version 0.1.0) [Computer software]. https://doi.org/10.32614/CRAN.package.multiCCA

This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for multiCCA version 0.1.0 [Data set]. HJJB, LLC. Data release v2026-08-18. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-18, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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