Package: multiCCA
Title: Multiple Canonical Correlation Analysis (Kernel and Functional)
Version: 0.1.0
Authors@R: 
    person("Tomasz", "Gorecki",
        email = "tomasz.gorecki@amu.edu.pl",
        role = c("aut", "cre"),
        comment = c(ORCID = "0000-0002-9969-5257"))
Description: 
    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>.
License: MIT + file LICENSE
Encoding: UTF-8
RoxygenNote: 7.3.3
Suggests: testthat (>= 3.0.0)
Config/testthat/edition: 3
Imports: fda, geigen, ggplot2, rlang
URL: https://github.com/Halmaris/multiCCA
BugReports: https://github.com/Halmaris/multiCCA/issues
NeedsCompilation: no
Packaged: 2026-03-19 14:57:46 UTC; Tomek
Author: Tomasz Gorecki [aut, cre] (ORCID:
    <https://orcid.org/0000-0002-9969-5257>)
Maintainer: Tomasz Gorecki <tomasz.gorecki@amu.edu.pl>
Repository: CRAN
Date/Publication: 2026-03-23 17:50:07 UTC
Built: R 4.6.0; ; 2026-04-30 14:07:06 UTC; unix
