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catfda: Statistical Analysis for Categorical Functional Data

Implements methods for estimating latent Gaussian processes from categorical functional data using binomial, probit, or multinomial GAM-based approaches, and for clustering individuals via multivariate functional principal component scores. Methods are described in Champon et al. (2026) <doi:10.1080/01621459.2026.2672226>.

Version: 0.1.0
Imports: mgcv (≥ 1.8-40), stats, rlang (≥ 1.0.0), foreach (≥ 1.5.0), doRNG (≥ 1.8.0)
Suggests: doParallel, testthat (≥ 3.0.0)
Published: 2026-09-08
DOI: 10.32614/CRAN.package.catfda (may not be active yet)
Author: Xiaoxia Champon [aut], Ana-Maria Staicu [aut], Chathura Jayalath ORCID iD [aut, cre], Anthony Weishampel [ctb], William Rand [ctb]
Maintainer: Chathura Jayalath <acj.chathura at gmail.com>
BugReports: https://github.com/XiaoxiaChampon/catfda/issues
License: MIT + file LICENSE
URL: https://github.com/XiaoxiaChampon/catfda
NeedsCompilation: no
Materials: README, NEWS
CRAN checks: catfda results

Documentation:

Reference manual: catfda.html , catfda.pdf

Downloads:

Package source: catfda_0.1.0.tar.gz
Windows binaries: r-devel: not available, r-release: catfda_0.1.0.zip, r-oldrel: catfda_0.1.0.zip
macOS binaries: r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): catfda_0.1.0.tgz, r-oldrel (x86_64): catfda_0.1.0.tgz

Linking:

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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.