lddmm: Longitudinal Drift-Diffusion Mixed Models (LDDMM)

Implementation of the drift-diffusion mixed model for category learning as described in Paulon et al. (2021) <doi:10.1080/01621459.2020.1801448>.

Version: 1.0.0
Depends: R (≥ 4.1.0)
Imports: Rcpp (≥ 1.0.6), dplyr, tidyr, ggplot2 (≥ 3.4.0), latex2exp, reshape2, stats, utils
LinkingTo: Rcpp, RcppArmadillo
Suggests: rmarkdown, knitr, testthat (≥ 3.0.0), statmod
Published: 2026-10-23
DOI: 10.32614/CRAN.package.lddmm
Author: Giorgio Paulon [aut, cre], Abhra Sarkar [aut, ctb]
Maintainer: Giorgio Paulon <giorgiopaulon90 at gmail.com>
BugReports: https://github.com/giorgiopaulon/LDDMM/issues
License: MIT + file LICENSE
URL: https://github.com/giorgiopaulon/LDDMM
NeedsCompilation: yes
Language: en-US
Materials: README, NEWS
CRAN checks: lddmm results

Documentation:

Reference manual: lddmm.html , lddmm.pdf
Vignettes: minimal_example (source, R code)

Downloads:

Package source: lddmm_1.0.0.tar.gz
Windows binaries: r-devel: lddmm_0.4.2.zip, r-release: lddmm_0.4.2.zip, r-oldrel: lddmm_0.4.2.zip
macOS binaries: r-release (arm64): lddmm_0.4.2.tgz, r-oldrel (arm64): lddmm_0.4.2.tgz, r-release (x86_64): lddmm_0.4.2.tgz, r-oldrel (x86_64): lddmm_0.4.2.tgz
Old sources: lddmm archive

Linking:

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