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: 0.2.0
Depends: R (≥ 4.1.0)
Imports: Rcpp (≥ 1.0.6), RcppProgress, rgen, mvtnorm, gtools, LaplacesDemon, dplyr, plyr, tidyr, ggplot2, latex2exp, reshape2, RColorBrewer
LinkingTo: Rcpp, RcppArmadillo, RcppProgress, rgen
Suggests: rmarkdown, knitr
Published: 2023-01-28
Author: Giorgio Paulon [aut, cre], Abhra Sarkar [aut, ctb]
Maintainer: Giorgio Paulon <giorgio.paulon at utexas.edu>
License: MIT + file LICENSE
NeedsCompilation: yes
Language: en-US
Materials: README
CRAN checks: lddmm results

Documentation:

Reference manual: lddmm.pdf
Vignettes: minimal_example

Downloads:

Package source: lddmm_0.2.0.tar.gz
Windows binaries: r-devel: lddmm_0.2.0.zip, r-release: lddmm_0.2.0.zip, r-oldrel: lddmm_0.1.0.zip
macOS binaries: r-release (arm64): lddmm_0.2.0.tgz, r-oldrel (arm64): lddmm_0.2.0.tgz, r-release (x86_64): lddmm_0.2.0.tgz, r-oldrel (x86_64): lddmm_0.2.0.tgz
Old sources: lddmm archive

Linking:

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