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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:0.4.2
Depends:R (≥ 4.1.0)
Imports:Rcpp (≥ 1.0.6),gtools,LaplacesDemon,dplyr,plyr,tidyr,ggplot2,latex2exp,reshape2,RColorBrewer
LinkingTo:Rcpp,RcppArmadillo,RcppProgress,rgen
Suggests:rmarkdown,knitr
Published:2024-01-17
DOI:10.32614/CRAN.package.lddmm
Author:Giorgio Paulon [aut, cre], Abhra Sarkar [aut, ctb]
Maintainer:Giorgio Paulon <giorgio.paulon at utexas.edu>
License:MIT + fileLICENSE
NeedsCompilation:yes
Language:en-US
Materials:README
CRAN checks:lddmm results

Documentation:

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

Downloads:

Package source: lddmm_0.4.2.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:

Please use the canonical formhttps://CRAN.R-project.org/package=lddmmto link to this page.


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