Package: lddmm 0.4.2

Giorgio Paulon
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>.
Authors:
lddmm_0.4.2.tar.gz
lddmm_0.4.2.tar.gz(r-4.7-arm64)lddmm_0.4.2.tar.gz(r-4.7-x86_64)lddmm_0.4.2.tar.gz(r-4.6-arm64)lddmm_0.4.2.tar.gz(r-4.6-x86_64)
lddmm_0.4.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
lddmm/json (API)
| # Install 'lddmm' in R: |
| install.packages('lddmm', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- data - Example dataset
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:1f9ee65044. Checks:6 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 168 | ||
| linux-devel-x86_64 | OK | 187 | ||
| source / vignettes | OK | 224 | ||
| linux-release-arm64 | OK | 155 | ||
| linux-release-x86_64 | OK | 164 | ||
| wasm-release | OK | 160 |
Exports:B_basiscompute_WAICdataextract_post_drawsextract_post_meanH_ballLDDMMlog_likelihoodlog_likelihood_indP_smooth1plot_accuracyplot_post_parsplot_RT
Dependencies:clicpp11dplyrfarvergenericsggplot2gluegtablegtoolsisobandlabelingLaplacesDemonlatex2explifecyclemagrittrpillarpkgconfigplyrpurrrR6RColorBrewerRcppRcppArmadilloRcppProgressreshape2rgenrlangS7scalesstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Spline Basis Functions | B_basis |
| Calculate WAIC | compute_WAIC |
| Example dataset | data |
| Parameter posterior draws | extract_post_draws |
| Parameter posterior means | extract_post_mean |
| Hamming Ball | H_ball |
| Drift Diffusion Model Fit | LDDMM |
| Log-likelihood computation | log_likelihood |
| Log-likelihood computation for a single observation | log_likelihood_ind |
| Spline Penalty Matrix | P_smooth1 |
| Descriptive plots | plot_accuracy |
| Plot posterior estimates | plot_post_pars |
| Descriptive plots | plot_RT |