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lddmm  

Longitudinal Drift-Diffusion Mixed Models (LDDMM)
View on CRAN: Click here


Download and install lddmm package within the R console
Install from CRAN:
install.packages("lddmm")

Install from Github:
library("remotes")
install_github("cran/lddmm")

Install by package version:
library("remotes")
install_version("lddmm", "0.4.2")



Attach the package and use:
library("lddmm")
Maintained by
Giorgio Paulon
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-11-08
Latest Update: 2024-01-17
Description:
Implementation of the drift-diffusion mixed model for category learning as described in Paulon et al. (2021) .
How to cite:
Giorgio Paulon (2021). lddmm: Longitudinal Drift-Diffusion Mixed Models (LDDMM). R package version 0.4.2, https://cran.r-project.org/web/packages/lddmm
Previous versions and publish date:
0.1.0 (2021-11-08 13:10), 0.2.0 (2023-01-28 10:10), 0.2.1 (2023-01-31 18:00), 0.3.0 (2023-03-26 06:20), 0.4.0 (2023-06-06 15:20)
Other packages that cited lddmm R package
View lddmm citation profile
Other R packages that lddmm depends, imports, suggests or enhances
Functions, R codes and Examples using the lddmm R package
Some associated functions: B_basis . H_ball . LDDMM . P_smooth1 . compute_WAIC . data . extract_post_draws . extract_post_mean . log_likelihood . log_likelihood_ind . plot_RT . plot_accuracy . plot_post_pars . 
Some associated R codes: RcppExports.R . data.R . fcts.R . zzz.R .  Full lddmm package functions and examples
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