Package: ggdmc
Type: Package
Title: Hierarchical Bayesian Inference for Choice Response Time Models
Version: 0.2.8.9
Date: 2025-08-08
Authors@R: c(person(given = "Yi-Shin", family = "Lin", role = c("aut", "cre"), email = "yishinlin001@gmail.com"))
Maintainer: Yi-Shin Lin <yishinlin001@gmail.com>
Description: Provides tools for fitting hierarchical Bayesian models of
        choice and response time using Differential Evolution Markov
        Chain Monte Carlo (DE-MCMC) sampling. Designed for cognitive
        scientists and psychologists, it supports models including the
        Linear Ballistic Accumulator (LBA) and Diffusion Decision Model
        (DDM), offering flexible parameter mapping and
        condition-specific modelling. Implements fast, parallelised C++
        routines for large-scale applications in decision modelling.
        Core functionality includes parameter sampling, simulation,
        model building, posterior recovery, and convergence
        diagnostics. Sampling methods follow Turner et al. (2013)
        <doi:10.1037/a0032222>, Braak (2006)
        <doi:10.1007/s11222-006-8769-1>, and Hu & Tsui (2010)
        <doi:10.1016/j.csda.2008.10.025>. The parameter mapping and
        condition-specific structure are based on Heathcote et al.
        (2018) <doi:10.3758/s13428-018-1067-y>.
License: GPL (>= 2)
Imports: ggdmcModel, ggdmcPrior, ggdmcLikelihood, Rcpp (>= 1.0.7),
        methods, data.table, matrixStats, lattice
Depends: R (>= 3.5.0)
LinkingTo: Rcpp (>= 1.0.7), RcppArmadillo (>= 0.10.7.5.0), ggdmcHeaders
Suggests: testthat (>= 3.0.0)
RoxygenNote: 7.3.2
Encoding: UTF-8
NeedsCompilation: yes
Repository: https://yxlin.r-universe.dev
Date/Publication: 2025-08-13 03:13:42 UTC
RemoteUrl: https://github.com/yxlin/ggdmc
RemoteRef: HEAD
RemoteSha: cee9795cce38dc606ce5bdf5436e7d92b88cdda9
Packaged: 2026-10-04 12:37:16 UTC; root
Author: Yi-Shin Lin [aut, cre]