ggdmc: Cognitive Models

Hierarchical Bayesian modelling. The 'ggdmc' package provides tools designed for fitting cognitive models, using population-based Markov Chain Monte Carlo (pMCMC) and fast C++ libraries. The paper by Heathcote, Lin, Reynolds, Strickland, Gretton, and Matzke (2018, <doi:10.3758/s13428-018-1067-y>) describes the early prototype of the package (by the version 0.4.2). The paper accompanied with the revamped latest version (> is under preparation Lin, Strickland, Reynold, and Heathcote (2018) and a further paper regarding the new pMCMC sampling modified based on Hu and Tsai's (2010) work is also under preparation. See 'citation("ggdmc")' for details.

Depends: R (≥ 3.4.0)
Imports: Rcpp (≥ 0.12.10), coda, rtdists, ggmcmc (≥ 0.7.3), stats, utils, data.table (≥ 1.10.4), tmvtnorm, ggplot2, matrixStats
LinkingTo: Rcpp (≥ 0.12.10), RcppArmadillo (≥, BH
Published: 2018-09-01
Author: Yi-Shin Lin [aut, cre], Andrew Heathcote [aut]
Maintainer: Yi-Shin Lin <yishin.lin at>
License: GPL-2
NeedsCompilation: yes
Citation: ggdmc citation info
Materials: README NEWS
CRAN checks: ggdmc results


Reference manual: ggdmc.pdf
Package source: ggdmc_0.2.5.2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X binaries: r-release: ggdmc_0.2.5.2.tgz, r-oldrel: not available
Old sources: ggdmc archive


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