Package: ggdmcHeaders 0.2.9.1

ggdmcHeaders: 'C++' Headers for 'ggdmc' Package

A fast 'C++' implementation of the design-based, Diffusion Decision Model (DDM) and the Linear Ballistic Accumulation (LBA) model. It enables the user to optimise the choice response time model by connecting with the Differential Evolution Markov Chain Monte Carlo (DE-MCMC) sampler implemented in the 'ggdmc' package. The package fuses the hierarchical modelling, Bayesian inference, choice response time models and factorial designs, allowing users to build their own design-based models. For more information on the underlying models, see the works by Voss, Rothermund, and Voss (2004) <doi:10.3758/BF03196893>, Ratcliff and McKoon (2008) <doi:10.1162/neco.2008.12-06-420>, and Brown and Heathcote (2008) <doi:10.1016/j.cogpsych.2007.12.002>.

Authors:Yi-Shin Lin [aut, cre]

ggdmcHeaders_0.2.9.1.tar.gz
ggdmcHeaders_0.2.9.1.zip(r-4.7)ggdmcHeaders_0.2.9.1.zip(r-4.6)ggdmcHeaders_0.2.9.1.zip(r-4.5)
ggdmcHeaders_0.2.9.1.tgz(r-4.6-any)ggdmcHeaders_0.2.9.1.tgz(r-4.5-any)
ggdmcHeaders_0.2.9.1.tar.gz(r-4.7-any)ggdmcHeaders_0.2.9.1.tar.gz(r-4.6-any)
ggdmcHeaders_0.2.9.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
ggdmcHeaders/json (API)

# Install 'ggdmcHeaders' in R:
install.packages('ggdmcHeaders', repos = c('https://yxlin.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/yxlin/ggdmcheaders/issues

On CRAN:

Conda:

4.56 score 6 packages 153 downloads 0 exports 0 dependencies

Last updated from:fb5066ac7b. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK93
source / vignettesOK115
linux-release-x86_64OK90
macos-release-arm64OK92
macos-oldrel-arm64OK92
windows-develOK57
windows-releaseOK65
windows-oldrelOK55
wasm-releaseOK79

Exports:

Dependencies: