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)
The package is a collection of the 'C++' implementation of the choice response time model. It connects the model to the Differential Evolution Markov Chain Monte Carlo (DE-MCMC) sampler implemented in the \pkg{ggdmc} package.
The package supports the hierarchical modelling, Bayesian inference, choice response time models and factorial designs, allowing users to build their own design-based models.
The package serves as the C++ backends for the following packages: ggdmcModel, ggdmcPrior, ggdmcLikelihood, lbaModel, ddModel and ggdmc.