ggdmcHeaders {ggdmcHeaders} | R Documentation |
'C++' Backend for the 'ggdmc' Ecosystem
Description
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 ggdmc package.
Details
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.
References
Voss, A., Rothermund, K., & Voss, J. (2004). Interpreting the parameters of the diffusion model: A empirical validation Memory and Cognition, 32(7), 1206–1220.
Ratcliff, R., & McKoon, G. (2008). The diffusion decision model: Theory and data for two-choice decision tasks. Neural Computation, 20(4), 873–922.
Brown S., & Heathcote, A. (2008). The simplest complete model of choice response time: Linear ballistic accumulation. Cognitive Psychology, 57(3), 153–178.