ggdmc: Supersonic DMC
In TasCL/ggdmc: Dynamic Model of Choice with Parallel Computation, and C++ Capabilities
Description
Author(s)
References
Description
ggdmc implements graphic grammar, Rcpp, and Open MPI for
Andrew Heathcote's Dynamic Models of Choice (DMC), an algorithm for fitting
various evidence accumulation models via differential evolution MCMC
sampler. Currently, ggdmc implements only drift-diffusion model.
Author(s)
Yi-Shin Lin <yishin.lin@utas.edu.au>
Andrew Heathcote <andrew.heathcote@utas.edu.au>
References
Turner, B. M., & Sederberg P. B. (2012). Approximate
Bayesian computation with differential evolution,
Journal of Mathematical Psychology, 56, 375–385.
Ter Braak (2006). A Markov Chain Monte Carlo version of the genetic
algorithm Differential Evolution: easy Bayesian computing for real
parameter spaces. Statistics and Computing, 16, 239-249.
TasCL/ggdmc documentation built on May 9, 2019, 4:19 p.m.
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Description Author(s) References
Description
ggdmc implements graphic grammar, Rcpp, and Open MPI for Andrew Heathcote's Dynamic Models of Choice (DMC), an algorithm for fitting various evidence accumulation models via differential evolution MCMC sampler. Currently, ggdmc implements only drift-diffusion model.
Author(s)
Yi-Shin Lin <yishin.lin@utas.edu.au>
Andrew Heathcote <andrew.heathcote@utas.edu.au>
References
Turner, B. M., & Sederberg P. B. (2012). Approximate
Bayesian computation with differential evolution,
Journal of Mathematical Psychology, 56, 375–385.
Ter Braak (2006). A Markov Chain Monte Carlo version of the genetic
algorithm Differential Evolution: easy Bayesian computing for real
parameter spaces. Statistics and Computing, 16, 239-249.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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