Fast Implementation of the Diffusion Decision Model

Provides the probability density function (PDF) and cumulative distribution function (CDF) of the diffusion decision model (DDM; e.g., Ratcliff & McKoon, 2008, ) with across-trial variability in the drift rate. Because the PDF and CDF of the DDM both contain an infinite sum, they needs to be approximated. 'fddm' implements all published approximations (Navarro & Fuss, 2009, ; Gondan, Blurton, & Kesselmeier, 2014, ; Blurton, Kesselmeier, & Gondan, 2017, ) plus new approximations. All approximations are implemented purely in 'C++' providing faster speed than existing packages.


Reference manual

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0.4-1 by Henrik Singmann, a month ago

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Authors: Kendal B. Foster [aut] , Henrik Singmann [ctb, cre]

Documentation:   PDF Manual  

GPL (>= 2) license

Imports Rcpp

Suggests rtdists, RWiener, ggplot2, reshape2, testthat, knitr, rmarkdown, microbenchmark, ggnewscale, ggforce

Linking to Rcpp

System requirements: C++11

See at CRAN