fddm: Fast Implementation of the Diffusion Decision Model

Provides the probability density function (PDF), cumulative distribution function (CDF), the first-order and second-order partial derivatives of the PDF, and a fitting function for the diffusion decision model (DDM; e.g., Ratcliff & McKoon, 2008, <doi:10.1162/neco.2008.12-06-420>) with across-trial variability in the drift rate. Because the PDF, its partial derivatives, and the CDF of the DDM both contain an infinite sum, they need to be approximated. 'fddm' implements all published approximations (Navarro & Fuss, 2009, <doi:10.1016/j.jmp.2009.02.003>; Gondan, Blurton, & Kesselmeier, 2014, <doi:10.1016/j.jmp.2014.05.002>; Blurton, Kesselmeier, & Gondan, 2017, <doi:10.1016/j.jmp.2016.11.003>; Hartmann & Klauer, 2021, <doi:10.1016/j.jmp.2021.102550>) plus new approximations. All approximations are implemented purely in 'C++' providing faster speed than existing packages.

Version:	1.0-2
Depends:	R (≥ 3.5.0)
Imports:	Rcpp (≥ 1.0.1), stats, methods, Formula
LinkingTo:	Rcpp, RcppEigen
Suggests:	rtdists, RWiener, ggplot2, reshape2, testthat, knitr, rmarkdown, microbenchmark, ggnewscale, ggforce, WienR, emmeans, estimability, lmtest, numDeriv
Published:	2024-07-02
DOI:	10.32614/CRAN.package.fddm
Author:	Kendal B. Foster [aut], Henrik Singmann [ctb, cre], Achim Zeileis [ctb] (methods partially taken from betareg)
Maintainer:	Henrik Singmann <singmann at gmail.com>
BugReports:	https://github.com/rtdists/fddm/issues
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL:	https://github.com/rtdists/fddm
NeedsCompilation:	yes
Materials:	README, NEWS
CRAN checks:	fddm results

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