fddm: Fast Implementation of the Diffusion Decision Model

Provides the probability density function (PDF), cumulative distribution function (CDF), and the partial derivatives of the PDF of 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.

Package details

AuthorKendal B. Foster [aut], Henrik Singmann [ctb, cre] (<https://orcid.org/0000-0002-4842-3657>)
MaintainerHenrik Singmann <singmann@gmail.com>
LicenseGPL (>= 2)
Version0.5-1
URL https://github.com/rtdists/fddm
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("fddm")

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fddm documentation built on March 18, 2022, 5:23 p.m.