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.
- Version1.0-2
- R versionunknown
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?Yes
- Last release07/02/2024
Documentation
Team
Henrik Singmann
MaintainerShow author detailsAchim Zeileis
Show author detailsRolesContributorKendal B. Foster
Show author detailsRolesAuthor
Insights
Last 30 days
This package has been downloaded 273 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 9 times.
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Last 365 days
This package has been downloaded 3,743 times in the last 365 days. Now we’re talking! This work is officially 'heard of in academic circles', just like those wild research papers on synthetic bananas. The day with the most downloads was Jul 04, 2024 with 48 downloads.
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Dependencies
- Imports2 packages
- Suggests15 packages
- Linking To2 packages