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dRiftDM: Estimating (Time-Dependent) Drift Diffusion Models
Fit and explore Drift Diffusion Models (DDMs), a common tool in psychology for describing decision processes in simple tasks. It can handle both time-independent and time-dependent DDMs. You either choose prebuilt models or create your own, and the package takes care of model predictions and parameter estimation. Model predictions are derived via the numerical solutions provided by Richter, Ulrich, and Janczyk (2023, <doi:10.1016/j.jmp.2023.102756>).
Getting started
Browse package contents
Package details |
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| Author | Valentin Koob [cre, aut, cph], Thomas Richter [aut, cph], Markus Janczyk [aut] |
| Maintainer | Valentin Koob <v.koob@web.de> |
| License | MIT + file LICENSE |
| Version | 0.2.2 |
| URL | https://github.com/bucky2177/dRiftDM https://bucky2177.github.io/dRiftDM/ |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
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