Other packages > Find by keyword >

DMCfun  

Diffusion Model of Conflict (DMC) in Reaction Time Tasks
View on CRAN: Click here


Download and install DMCfun package within the R console
Install from CRAN:
install.packages("DMCfun")

Install from Github:
library("remotes")
install_github("cran/DMCfun")

Install by package version:
library("remotes")
install_version("DMCfun", "4.0.1")



Attach the package and use:
library("DMCfun")
Maintained by
Ian G. Mackenzie
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-07-01
Latest Update: 2024-09-16
Description:
DMC model simulation detailed in Ulrich, R., Schroeter, H., Leuthold, H., & Birngruber, T. (2015). Automatic and controlled stimulus processing in conflict tasks: Superimposed diffusion processes and delta functions. Cognitive Psychology, 78, 148-174. Ulrich et al. (2015) . Decision processes within choice reaction-time (CRT) tasks are often modelled using evidence accumulation models (EAMs), a variation of which is the Diffusion Decision Model (DDM, for a review, see Ratcliff & McKoon, 2008). Ulrich et al. (2015) introduced a Diffusion Model for Conflict tasks (DMC). The DMC model combines common features from within standard diffusion models with the addition of superimposed controlled and automatic activation. The DMC model is used to explain distributional reaction time (and error rate) patterns in common behavioural conflict-like tasks (e.g., Flanker task, Simon task). This R-package implements the DMC model and provides functionality to fit the model to observed data. Further details are provided in the following paper: Mackenzie, I.G., & Dudschig, C. (2021). DMCfun: An R package for fitting Diffusion Model of Conflict (DMC) to reaction time and error rate data. Methods in Psychology, 100074. .
How to cite:
Ian G. Mackenzie (2020). DMCfun: Diffusion Model of Conflict (DMC) in Reaction Time Tasks. R package version 4.0.1, https://cran.r-project.org/web/packages/DMCfun. Accessed 06 Mar. 2026.
Previous versions and publish date:
0.12.0 (2020-07-01 10:40), 0.12.1 (2020-07-02 09:30), 0.15.0 (2020-09-20 17:50), 1.1.0 (2020-11-25 13:10), 1.3.0 (2021-01-10 18:50), 2.0.0 (2021-09-20 16:30), 2.0.2 (2021-10-25 09:30), 3.5.2 (2024-01-09 16:00), 3.5.4 (2024-02-24 17:20)
Other packages that cited DMCfun R package
View DMCfun citation profile
Other R packages that DMCfun depends, imports, suggests or enhances
Complete documentation for DMCfun
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

solitude  
An Implementation of Isolation Forest
Isolation forest is anomaly detection method introduced by the paper Isolation based Anomaly Detecti ...
Download / Learn more Package Citations See dependency  
DatabionicSwarm  
Swarm Intelligence for Self-Organized Clustering
Algorithms implementing populations of agents that interact with one another and sense their environ ...
Download / Learn more Package Citations See dependency  
openxlsx  
Read, Write and Edit xlsx Files
Simplifies the creation of Excel .xlsx files by providing a high level interface to writing, stylin ...
Download / Learn more Package Citations See dependency  
lbfgs  
Limited-memory BFGS Optimization
A wrapper built around the libLBFGS optimization library by Naoaki Okazaki. The lbfgs package implem ...
Download / Learn more Package Citations See dependency  
mlr3viz  
Visualizations for 'mlr3'
Visualization package of the 'mlr3' ecosystem. It features plots for mlr3 objects such as tasks, le ...
Download / Learn more Package Citations See dependency  
EMVS  
The Expectation-Maximization Approach to Bayesian Variable Selection
An efficient expectation-maximization algorithm for fitting Bayesian spike-and-slab regularization p ...
Download / Learn more Package Citations See dependency  

26,264

R Packages

223,360

Dependencies

70,244

Author Associations

26,265

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA