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R/Cpp implementation of the diffusion process model (Diffusion Model for Conflict Tasks, DMC) presented in Automatic and controlled stimulus processing in conflict tasks: Superimposed diffusion processes and delta functions (https://www.sciencedirect.com/science/article/pii/S0010028515000195)
CRAN https://cran.r-project.org/web/packages/DMCfun/index.html
The package is presented in the following paper:
https://www.sciencedirect.com/science/article/pii/S259026012100031X
# install version from CRAN
install.packages("DMCfun")
library(DMCfun)
# install version from GitHub
# install.packages("devtools")
devtools::install_github("igmmgi/DMCfun")
dmc$means
Comp rtCor sdRtCor perErr rtErr sdRtErr
1 comp 440. 105. 0.633 479. 104.
2 incomp 459. 94.8 1.38 406. 95.2
dmc$means
Comp rtCor sdRtCor perErr rtErr sdRtErr
1 comp 421. 90.4 0.259 504. 119.
2 incomp 484. 103. 2.37 425. 82.7
params <- list(tau = seq(20, 170, 10))
dmc <- dmcSims(params)
plot(dmc, ncol = 2, col = c("red", "green"))
summary(fit)
amp tau drc bnds resMean resSD aaShape spShape sigm rmse
1 19.3 98.8 0.593 55.8 325. 28.4 2.26 2.84 4 8.91
amp tau drc bnds resMean resSD aaShape spShape sigm RMSE
1 16.91 47.77 0.59 56.68 317.16 33.43 1.68 3.53 4 10.01
summary(fit)
amp tau drc bnds resMean resSD aaShape spShape sigm RMSE
1 17.26 222.19 0.64 57.49 328.06 28.41 1.7 2.18 4 5.79
amp tau drc bnds resMean resSD aaShape spShape sigm RMSE
1 14.31 42.29 0.55 57.54 308.63 25.98 2.15 3.56 4 8.86
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