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dmcfun

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)

https://github.com/igmmgi/dmcfun

Science Score: 33.0%

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    Links to: sciencedirect.com
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    1 of 4 committers (25.0%) from academic institutions
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    Low similarity (8.2%) to scientific vocabulary
Last synced: 10 months ago · JSON representation

Repository

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)

Basic Info
  • Host: GitHub
  • Owner: igmmgi
  • License: other
  • Language: R
  • Default Branch: master
  • Homepage:
  • Size: 17.4 MB
Statistics
  • Stars: 18
  • Watchers: 1
  • Forks: 6
  • Open Issues: 4
  • Releases: 0
Created almost 8 years ago · Last pushed over 1 year ago
Metadata Files
Readme License

README.md

DMCfun

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

Installation

``` r

install version from CRAN

install.packages("DMCfun") library(DMCfun)

install version from GitHub

install.packages("devtools")

devtools::install_github("igmmgi/DMCfun") ```

Basic Examples DMC Simulation

r dmc <- dmcSim(fullData = TRUE) plot(dmc) alt text

r 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

r dmc <- dmcSim(fullData = TRUE, tau = 150) plot(dmc) alt text

r 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

r params <- list(tau = seq(20, 170, 10)) dmc <- dmcSims(params) plot(dmc, ncol = 2, col = c("red", "green")) alt text

Basic Examples DMC Fit: Real data using optimx (Nelder-Mead)

r fit <- dmcFit(flankerData) # flanker data from Ulrich et al. (2015) plot(fit, flankerData) alt text

r 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

r fit <- dmcFit(simonData) # simon data from Ulrich et al. (2015) plot(fit, simonData) alt text

r 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

Basic Examples DMC Fit: Real data using DEoptim

r fit <- dmcFitDE(flankerData) # flanker data from Ulrich et al. (2015) plot(fit, flankerData) alt text

r 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

r fit <- dmcFitDE(simonData) # simon data from Ulrich et al. (2015) plot(fit, simonData) alt text

r 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

Owner

  • Login: igmmgi
  • Kind: user

GitHub Events

Total
  • Issues event: 1
  • Watch event: 1
  • Push event: 1
Last Year
  • Issues event: 1
  • Watch event: 1
  • Push event: 1

Committers

Last synced: over 2 years ago

All Time
  • Total Commits: 433
  • Total Committers: 4
  • Avg Commits per committer: 108.25
  • Development Distribution Score (DDS): 0.014
Past Year
  • Commits: 50
  • Committers: 1
  • Avg Commits per committer: 50.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
ian i****e@u****e 427
igm i****e@u****e 3
Tillmann Nett m****l@t****e 2
ian i****n@w****x 1
Committer Domains (Top 20 + Academic)
w541.fritz.box: 1 tcrueger.de: 1 unni-tuebingen.de: 1 uni-tuebingen.de: 1

Issues and Pull Requests

Last synced: 11 months ago

All Time
  • Total issues: 9
  • Total pull requests: 3
  • Average time to close issues: about 16 hours
  • Average time to close pull requests: about 13 hours
  • Total issue authors: 7
  • Total pull request authors: 2
  • Average comments per issue: 0.89
  • Average comments per pull request: 1.0
  • Merged pull requests: 2
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 1
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 1
  • Pull request authors: 0
  • Average comments per issue: 0.0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • LiKao (3)
  • milleratotago (1)
  • ArcticShorer-Williams (1)
  • ezrp (1)
  • HeatherUrry (1)
  • suwangcn (1)
Pull Request Authors
  • LiKao (2)
  • lboel (1)
Top Labels
Issue Labels
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • cran 291 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 10
  • Total maintainers: 1
cran.r-project.org: DMCfun

Diffusion Model of Conflict (DMC) in Reaction Time Tasks

  • Versions: 10
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 291 Last month
Rankings
Forks count: 14.9%
Stargazers count: 15.1%
Average: 27.7%
Dependent packages count: 29.8%
Dependent repos count: 35.5%
Downloads: 43.4%
Maintainers (1)
ian.mackenzie@uni-tuebingen.de
Last synced: 11 months ago

Dependencies

DESCRIPTION cran
  • R >= 3.5.0 depends
  • DEoptim * imports
  • Rcpp >= 0.12.16 imports
  • dplyr >= 1.0.0 imports
  • parallel * imports
  • pbapply * imports
  • tidyr * imports
  • ggplot2 * suggests
  • scales * suggests
  • shiny * suggests
  • testthat * suggests