Package: dRiftDM 0.2.1.9000

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>).

Authors:Valentin Koob [cre, aut, cph], Thomas Richter [aut, cph], Markus Janczyk [ctb]

dRiftDM_0.2.1.9000.tar.gz
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dRiftDM.pdf |dRiftDM.html
dRiftDM/json (API)
NEWS

# Install 'dRiftDM' in R:
install.packages('dRiftDM', repos = c('https://bucky2177.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/bucky2177/driftdm/issues

Pkgdown site:https://bucky2177.github.io

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

cpp

6.03 score 6 stars 5 scripts 54 downloads 30 exports 17 dependencies

Last updated 18 hours agofrom:702a552dc5. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKJan 14 2025
R-4.5-win-x86_64OKJan 14 2025
R-4.5-linux-x86_64OKJan 14 2025
R-4.4-win-x86_64OKJan 14 2025
R-4.4-mac-x86_64OKJan 14 2025
R-4.4-mac-aarch64OKJan 14 2025
R-4.3-win-x86_64OKJan 14 2025
R-4.3-mac-x86_64OKJan 14 2025
R-4.3-mac-aarch64OKJan 14 2025

Exports:b_codingb_coding<-calc_statscoef<-comp_funscomp_funs<-component_shelfcondsdmc_dmdrift_dmestimate_modelestimate_model_idsflex_prmsflex_prms<-get_example_fits_idsload_fits_idsmodify_flex_prmsobs_dataobs_data<-prms_solveprms_solve<-ratcliff_dmre_evaluate_modelsimulate_datasimulate_tracessimulate_valuessolversolver<-ssp_dmunpack_traces

Dependencies:clicrayonDEoptimdfoptimgluehmslifecyclepkgconfigprettyunitsprogressR6rbibutilsRcppRdpackrlangvctrswithr

use_ddm_models

Rendered fromuse_ddm_models.Rmdusingknitr::rmarkdownon Jan 14 2025.

Last update: 2024-12-12
Started: 2023-11-16

Readme and manuals

Help Manual

Help pageTopics
The Coding of the Boundariesb_coding b_coding.drift_dm b_coding.fits_ids_dm b_coding<- b_coding<-.drift_dm
Calculate Statisticscalc_stats calc_stats.data.frame calc_stats.drift_dm calc_stats.fits_ids_dm
Convenient Coefficients Accesscoef.drift_dm coef.fits_ids_dm coef<- coef<-.drift_dm
The Component Functions of A Modelcomp_funs comp_funs.drift_dm comp_funs.fits_ids_dm comp_funs<- comp_funs<-.drift_dm
Diffusion Model Componentscomponent_shelf
The Conditions of an Objectconds conds.data.frame conds.drift_dm conds.fits_ids_dm conds.traces_dm_list
Create the Diffusion Model for Conflict Tasksdmc_dm
A synthetic data set with two conditionsdmc_synth_data
Create a drift_dm objectdrift_dm print.drift_dm
Estimate the Parameters of a drift_dm Modelestimate_model
Fit Multiple Individuals and Save Resultsestimate_model_ids
Flex_Prmsflex_prms flex_prms.drift_dm flex_prms.flex_prms flex_prms.numeric flex_prms<- flex_prms<-.drift_dm print.flex_prms
Auxiliary Function to create a fits_ids objectget_example_fits_ids
Plot Parameter Distribution(s)hist.coefs_dm
Load Estimates of a Fit Procedureload_fits_ids print.fits_ids_dm
Extract Log-Likelihood for a drift_dm ObjectlogLik.drift_dm
Extract Model Statistics for fits_ids_dm ObjectAIC.fits_ids_dm BIC.fits_ids_dm logLik.fits_ids_dm
Set Instructions to a flex_prms objectmodify_flex_prms modify_flex_prms.drift_dm modify_flex_prms.flex_prms
Get the Number of Observations for a drift_dm Objectnobs.drift_dm
The Observed Dataobs_data obs_data.drift_dm obs_data.fits_ids_dm obs_data<- obs_data<-.drift_dm
Plot Conditional Accuracy Functions (CAFs)plot.cafs
Plot Delta Functionsplot.delta_funs
Plot Components of a Drift Diffusion Modelplot.drift_dm
Plot Multiple Statisticsplot.list_stats_dm
Plot Quantilesplot.quantiles
Plot Traces of a Drift Diffusion Modelplot.traces_dm plot.traces_dm_list
Summary and Printing for fits_ids_dm Objectsprint.summary.fits_ids_dm summary.fits_ids_dm
The Parameters for Deriving Model Predictionsprms_solve prms_solve.drift_dm prms_solve.fits_ids_dm prms_solve<- prms_solve<-.drift_dm
Create a Basic Diffusion Modelratcliff_dm
A synthetic data set with one conditionratcliff_synth_data
Re-evaluate the modelre_evaluate_model
Set Default Colorsset_default_colors
Simulate Synthetic Responsessimulate_data simulate_data.drift_dm
Simulate Trajectories/Traces of a Modelprint.traces_dm print.traces_dm_list simulate_traces simulate_traces.drift_dm simulate_traces.fits_ids_dm
Simulate Traces for One Conditionssimulate_traces_one_cond
Simulate Valuessimulate_values
The Solver for Deriving Model Predictionssolver solver.drift_dm solver.fits_ids_dm solver<- solver<-.drift_dm
Create the Shrinking Spotlight Modelssp_dm
Summary for 'drift_dm' Objectsprint.summary.drift_dm summary.drift_dm
Summarizing Flex Parametersprint.summary.flex_prms summary.flex_prms
Exemplary Flanker Dataulrich_flanker_data
Exemplary Simon Dataulrich_simon_data
Unpack/Destroy Traces Objectsunpack_traces unpack_traces.traces_dm unpack_traces.traces_dm_list