Package: dRiftDM 0.3.2
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:
dRiftDM_0.3.2.tar.gz
dRiftDM_0.3.2.zip(r-4.7)dRiftDM_0.3.2.zip(r-4.6)dRiftDM_0.3.2.zip(r-4.5)
dRiftDM_0.3.2.tgz(r-4.6-x86_64)dRiftDM_0.3.2.tgz(r-4.6-arm64)dRiftDM_0.3.2.tgz(r-4.5-x86_64)dRiftDM_0.3.2.tgz(r-4.5-arm64)
dRiftDM_0.3.2.tar.gz(r-4.7-arm64)dRiftDM_0.3.2.tar.gz(r-4.7-x86_64)dRiftDM_0.3.2.tar.gz(r-4.6-arm64)dRiftDM_0.3.2.tar.gz(r-4.6-x86_64)
dRiftDM_0.3.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
dRiftDM/json (API)
| # Install 'dRiftDM' in R: |
| install.packages('dRiftDM', repos = c('https://bucky2177.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/bucky2177/driftdm/issues
Pkgdown/docs site:https://bucky2177.github.io
Datasets:
- dmc_synth_data - A synthetic data set with two conditions
- ratcliff_synth_data - A synthetic data set with one condition
- ssp_synth_data - A synthetic data set with two conditions
- ulrich_flanker_data - Exemplary Flanker Data
- ulrich_simon_data - Exemplary Simon Data
Last updated from:8150cee230. Checks:13 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 193 | ||
| linux-devel-x86_64 | OK | 261 | ||
| source / vignettes | OK | 319 | ||
| linux-release-arm64 | OK | 217 | ||
| linux-release-x86_64 | OK | 215 | ||
| macos-release-arm64 | OK | 152 | ||
| macos-release-x86_64 | OK | 430 | ||
| macos-oldrel-arm64 | OK | 137 | ||
| macos-oldrel-x86_64 | OK | 274 | ||
| windows-devel | OK | 235 | ||
| windows-release | OK | 239 | ||
| windows-oldrel | OK | 187 | ||
| wasm-release | OK | 156 |
Exports:b_codingb_coding<-calc_statscheck_discretizationcoef<-comp_funscomp_funs<-component_shelfcondsconds<-cost_functioncost_function<-cost_valueddm_optsddm_opts<-dmc_dmdrift_dmestimate_dmestimate_modelestimate_model_idsflex_prmsflex_prms<-get_example_fitsget_lower_upperload_fits_idsmodify_flex_prmsobs_dataobs_data<-pdfsprms_solveprms_solve<-ratcliff_dmre_evaluate_modelsimulate_datasimulate_tracessimulate_valuessolversolver<-ssp_dmunpack_objunpack_traces
Dependencies:clicodacrayonDEoptimdfoptimgluehmslatticelifecyclemagrittrmirainanonextpbapplypkgconfigprettyunitsprogresspurrrR6rbibutilsRcppRdpackrlangvctrswithr
How To Perform a Model Recovery
Last update: 2025-12-05
Started: 2025-11-17
Introduction to dRiftDM
An Examplary Model | Basic Properties of a Model | Exploring a Model | simulate_traces() | calc_stats() | Changing Model Properties | coef() | prms_solve() | Remark: Discretization Settings | solver() | b_coding() | obs_data() | The summary() Function | Fitting a Model | Fitting a Model Separately to Individual Data Using Classical Optimization Techniques | Remark: Fitting Just One Individual | Fitting a Model to Aggregated Data Using Classical Optimization Techniques | Checking Model Fit | Extracting Parameter Estimates and Fit Statistics | Experimental: Perform Bayesian Parameter Estimation | Simulating Data | Remark: Stripping Away "Unnecesary" Attributes and Class Labels
Last update: 2025-12-01
Started: 2025-02-26
Core DDM Parameters: Impact on RTs and Accuracy
Last update: 2025-11-17
Started: 2025-10-17
How To Customize DDMs
The Model Structure in dRiftDM | Modifying flex_prms objects | Modifying How Each Parameter Behaves Across Conditions | Defining New Conditions | Customizing Component Functions | Example 1: Custom Drift Rate | Example 2: Custom Starting Point (Distribution) | Example 3: Custom Boundary | Example 4: Custom Non-Decision Time | Final Comments | Remark: Trial-by-Trial Variability in the Drift Rate
Last update: 2025-11-17
Started: 2025-02-26
How to Convert DMC's parameters
The Mathematical Equations | Scaling for the Diffusion Constant | Scaling the Time Space | An R Helper Function | References
Last update: 2025-10-17
Started: 2025-02-26
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| The Coding of the Boundaries | b_coding b_coding.drift_dm b_coding.fits_agg_dm b_coding.fits_ids_dm b_coding<- b_coding<-.drift_dm |
| Calculate Statistics | calc_stats calc_stats.data.frame calc_stats.drift_dm calc_stats.fits_agg_dm calc_stats.fits_ids_dm print.stats_dm print.stats_dm_list |
| Check time/space discretization via reference comparison | check_discretization check_discretization.drift_dm check_discretization.fits_agg_dm check_discretization.fits_ids_dm |
| Access Coefficients of a Model | coef.drift_dm coef.fits_agg_dm coef.fits_ids_dm coef.mcmc_dm coef<- coef<-.drift_dm print.coefs_dm |
| The Component Functions of A Model | comp_funs comp_funs.drift_dm comp_funs.fits_agg_dm comp_funs.fits_ids_dm comp_funs<- comp_funs<-.drift_dm |
| Diffusion Model Components | component_shelf |
| The Conditions of an Object | conds conds.data.frame conds.drift_dm conds.fits_agg_dm conds.fits_ids_dm conds.traces_dm_list conds<- conds<-.drift_dm |
| Access/Replace the Cost Function Label and Access the Cost Function Value | cost_function cost_function.drift_dm cost_function.fits_agg_dm cost_function.fits_ids_dm cost_function<- cost_function<-.drift_dm cost_value cost_value.drift_dm cost_value.fits_agg_dm cost_value.fits_ids_dm |
| Optional Arguments for the Component Functions | ddm_opts ddm_opts.drift_dm ddm_opts.fits_agg_dm ddm_opts<- ddm_opts<-.drift_dm |
| Create the Diffusion Model for Conflict Tasks | dmc_dm |
| A synthetic data set with two conditions | dmc_synth_data |
| Create a drift_dm object | drift_dm print.drift_dm |
| Fit a DDM to Observed Data | estimate_dm print.fits_agg_dm print.fits_ids_dm print.mcmc_dm |
| Estimate the Parameters of a drift_dm Model | estimate_model |
| Fit Multiple Individuals and Save Results | estimate_model_ids |
| Flex_Prms | flex_prms flex_prms.drift_dm flex_prms.flex_prms flex_prms.numeric flex_prms<- flex_prms<-.drift_dm print.flex_prms |
| Auxiliary Function to load a 'fits_ids_dm', 'fits_agg_dm', or 'mcmc_dm' object | get_example_fits |
| Get Default Parameter Ranges for a Model | get_lower_upper get_lower_upper.drift_dm |
| Plot Parameter Distribution(s) | hist.coefs_dm |
| Load Estimates of a Fit Procedure | load_fits_ids |
| Extract Log-Likelihood for a drift_dm Object | logLik.drift_dm |
| Extract Model Statistics for fits_ids_dm Object | AIC.fits_ids_dm BIC.fits_ids_dm logLik.fits_ids_dm |
| Set Instructions to a flex_prms object | modify_flex_prms modify_flex_prms.drift_dm modify_flex_prms.flex_prms |
| Get the Number of Observations for a drift_dm Object | nobs.drift_dm |
| The Observed Data | obs_data obs_data.drift_dm obs_data.fits_agg_dm obs_data.fits_ids_dm obs_data<- obs_data<-.drift_dm |
| Access the Probability Density Functions of a Model | pdfs pdfs.drift_dm pdfs.fits_agg_dm |
| Plot Conditional Accuracy Functions (CAFs) | plot.cafs |
| Plot Delta Functions | plot.delta_funs |
| Plot Distributions of Predicted and Observed Data | plot.densities |
| Plot Components of a Drift Diffusion Model | plot.drift_dm |
| Plot MCMC Results and Diagnostics for 'mcmc_dm' Objects | plot.mcmc_dm |
| Plot Response Time Quantiles | plot.quantiles |
| Plot Multiple Statistics | plot.stats_dm_list |
| Plot Traces of a Drift Diffusion Model | plot.traces_dm plot.traces_dm_list |
| Summary and Printing for 'fits_agg_dm' Objects | print.summary.fits_agg_dm summary.fits_agg_dm |
| Summary and Printing for fits_ids_dm Objects | print.summary.fits_ids_dm summary.fits_ids_dm |
| The Parameters for Deriving Model Predictions | prms_solve prms_solve.drift_dm prms_solve.fits_agg_dm prms_solve.fits_ids_dm prms_solve<- prms_solve<-.drift_dm |
| Create a Basic Diffusion Model | ratcliff_dm |
| A synthetic data set with one condition | ratcliff_synth_data |
| Re-evaluate the model | re_evaluate_model |
| Simulate Synthetic Responses | simulate_data simulate_data.drift_dm |
| Simulate Trajectories/Traces of a Model | print.traces_dm print.traces_dm_list simulate_traces simulate_traces.drift_dm simulate_traces.fits_agg_dm simulate_traces.fits_ids_dm |
| Simulate Traces for One Conditions | simulate_traces_one_cond |
| Simulate Values | simulate_values |
| The Solver for Deriving Model Predictions | solver solver.drift_dm solver.fits_agg_dm solver.fits_ids_dm solver<- solver<-.drift_dm |
| Create the Shrinking Spotlight Model | ssp_dm |
| A synthetic data set with two conditions | ssp_synth_data |
| Summary for 'coefs_dm' Objects | print.summary.coefs_dm summary.coefs_dm |
| Summary for 'drift_dm' objects | print.summary.drift_dm summary.drift_dm |
| Summarizing Flex Parameters | print.summary.flex_prms summary.flex_prms |
| Summary for 'mcmc_dm' Objects | print.summary.mcmc_dm summary.mcmc_dm |
| Summary for 'stats_dm' Objects | print.summary.basic_stats print.summary.cafs print.summary.delta_funs print.summary.fit_stats print.summary.quantiles print.summary.stats_dm print.summary.stats_dm_list print.summary.sum_dist summary.basic_stats summary.cafs summary.delta_funs summary.fit_stats summary.quantiles summary.stats_dm summary.stats_dm_list summary.sum_dist |
| Summary for traces_dm and traces_dm_list Objects | print.summary.traces_dm print.summary.traces_dm_list summary.traces_dm summary.traces_dm_list |
| Exemplary Flanker Data | ulrich_flanker_data |
| Exemplary Simon Data | ulrich_simon_data |
| Unpack/Destroy dRiftDM Objects | unpack_obj unpack_obj.coefs_dm unpack_obj.stats_dm unpack_obj.stats_dm_list unpack_obj.traces_dm unpack_obj.traces_dm_list |
| Unpack/Destroy Traces Objects | unpack_traces unpack_traces.traces_dm unpack_traces.traces_dm_list |
