Estimating (Time-Dependent) Drift Diffusion Models
Convolute the First Passage Times with the Non-Decision Time Distribut...
Aggregate Statistics Across ID
The Coding of the Boundaries
Constant Boundary
Collapsing Boundary - Hyperbolic Ratio Function
Collapsing Boundary - Weibull Function
Calculate Basic Mean, Standard Deviations, and Percentages for Observe...
Calculate Basic Statistics for Response Times or Probability Densities
Calculate CAFs
Calculate CAFs
Calculate delta function(s)
Calculate and Combine Density Estimates for Observed and Predicted Dat...
Calculate Fit Statistics
Calculate the Log-Likelihood
Calculate the PDFs
Calculate Quantiles
Calculate Quantiles
RMSE Calculation and Helpers
Calculate Statistics for Model Prediction and/or Observed Data
Calculate Statistics
Metropolis Acceptance Step for Vectorized MCMC Sampling
Check a B_Coding
Checks if a variable/vector of length 1 is a number > 0 or 0/expressio...
Check time/space discretization via reference comparison
Check if Object is a Named Numeric Vector
checks if all entries of internal_list are an expression or integer. T...
Check and Reduce the Observed Data
Access Coefficients of a Model
The Component Functions of A Model
Evaluate all Component Functions
Diffusion Model Components
The Conditions of an Object
Copy Class Attributes from One Object to Another
Access/Replace the Cost Function Label and Access the Cost Function Va...
Count the number of digits > 0
Create a matrix for lower and upper
Create "Temperatures" for TIDE
Perform Crossover Between Chains
Default Prior for Group-Level (Hyper) Parameters
Optional Arguments for the Component Functions
Default Values for the dRiftDM Package
Create the Diffusion Model for Conflict Tasks
Temporarily suppress new stats generation during resampling
Draw Samples Using Inverse Transform Sampling
Available Cost Functions for Model Estimation
Pre-built Drift Diffusion Models
Available types of statistics
Create a drift_dm object
dRiftDM: Estimating (Time-Dependent) Drift Diffusion Models
Maybe droplevels of ID column
Derivative of a Constant Boundary
Truncated Normal Density Function
(Hierarchical) Bayesian Estimation with Differential Evolution
(Hierarchical) Bayesian Estimation
Internal wrapper for classical estimation of individuals
Estimate Parameters of a drift_dm Model via Classical Optimization
Fit a DDM to Observed Data
Fit Multiple Individuals and Save Results
Estimate the Parameters of a drift_dm Model
Specify custom parameters
Exclude parameters from being modified (i.e., fix it; internal docu)
Flex_Prms
Set parameters as equal across conditions
Set special dependencies (internal docu)
Set a specific value to the parameter matrix (internal docu)
Allow parameters to vary
Perform a Full Crossover Step Using Differential Evolution
Compute average trials per condition across individuals
Get default/fall back component functions
Generate Prior Functions for Model Parameters
Auxiliary Function to load a fits_ids_dm, fits_agg_dm, or `mcmc_dm...
Compute EZ Diffusion parameters
Get Default Parameter Ranges for a Model
Turn default/special parameter specifications to vectors
TITLE
Extract a Subset of MCMC Chains
Plot Parameter Distribution(s)
Aggregate Data Frame Columns by Group
Turn an internal list to a matrix
Check if an object of length <= 1 is either empty or contains entry wi...
Check if an object is a valid numeric vector
Relabel the internal list
Load Estimates of a Fit Procedure
Conditional Log-Posterior Distributions for MCMC Sampling
Extract Log-Likelihood for a drift_dm Object
Extract Model Statistics for fits_ids_dm Object
Get the maximum number from an internal entry or flex_prms_obj (intern...
Convert MCMC Chain Array to a coda::mcmc.list Object
Perform a Migration Step Between Chains
Set Instructions to a flex_prms object
Constant Drift Rate
Drift Rate for DMC
Integral of Constant Drift Rate
Integral of DMC's Drift Rate
Drift Rate for SSP
Create a DDM model --- internal
Create a New stats_dm Object
Get the Number of Observations for a drift_dm Object
Constant Non-Decision time
Truncated Normally-Distributed Non-Decision Time
Uniform Non-Decision Time
Disassemble an Observed Data set
The Observed Data
Access the Probability Density Functions of a Model
Plot MCMC Chains for Drift Diffusion Model Parameters
Plot Conditional Accuracy Functions (CAFs)
Plot Delta Functions
Plot Distributions of Predicted and Observed Data
Plot Components of a Drift Diffusion Model
Plot MCMC Results and Diagnostics for mcmc_dm Objects
Plot Response Time Quantiles
Plot Multiple Statistics
Plot Traces of a Drift Diffusion Model
Print Functions for Stats Objects
Generate Parameter-Condition Labels
Unique Conditions-Parameter Combinations
Extract the conditions and parameters from an instruction string
The Parameters for Deriving Model Predictions
Format Parameters as String
Create a Basic Diffusion Model
Re-evaluate the model
Remove flags added when calling estimate_classical
Internal Helpers for Resampling of Summary Statistics
Set aggregated data to a model object
Set default graphical parameters for plotting in dRiftDM
Set Default Colors
Set one specific aspect of the solver settings
Simulate Synthetic Responses
Simulate one data set
Simulate Traces for One Conditions
Simulate Trajectories/Traces of a Model
Simulate Values
The Solver for Deriving Model Predictions
Sorts the numbers in ascending order
Create the Shrinking Spotlight Model
Get Quantiles/CAFs from PDFs and stats_agg_info
Resample Observed and Predicted Statistics for Interval Estimation
Helper to get, set, or reset package-global options for statistics
Reads Info file
Summary for coefs_dm Objects
Summary for drift_dm objects
Summary and Printing for fits_agg_dm Objects
Summary and Printing for fits_ids_dm Objects
Summarizing Flex Parameters
Summary for mcmc_dm Objects
Summary for stats_dm Objects
Summary for traces_dm and traces_dm_list Objects
Numerical integration using the trapezoidal rule
Convert Character Digits to Numeric Digits
Unpack/Destroy dRiftDM Objects
Unpack/Destroy Traces Objects
Update all prms
Update aggregated statistics in a drift_dm object
Validate a DDM object
Validate a an Object of Type fits_ids_dm
checks if a flex_prms_object is parameterized in a reasonable way
Validate a stats_dm Object
Beta-Shaped Starting Point Distribution Centered Around Zero
Constant Starting Point at Zero
Uniform Starting Point Distribution Centered Around Zero
Update the parameter matrix for vector inputs (internal docu)
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>).
Useful links