R Package to Calculate the PDF and CDF of Evidence Accumulation Models | Overview | 0 Preparation | 1 Random Sampling | 2 Calculating the PDF and CDF | 3 Fitting a Model to Data | 4. Implement your custom EAM | 4.1 Option 1: use R or Rcpp functions | 4.1.1 Define R or Rcpp functions | 4.1.2 Register the functions for ream | 4.1.3 Run the new implementation of LIM and compare it to LIM | 4.1.4 Using Rcpp instead | 4.2.2 Register the functions for ream | 4.2.3 Run the new implementation of LIM and compare it to LIM | 4.3 Option 3: change the package | 4.3.1 Get the source code | 4.3.2 Get your system ready | 4.3.3 What source files to modify | 4.3.4 How to modify the necessary class methods | 4.3.5 Recompile the R package | 4.3.6 Some notes | References

Overview | 1 Detailed explanation of the steps | 1.1 Model converter | 1.2 Model specifications | 1.2.1 Model restrictions of ertmpt models | Modifying process probabilities | Modifying process completion times | 1.2.2 Model restrictions of drtmpt models | Modifying the threshold parameter in a process | Modifying the drif rate parameter in a process | Modifying the relative starting point parameter in a process | 1.2.3 Modifying motor and exectution times | 1.3 The right data format | 1.4 Model fitting | 1.5 Checking model convergence and getting a summary | 2 Equation and model files | 2.1 Equation files | 2.2 Model files | 3 Data transformation | 3.1 Labels in a data file | 3.2 Numbers in a data file | 4 Data simulation and simulation-based calibration | Data simulation | 4.1 Simulation-based calibration | References