This template is designed for creating artificial data, performing parameter recovery, and evaluating parameters in empirical data using Stan. This template facilitates the simulation of experimental data and the evaluation of model parameters.
By generating artificial data, you can test the robustness and accuracy of your models, ensuring they can reliably recover known parameters. Additionally, parameter recovery from empirical data allows for the validation and fine-tuning of models based on real-world experimental results.
The integration of these capabilities within the Stan framework enables efficient Bayesian inference and posterior sampling, making it a powerful tool for both theoretical and empirical research.
We provided you with a multi-level modeling of the 3 models we learned in the workshop, and you can create and add your own models.