Introduction to Optimization and Bayesian Inference for Model Fitting

Tutorials on statistical model fitting (optimization and Bayesian inference) for Day 2 of the BAMB! 2022 summer school for advanced modeling of behavior. The provided tutorials are in MATLAB, but the content is language-independent.

Lecturer: Luigi Acerbi, @AcerbiLuigi (University of Helsinki).

• To run the tutorials, download / clone the repository locally.
• Ensure that the BADS and VBMC toolboxes are installed (see below).
• Introduction to Optimization for Statistical Model fitting: slides, code.
• Introduction to Bayesian Inference for Statistical Model fitting: slides, code.
• Visualization of optimization algorithms: https://github.com/lacerbi/optimviz

Toolboxes for model fitting

The tutorials use the following open-source MATLAB toolboxes. You will need to install them from here:

• Bayesian Adaptive Direct Search (BADS) optimization algorithm: https://github.com/lacerbi/bads
• Variational Bayesian Monte Carlo (VBMC) inference algorithm: https://github.com/lacerbi/vbmc

License

Unless stated otherwise, the material in this repo is released under the MIT License.