Demos
- Fitting go/no-go using the chi-qsuare approach
- Tutorial for analyzing instrumental learning data with the HDDMrl module
- OUTLINE
- 1. Background
- 2. Installing the module
- 3. How the RLDDM works
- 4. Structuring data
- 5. Running basic model
- 6. Checking results
- 7. Posterior predictive checks
- 8. Parameter recovery
- 9. Separate learning rates for positive and negative prediction errors
- Posterior predictive check
- 10. depends_on vs. split_by
- 11. Probabilistic binary outcomes vs. normally distributed outcomes
- 12. HDDMrlRegressor
- 13. Regular RL without RT
- Posterior predictive check
- Tutorial for analyzing instrumental learning data with the HDDMnnRL module