bauer: Bayesian Estimation of Perceptual, Numerical and Risky Choice

bauer is a PyMC-based Python library for fitting hierarchical Bayesiancognitive models to behavioural decision-making data. It covers magnitudecomparison, psychometric functions, and risky choice tasks, and is designedfor cognitive models that are ill-posed at the per-participant level. Documentation Full documentation, tutorials, and API reference:https://ruffgroup.github.io/bauer/ Source code https://github.com/ruffgroup/bauer Citing bauer If you use bauer in your research, please cite this Zenodo record(DOI: 10.5281/zenodo.20008828). Related software - braincoder for fitting encoding models and Bayesian decoding of stimulus features from neural data.