HSSM — Hierarchical Sequential Sampling Modeling

HSSM is a Python toolbox for hierarchical Bayesian modeling of choice and response-time data with sequential sampling models. It supports trial-wise and hierarchical regression, reinforcement-learning models, posterior diagnostics, model comparison, and custom likelihoods through a high-level PyMC and Bambi interface. HSSM is a BRAINSTORM project at Brown University.

Install

Use Python 3.12, 3.13, or 3.14 in a fresh environment:

pip install hssm

The installation guide covers uv, CUDA extras, Colab, development installs, and troubleshooting.

Start with the documentation

The HSSM documentation is the canonical source for durable guidance. Begin with the quickstart, then follow the main tutorial. The ecosystem map explains when work belongs in HSSM or one of its sibling projects.

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