Reference

This section records the public HSSM interfaces and project metadata. Use the learning index for guided examples or the how-to index for task-oriented procedures.

Core modeling interfaces

• hssm.HSSM builds and fits an HSSM model.
• hssm.aDDM and hssm.aDDMConfig provide the specialized attentional drift-diffusion interface.
• hssm.Param, hssm.Prior, and hssm.Link describe parameter formulas, priors, and links.
• hssm.ModelConfig describes registered model configurations.
• hssm.rl contains the reinforcement-learning interfaces.
• Built-in models and likelihoods records every hssm.HSSM(model=...) name, configured likelihood kind, parameter, and choice.
• The ONNX likelihood contract records the portable artifact boundary for approximate differentiable likelihoods.

Functions and specialized modules

• hssm.list_data lists package-supplied datasets.
• hssm.load_data loads package-supplied datasets.
• hssm.simulate_data simulates supported models.
• hssm.show_defaults inspects model defaults.
• hssm.set_floatX selects floating-point precision.
• hssm.check_data_for_rl validates RLSSM data.
• hssm.list_models and hssm.register_model discover and extend the HSSM model registry.
• hssm.likelihoods records likelihood interfaces.
• hssm.distribution_utils records distribution helpers.
• hssm.plotting records plotting functions.

Project reference

• Changelog — release-by-release behavior changes.
• Ecosystem map — package ownership and contributor routes across the native HSSM ecosystem.
• Contribution guide and local development setup.
• Credits and license.

Historical tutorial snapshots

These archives preserve the material presented at a specific event. Prefer the current Learn and How-to pages above for maintained guidance.

• Winterbrain 2025 — Talk 1.
• Winterbrain 2025 — Talk 2.
• PyMC to HSSM — MathPsych 2025.