Skip to content

Changelog

This project follows semantic versioning where practical during alpha development. Alpha releases can still contain intentionally breaking API changes; pin exact versions.

0.2.0 — unreleased

Added

  • Directed Bayes-factor helpers, pairwise tables, posterior model probabilities, independent-evidence aggregation, and Savage–Dickey/history effect utilities.
  • Typed count/trajectory validation scenarios, recovery and coverage summaries, superiority/ROPE probabilities, and complete validation runners.
  • Cumulative-prefix count and trajectory Bayes-factor scans with schema validation and replicate summaries.
  • Donor-aware simulation, posterior extraction, variance decomposition, leave-one-donor-out mixture sensitivity, and independent-condition contrasts.
  • SMC/posterior/trajectory diagnostics.
  • Optional UI-neutral Matplotlib plotting.
  • Atomic inference persistence and checksummed scan bundles/archives.
  • MkDocs Material documentation and artifact-based GitHub Pages deployment.

Changed

  • README.md is the canonical package and PyPI introduction.
  • Package-scale validation ceilings replace inherited web-demo limits. These are broad safety bounds, not practical workload recommendations; frontends should impose tighter limits.
  • Package version advanced to 0.2.0.

Stability notes

  • Version 0.2 remains alpha.
  • Bayes-factor fields encode direction explicitly as numerator_vs_denominator.
  • Scan sample sizes are nested cumulative prefixes within each scenario/replicate.
  • Leave-one-donor-out moments recompute mixtures without refitting.

0.1.0

  • Initial standalone package with event-count, donor-aware, condition-wise, and ordered-trajectory simulation/inference, result tables, and archives.