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[2.2.0] - 2026-08-26
This section describes the
2.2.0source candidate. It becomes a published
GitHub Release only after the matchingv2.2.0tag workflow succeeds.
Added
- Added an opt-in incremental research path with strict long-form point-in-time
controls and hashed controls catalogs. - Added paired ridge models on identical rows and folds: M0 uses all declared
controls, while M2 adds every preregistered astronomy feature under the same
alpha grid and fit budget. - Added Newey-West HAC inference, circular moving-block bootstrap, and a full
M2-pipeline joint circular-shift placebo over the declared cyclic group. - Added conservative union-null max-p aggregation and Bonferroni family
adjustment, with explicit limits on what the local runner can certify. - Added validator-clean controls/hypothesis templates and a complete synthetic
end-to-end incremental demo generator.
Dependencies
- NumPy is now a direct, exact-pinned
research/alldependency because the
incremental contract directly relies on float64 arrays andnumpy.linalg.
Python-specific pins keep resolution explicit; the core install is unchanged.
Compatibility and evidence boundary
- With
incremental_modelabsent or exactly{ "enabled": false }, the legacy
univariate path and result schema remain1.0.0. - Enabled incremental hypotheses require hypothesis schema
2.0.0, both
controls inputs, and emit research result schema2.0.0. Core result schema
remains2.0.0; astronomy schema remains1.0.0. - A positive loss differential or adjusted threshold diagnostic does not change
the evidence label. This release never emitsCONFIRMATORY_PASSand does not
claim causality, a complete financial baseline, stable alpha, or live-trading
readiness.