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docs(stat_run): record deterministic-core rationale (why not scipy/statsmodels) #4

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docs(stat_run): record deterministic-core rationale (why not scipy/statsmodels) #4

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8 changes: 8 additions & 0 deletions scripts/core/stat_run.py
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Original file line number Diff line number Diff line change
Expand Up @@ -187,6 +187,10 @@ def permutation_test(req):
(it is a stochastic estimate of the same exact p, hence corroborated_inference not
operational_fact).

Deliberately reimplemented, not a thin scipy wrapper: output must be byte-stable across
scipy versions and carry the envelope's provenance fields (exact/seed/n_combinations).
This is the deterministic core — do not "simplify" to scipy.stats.permutation_test.

Input: {op, groups:[a,b], alternative?: two-sided|less|greater, n_resamples?: int,
exact_max_perms?: int}
"""
Expand Down Expand Up @@ -264,6 +268,10 @@ def multiple_testing(req):
hypotheses survive alpha — is only as strong as the input p-values, so the claim is scoped
to "adjustment computed", NOT "these effects are real".

Deliberately reimplemented, not a statsmodels wrapper, for the same deterministic-core
reason: byte-stable adjusted p-values across library versions. Do not "simplify" to
statsmodels.stats.multitest.multipletests.

Input: {op, pvalues:[...], alpha?: float (default 0.05)}
"""
pvals = list(map(float, req["pvalues"]))
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