Legacy SHT audit ledger#

This document records the baseline findings that must be resolved before an affected method can ship in pySHT. The executable baseline is SHT 0.1.9 at Git commit 4e29cda1257f86dd0237d37329af358b54d04f2b.

The legacy namespace contains 54 statistical tests and two dynamic adapters. The adapters are unnecessary in Python because ordinary callables can be passed directly. Implemented and independently validated slices are recorded separately in the Biswas–Ghosh, classical mean, and classical variance ledgers.

Legacy parity is not evidence of correctness. A method is release-ready only after its primary formula, calibration, numerical implementation, invariants, and null behavior have been independently checked.

Legacy method

Initial status

Confirmed concern

Required gate

cov2.2012LC

Red

Dimensionally inconsistent scale-dependent normalization

Re-derive from Li–Chen and prove common-scale invariance

cov1.2012Fisher

Red

Computation ignores the whitened data and supplied null covariance

Whitening-equivalence oracle

cov1.2015WL, cov2.2015WL

Red

Equality-facing API implements one directional tail

Re-derive all supported alternatives

mvar2.1930PN, mvar2.1982Muirhead

Red

Reversed p-value tails

Null calibration and power in both directions

eqdist.2014BG

Red

Legacy asymptotic variance changes under row permutation

Order-invariant derivation; corrected permutation implementation first

meank.2019CPH

Red

Stale loop index reuses the wrong group

Group-order and unequal-size tests

mean2.1958Dempster

Red

Raw positive ratio is incorrectly calibrated as standard normal

Primary-paper re-derivation

mvar2.2012ZXC

Red

Exact quadrature is unstable and underflows in stronger alternatives

Log-domain/high-precision oracle

norm.1996AJB, norm.2008RJB

Red

Documented default call fails

Default-call smoke tests

maximum pairwise BF kernels

Red

Double-to-float truncation and exponentiation overflow

Float64, log-domain implementation

Classical one- and two-sample t tests, scalar chi-square/F variance tests, one-way ANOVA, and Shapiro–Wilk matched trusted baseline implementations in the initial fixed-data probes. These procedures have now passed their pySHT validation gates and are available in their scientific category modules.