bk_check_anova(). The comparison used
isTRUE(all.equal()), which reported a difference on
attribute mismatch even when the two totals were numerically identical;
it now compares attribute-stripped numeric values against a
tolerance.bk_check_variability() —
GCV/PCV/heritability/genetic-advance identities (h2 = (GCV/PCV)^2; GAM =
K * h2 * PCV; GAM = K * GCV^2 / PCV; GCV <= PCV).bk_check_anova() — df and SS additivity, MS = SS/df, F
= MS/MSe.bk_check_precision() — CV%, SEm, CD from MSe, and CD =
t * SEm * sqrt(2).bk_check_corr() — symmetry, unit diagonal, |r| <= 1,
and positive semi-definiteness with a rigorous Weyl rounding bound.bk_audit() combines module results;
print() and summary() methods.k = "auto" reconciles genetic advance against the
standard selection differential family (2.64, 2.06, 1.76, 1.40) and
reports which member fits.bk_example(), including two planted
errors that demonstrate error localisation.
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