Varying slopes: multiple slopes per factor (V≥2) + full rank-drop contract (#60)#80
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…pivoted Cholesky (#60) Generalizes the within-level reparametrization to any slope count: one-pass multivariate Welford moments per level, pivoted Cholesky on the centered slope Gram (raw for slope-only terms) taking the largest-remaining-variance direction each step, and a whitening map whose transpose back-transforms coefficients — dropped directions come back as exact zeros with a data-independent layout. Completes the rank-drop contract: within-level collinear slopes drop exactly one direction (the pivot picks the survivor); a crate-internal relative rank tolerance (1e-10, per-column so it is scale-invariant) governs the threshold, with zero keeping near-degenerate directions. The multi-term gate stays (#61); only the V>=2 restriction lifts.
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Closes #60.
Generalizes the within-level reparametrization to any slope count on the sole factor: one-pass multivariate Welford moments per level, pivoted Gram–Schmidt on the centered slope Gram (raw for slope-only terms) taking the largest-remaining-variance direction each step, and a whitening map whose transpose back-transforms coefficients — dropped directions come back as exact zeros with a data-independent layout.