analysis op• Data kinds: design × signal → table
• Call: import fullseye as fs; fs.ledger.rsm_fit(design=None, y=None, model='quadratic') -> 'dict' (implementation को सीधे call करना हो तो import multivar; multivar.rsm_fit(design=None, y=None, model='quadratic') -> 'dict', registry से लेना हो तो opsmultivar.get("rsm_fit"))
design (coded units) पर response surface fit: ANOVA, lack of fit, stationary point।
> नीचे का विस्तृत विवरण मूल text में है — सारांश और headings का अनुवाद हो चुका है।
model: "linear" (b0 + sum b_i x_i), "interaction" (+ b_ij x_i x_j) or "quadratic" (+ b_ii x_i^2) — fitted by least squares on the coded matrix of the design (so coefficients are comparable across factors).
Refuses a model the plan cannot support: if the model matrix is rank-deficient (a two-level plan cannot see x^2 — every x_i^2 equals the intercept; a resolution III fraction cannot separate a main effect from a two-factor interaction) the op raises ValueError naming the aliased terms, instead of returning one of infinitely many least-squares solutions. It also needs more runs than terms (a residual to judge with).
Returns coefficients with standard errors and t, the ANOVA (model / residual and, when the plan has replicated points, lack of fit vs pure error with its F test), R^2, adjusted R^2, predicted R^2 (from PRESS). For the quadratic model, the stationary point x_s = -B^{-1} b / 2 (B symmetric with b_ii on the diagonal and b_ij/2 off it) in coded and natural units, the predicted response there, the eigenvalues of B (canonical analysis: all negative = maximum, all positive = minimum, mixed = saddle, any near zero = ridge) and whether x_s lies inside the explored region.
• design_of_experiments family guide
• Sample data catalog (DL URL / license) — 2-D के लिए skimage.data (BSD/public) + synthetic, 3-D के लिए real data sources (Stanford/PDS आदि) के DL URL।
• Operators का स्रोत और संदर्भ — इस op family के मूल research/methods के स्रोत।
• Algorithm का मानक स्रोत (लेखक, वर्ष) और उपयोग ऊपर की family usage guide में दिए गए हैं।
• multivar_inspection_tour — py -3.11 examples/multivar_inspection_tour.py
table को input के रूप में लेते हैं)—
analysis)mv_pca · mv_pls · doe_main_effects
*Provenance: multivar.py — MULTIVAR operator registry. यह per-op note tools/opdocs.py md से अपने-आप generate होता है (हाथ से edit न करें)।*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.