analysis op• データ種: design × signal → table
• 呼び出し: import fullseye as fs; fs.ledger.rsm_fit(design=None, y=None, model='quadratic') -> 'dict' (実装を直接呼ぶなら import multivar; multivar.rsm_fit(design=None, y=None, model='quadratic') -> 'dict'、台帳から引くなら opsmultivar.get("rsm_fit"))
design(符号化単位)に応答曲面を当てる: 分散分析・当てはまりの悪さ・停留点。
> 以下の詳細説明は原文のままです —— 要約と見出しは訳出済み。
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 ファミリ ガイド
• サンプルデータ カタログ(DL URL / ライセンス) — 2-D は skimage.data(BSD/public)+ 合成、3-D は実データ源(Stanford/PDS 等)の DL URL。
• 演算子の来歴・参考文献 — この op 族の元になった研究/手法の出典。
• アルゴリズムの正典(著者・年)と用途は上記ファミリ使い方ガイドに記載。
• multivar_inspection_tour — py -3.11 examples/multivar_inspection_tour.py
table を入力に取れる)—
analysis)mv_pca · mv_pls · doe_main_effects
*Provenance: multivar.py — MULTIVAR operator registry. この per-op ノートは tools/opdocs.py md が自動生成(手編集しない)。*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.