analysis op• 데이터 종류: design × signal → table
• 호출: import fullseye as fs; fs.ledger.rsm_fit(design=None, y=None, model='quadratic') -> 'dict'(구현을 직접 호출하려면 import multivar; multivar.rsm_fit(design=None, y=None, model='quadratic') -> 'dict', 원장에서 가져오려면 opsmultivar.get("rsm_fit"))
design(부호화 단위)에 반응표면을 적합: 분산분석, 적합결여, 정상점.
> 아래 상세 설명은 원문입니다 —— 요약과 제목은 번역되어 있습니다.
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 패밀리 가이드
• 샘플 데이터 카탈로그(DL URL / 라이선스) —— 2-D 는 skimage.data(BSD/public)+ 합성, 3-D 는 실데이터 소스(Stanford/PDS 등)의 DL URL.
• 연산자의 내력·참고문헌 —— 이 연산자 족의 바탕이 된 연구/기법의 출처.
• 알고리즘의 정전(저자·연도)과 용도는 위의 패밀리 사용 가이드에 적혀 있습니다.
• multivar_inspection_tour — py -3.11 examples/multivar_inspection_tour.py
table 를 입력으로 받는 것)—
analysis)mv_pca · mv_pls · doe_main_effects
*Provenance: multivar.py — MULTIVAR 연산자 레지스트리. 이 op 노트는 tools/opdocs.py md 가 자동 생성합니다(직접 편집하지 마세요).*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.