multivariate op• 資料種類:matrix → table
• 呼叫: import fullseye as fs; fs.ledger.spc_hotelling_t2(data, alpha=0.0027, mean=None, cov=None)(要直接呼叫實作,import spc; spc.spc_hotelling_t2(data, alpha=0.0027, mean=None, cov=None);從台帳取用則 opsspc.get("spc_hotelling_t2"))
> 該運算子的說明尚無譯文,以下照原文給出。
Multivariate SPC by Hotelling's T² with an F-distributed control limit.
`data is a 2-D array of shape (m, p) — m observations of p`
correlated features. With the sample mean vector `mu and covariance S`
(unless passed in explicitly), each row's statistic is::
T^2_i = (x_i - mu)' S^-1 (x_i - mu)
charted against the phase-II control limit::
UCL = p (m+1)(m-1) / (m (m-p)) * F_{alpha, p, m-p}
at false-alarm rate `alpha` (default 0.0027, the 3-sigma-equivalent). Returns
a dict with the per-row `t2 array, the ucl`, the integer indices
`out_of_control, and in_control. The mean row (x == mu`) has
`T^2 == 0` (pinned in the tests).
Raises `ValueError`: a non-2-D / empty *data*, fewer observations than
features plus one (covariance not invertible), `alpha outside (0, 1)`, a
singular covariance, or non-finite / mislabelled input.
• 範例資料目錄(下載 URL / 授權) —— 2-D 用 skimage.data(BSD/公有領域)加合成圖,3-D 給出真實資料源(Stanford/PDS 等)的下載 URL。
• 運算子來歷與參考文獻 —— 該運算子族所依據的研究/方法出處。
• 演算法的正典(作者・年份)與用途見上面的族使用指南。
• poc_spc — py -3.11 examples/poc_spc.py
table 作為輸入)—
multivariate)—
*Provenance: spc.py — SPC 運算子登記表。本條目由 tools/opdocs.py md 自動產生(請勿手動編輯)。*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.