Expand description
Control limits for SPM monitoring statistics.
Provides upper control limits (UCL) for T-squared and SPE statistics:
- T-squared: chi-squared distribution quantile. For finite calibration
samples of size n, T² follows
(n·ncomp/(n−ncomp))·F(ncomp, n−ncomp)rather thanχ²(ncomp). The chi-squared limit is the large-sample (n → ∞) limit. - SPE: moment-matched chi-squared approximation (Box, 1954, Theorem 1,
pp. 292–295). The derivation matches the first two moments of the SPE
distribution to a scaled chi-squared:
E[a·χ²(b)] = a·b = mean,Var[a·χ²(b)] = 2a²·b = var, givinga = var/(2·mean),b = 2·mean²/var.
§Accuracy
The moment-matching approximation is exact when SPE follows a scaled
chi-squared distribution (holds under Gaussian scores). For non-Gaussian
data, the approximation error is O(κ₄) where κ₄ is the excess kurtosis
of the SPE distribution. Use spe_moment_match_diagnostic to assess
adequacy.
§References
- Box, G.E.P. (1954). Some theorems on quadratic forms applied in the study of analysis of variance problems, I. Annals of Mathematical Statistics, 25(2), 290–302. Theorem 1, pp. 292–295.
- Woodall, W.H. & Ncube, M.M. (1985). Multivariate CUSUM quality-control procedures. Technometrics, 27(3), 285–292. §2, pp. 286–288.
Structs§
- Control
Limit - A control limit for a monitoring statistic.
Functions§
- spe_
control_ limit - Compute the SPE control limit using moment-matched chi-squared approximation.
- spe_
moment_ match_ diagnostic - Diagnostic for the SPE moment-match chi-squared approximation.
- t2_
control_ limit - Compute the T-squared control limit based on the chi-squared distribution.