Salīdzināt metodes

	MCUSUM karte	Diagramma MEWMA
Nozare	Statistika	Statistika
Saime	Process / pipeline	Process / pipeline
Izcelsmes gads	1988	1992
Autors	Robert Crosier	Lowry, Woodall, Champ & Rigdon
Tips	Multivariate sequential monitoring chart	Multivariate sequential monitoring chart
Pirmavots	Crosier, R. B. (1988). Multivariate generalizations of cumulative sum quality-control schemes. Technometrics, 30(3), 291–303.	Lowry, C. A., Woodall, W. H., Champ, C. W., & Rigdon, S. E. (1992). A multivariate exponentially weighted moving average control chart. Technometrics, 34(1), 46–53.
Citi nosaukumi	Multivariate Cumulative Sum Chart, MCUSUM Control Chart, Crosier MCUSUM Scheme, Çok Değişkenli CUSUM Kontrol Grafiği	Multivariate Exponentially Weighted Moving Average Chart, MEWMA Control Chart, Vector EWMA Chart, Çok Değişkenli EWMA Kontrol Grafiği
Saistītās	2	2
Kopsavilkums	The Multivariate CUSUM (MCUSUM) Chart is a sequential monitoring scheme designed to detect small, persistent mean shifts in a process characterized by multiple correlated quality variables simultaneously. Introduced by Robert Crosier in 1988, it extends the classical univariate CUSUM principle to the multivariate setting by accumulating a vector-valued sum of deviations from the in-control mean, scaled by the process covariance structure, and comparing a scalar norm of that cumulative sum against a control limit.	The Multivariate EWMA (MEWMA) control chart is a statistical process monitoring method designed to detect small and sustained shifts in the mean vector of a multivariate process. Introduced by Lowry, Woodall, Champ, and Rigdon in 1992, it extends the univariate EWMA chart to p-dimensional observation vectors by computing an exponentially weighted moving average of successive measurement vectors and charting a Hotelling-type quadratic form against a control limit determined by a target average run length.