Salīdzināt metodes

	Diagramma MEWMA	EWMA kontroles karte
Nozare	Statistika	Statistika
Saime	Process / pipeline	Process / pipeline
Izcelsmes gads	1992	1959
Autors	Lowry, Woodall, Champ & Rigdon	S. W. Roberts
Tips	Multivariate sequential monitoring chart	Statistical process control chart for small shifts
Pirmavots	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.	Roberts, S. W. (1959). Control chart tests based on geometric moving averages. Technometrics, 1(3), 239–250.
Citi nosaukumi	Multivariate Exponentially Weighted Moving Average Chart, MEWMA Control Chart, Vector EWMA Chart, Çok Değişkenli EWMA Kontrol Grafiği	exponentially weighted moving average chart, EWMA control chart, geometric moving average chart, EWMA kontrol kartı
Saistītās	2	3
Kopsavilkums	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.	The exponentially weighted moving average (EWMA) control chart, introduced by S. W. Roberts in 1959, monitors a process using a weighted average that gives the most recent observation the greatest weight while letting older observations fade geometrically. Like CUSUM, this memory makes it highly effective at detecting small, sustained shifts in the process mean, with a single smoothing parameter λ controlling how much past information the chart retains.