Võrdle meetodeid
Vaata valitud meetodeid kõrvuti; erinevad read on esile tõstetud.
| MEWMA diagramm× | EWMA Chart× | |
|---|---|---|
| Valdkond | Statistika | Statistika |
| Perekond | Process / pipeline | Process / pipeline |
| Tekkeaasta≠ | 1992 | 1959 |
| Looja≠ | Lowry, Woodall, Champ & Rigdon | S. W. Roberts |
| Tüüp≠ | Multivariate sequential monitoring chart | Statistical process control chart for small shifts |
| Algallikas≠ | 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. DOI ↗ | Roberts, S. W. (1959). Control chart tests based on geometric moving averages. Technometrics, 1(3), 239–250. DOI ↗ |
| Rööpnimetused | 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 |
| Seotud≠ | 2 | 3 |
| Kokkuvõte≠ | 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. |
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