A General Multivariate Exponentially Weighted Moving-Average Control Chart

75 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Profile Monitoring with Binary Data and Random Predictors (2011, methodology): “This property is consistent with that of the classical EWMA schemes in the literatures (Lucas and Saccucci 1990; Lowry et al. 1992).”
The computation of average run length and average time to signal: an overview (2014, background): “Runger and Prabhu [71] extended the advantages of the Markov chain approximation to multivariate EWMA [81] and showed that this analysis can be applied whenever the multivariate control statistic can be modelled as a Markov chain and the run length performance depends on the off-target mean only thr”
Directional MEWMA Schemes for Multistage Process Monitoring and Diagnosis (2008, methodology): “Note that, as shown by Lowry et al. (1992), the off-target performance of the MEWMA chart can be determined by assuming, without loss of generality, that the off-target mean vector is δ1l, where l is the unit vector along the first coordinate axis. For the multistage process model, δ1 = δ(hζΣ −1hζ)1”