Abstract
In this paper various types of EWMA control charts are introduced for the simultaneous monitoring of the mean and the autocovariances. The target process is assumed to be a stationary process up to fourth-order or an ARMA process with heavy tailed innovations. The case of a Gaussian process is included in our results as well.
The charts are compared within a simulation study. As a measure of the performance the average run length is taken. The target process is an ARMA (1,1) process with Student-t distributed innovations. The behavior of the charts is analyzed with respect to several out-of-control models. The best design parameters are determined for each chart. Our comparisons show that the multivariate EWMA chart applied to the residuals has the best overall performance.
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Rosołowski, M., Schmid, W. EWNA charts for monitoring the mean and the autocovariances of stationary processes. Statistical Papers 47, 595–630 (2006). https://doi.org/10.1007/s00362-006-0308-9
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DOI: https://doi.org/10.1007/s00362-006-0308-9