Exponentially weighted moving average charts for correlated multivariate Poisson processes
Sherzod Akhundjanov () and
Francis G. Pascual
Communications in Statistics - Theory and Methods, 2017, vol. 46, issue 10, 4977-5000
In this article, we study exponentially weighted moving average (EWMA) control schemes to monitor the multivariate Poisson distribution with a general covariance structure, so that the practitioner can simultaneously monitor multiple correlated attribute processes more effectively. The statistical performance of the charts is assessed in terms of the run length properties and compared against other mainstream attribute control schemes. The application of the proposed methods to real-life and simulated datasets is demonstrated.
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Persistent link: https://EconPapers.repec.org/RePEc:taf:lstaxx:v:46:y:2017:i:10:p:4977-5000
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