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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

Abstract: 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.

Date: 2017
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DOI: 10.1080/03610926.2015.1096392

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