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Monotonic change-point estimation of multivariate Poisson processes using a multi-attribute control chart and MLE
Niaki, S. T. A ; Sharif University of Technology
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- Type of Document: Article
- DOI: 10.1080/00207543.2013.857797
- Abstract:
- In this paper, a new multi-attribute T2 control chart is initially proposed to monitor multi-attribute processes based on a transformation technique. Then, the maximum likelihood estimator of a multivariate Poisson process change point is derived for unknown changes that are assumed to belong to a family of monotonic changes. Using extensive simulation experiments, the performance of the proposed change-point estimator is compared to the ones derived for step changes and linear-trend disturbances, when the true change types are step change, linear trends and multiple-step changes. We show when the type of the change is not known a priori, the proposed estimator is an appropriate choice, since it accurately estimates the true time of the process changes, regardless of change type, shift magnitudes and process dimension
- Keywords:
- Change-point estimation ; Multi-attribute processes ; Flowcharting ; Maximum likelihood estimation ; Change-points ; Maximum likelihood estimator ; Monotonic change ; Multi-attribute process ; Root transformation ; Estimation
- Source: International Journal of Production Research ; Vol. 52, issue. 10 , Nov , 2014 , pp. 2954-2982 ; ISSN: 00207543
- URL: http://www.tandfonline.com/doi/abs/10.1080/00207543.2013.857797