Cluster-based artificial contrasts for inhomogeneously distributed data with an indicator variable

Wook-Yeon Hwang

International Journal of Production Research, 2016, vol. 54, issue 17, 5045-5055

Abstract: Multivariate statistical process control is used for simultaneously monitoring several process variables. The original artificial contrasts (AC) are very useful for monitoring inhomogeneously distributed data with an indicator variable. The cluster-based AC improve it by considering separated clusters, respectively. Then the artificial data used for the AC overlap each cluster. Numerical experiments show that our method outperforms existing methods in terms of Type-II error rate.

Date: 2016
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DOI: 10.1080/00207543.2015.1075667

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