A distribution‐free control chart for monitoring high‐dimensional processes based on interpoint distances

Lianjie Shu and Jinyu Fan

Naval Research Logistics (NRL), 2018, vol. 65, issue 4, 317-330

Abstract: With rapid advances in sensing technology and data acquisition systems, high‐dimensional data appear in many settings. The high dimensionality presents a new challenge to the traditional tools in multivariate statistical process control, due to the “curse of dimensionality.” Various tests for mean vectors in high dimensional situations have been discussed recently; however, they have been rarely adapted to process monitoring. This paper develops a distribution‐free control chart based on interpoint distances for monitoring mean vectors in high‐dimensional settings. Other than the Euclidean distance, the family of Minkowski distance is used for discussion, which is a generalization of the former and other distances. The proposed approach is very general as it represents a class of distribution‐free control charts based on distances. Numerical results show that the proposed control chart is efficient in detecting mean shifts in both symmetric and heavy‐tailed distributions.

Date: 2018
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https://doi.org/10.1002/nav.21809

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Persistent link: https://EconPapers.repec.org/RePEc:wly:navres:v:65:y:2018:i:4:p:317-330

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