Multivariate process control charts based on the Lp depth

被引：7

作者：

Pandolfo G. ^{[1
]}

Iorio C. ^{[1
]}

Staiano M. ^{[1
]}

Aria M. ^{[2
]}

Siciliano R. ^{[1
]}

机构：

[1] Department of Industrial Engineering, University of Naples Federico II, Naples

[2] Department of Economics and Statistics, University of Naples Federico II, Naples

来源：

Applied Stochastic Models in Business and Industry | 2021年 / 37卷 / 02期

关键词：

ARL; Mahalanobis depth; non-parametric statistics; Q charts;

D O I：

10.1002/asmb.2616

中图分类号：

学科分类号：

摘要：

Even if large historical dataset could be available for monitoring key quality features of a process via multivariate control charts, previous knowledge may not be enough to reliably identify or adopt a unique model for all the variables. When no specific parametric model turns out to be appropriate, some alternative solutions should be adopted and exploiting non-parametric methods to build a control chart appears a reasonable choice. Among the possible non-parametric statistical techniques, data depth functions are gaining a growing interest in multivariate quality control. Within the literature, several notions of depth are effective for this purpose, even in the case of deviation from the normality assumption. However, the use of the Lp depth for constructing non-parametric multivariate control charts has been surprisingly neglected so far. Hence, the goal of this work is to investigate the behavior the Lp depth in the statistical process control and to compare its performances to those of the Mahalanobis depth, which is often adopted to build depth-based control charts. © 2021 The Authors. Applied Stochastic Models in Business and Industry published by John Wiley & Sons Ltd.

引用

页码：229 / 250

页数：21

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