A Markov chain model for the multivariate exponentially weighted moving averages control chart

被引：132

作者：

Runger, GC ^{[1
]}

Prabhu, SS ^{[1
]}

机构：

[1] SAS INST INC, STAT QUAL IMPROVEMENT R&D DEPT, CARY, NC 27513 USA

来源：

JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION | 1996年 / 91卷 / 436期

关键词：

average run length; exponentially weighted moving averages; multivariate control chart; statistical process control;

D O I：

10.2307/2291599

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

A Markov chain approximation is used to determine the run length performance of a multivariate statistical process control chart. The Markov chain approach is widely used in the analysis of univariate control charts, and we extend the advantages of this type of analysis to a multivariate exponentially weighted moving averages control chart. The analysis can be applied whenever the multivariate control statistic can be modeled as a Markov chain and the run length performance depends on the off-target mean only through the noncentrality parameter.

引用

页码：1701 / 1706

页数：6

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