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Activity Number: 354
Type: Contributed
Date/Time: Tuesday, August 6, 2013 : 10:30 AM to 12:20 PM
Sponsor: Quality and Productivity Section
Abstract - #307858
Title: Multivariate JS-Type Control Charts
Author(s): Hsiuying Wang*+
Companies: National Chiao Tung University
Keywords: control chart ; James-Stein estimators ; monitoring
Abstract:

In this study, we focus on improving parameter estimation in Phase I study to construct more accurate Phase II control limits for monitoring multivariate quality characteristics. For a multivariate normal distribution with unknown mean, the usual mean estimator is known to be inadmissible under the squared error loss when the dimension of the variable is greater than 2. Shrinkage estimators, such as the James-Stein estimators, are shown to have better performance than the conventional estimators in the literature. We utilize the James-Stein estimators to improve the Phase I parameter estimation. Multivariate control limits for the Phase II monitoring based on the improved estimators are proposed. The resulting control charts, JS-type charts, are shown to have substantial improvement than the existing ones.


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