乐胖代购免代理版

{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,8]],"date-time":"2024-08-08T02:52:35Z","timestamp":1723085555023},"reference-count":30,"publisher":"Wiley","issue":"3","license":[{"start":{"date-parts":[[2015,6,29]],"date-time":"2015-06-29T00:00:00Z","timestamp":1435536000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"name":"Universiti Sains Malaysia Research University","award":["1001\/PMATHS\/811263"]},{"name":"Fundamental Research Grant Scheme","award":["FRGS\/2\/2014\/SG04\/UTAR\/02\/1"]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Quality & Reliability Eng"],"published-print":{"date-parts":[[2016,4]]},"abstract":"Existing charts in the literature usually monitor either the mean or the variance of the process. However, in certain scenarios, the practitioner is not interested in the changes in the mean or the variance but is instead interested in monitoring the relative variability compared with the mean. This relative variability is called the coefficient of variation (CV). In the existing literature, none of the control charts that monitor the CV are applied for multivariate data. To fill this gap in research, this paper proposes a CV chart that monitors the CV for multivariate data. To the best of the authors' knowledge, this proposed chart is the first control chart for this purpose. The distributional properties of the sample CV for multivariate data and the procedures to implement the chart are presented in this paper. Formulae to compute the control limits, the average run length, the standard deviation of the run length, and the expected average run length for the case of unknown shift size are derived. From the numerical examples provided, the effects of the number of variables, the sample size, the shift size and the in\u2010control value of the CV are studied. Finally, we demonstrate the usefulness and applicability of the proposed chart on real data. 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