A Bayesian control chart for a common coefficient of variation |
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Authors: | R van Zyl A J van der Merwe |
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Institution: | 1. Department of Biostatistics, Quintiles International, Bloemfontein, South Africa;2. Department of Actuarial Sciences and Mathematical Statistics, University of the Free State, Bloemfontein, South Africa |
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Abstract: | By using the medical data analyzed by Kang et al. (2007 Kang, C.W., Lee, M.S., Seong, Y.J., Hawkins, D.M. (2007). A control chart for the coefficient of variation. J. Qual. Technol. 39(2):151–158.Taylor &; Francis Online], Web of Science ®] , Google Scholar]), a Bayesian procedure is applied to obtain control limits for the coefficient of variation. Reference and probability matching priors are derived for a common coefficient of variation across the range of sample values. By simulating the posterior predictive density function of a future coefficient of variation, it is shown that the control limits are effectively identical to those obtained by Kang et al. (2007 Kang, C.W., Lee, M.S., Seong, Y.J., Hawkins, D.M. (2007). A control chart for the coefficient of variation. J. Qual. Technol. 39(2):151–158.Taylor &; Francis Online], Web of Science ®] , Google Scholar]) for the specific dataset they used. This article illustrates the flexibility and unique features of the Bayesian simulation method for obtaining posterior distributions, predictive intervals, and run-lengths in the case of the coefficient of variation. A simulation study shows that the 95% Bayesian confidence intervals for the coefficient of variation have the correct frequentist coverage. |
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Keywords: | Coefficient of variation control charts probability-matching prior reference prior |
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