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政大典藏 > College of Commerce > Department of Business Administation > Periodical Articles > Item 140.119/100719

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/100719

Title:	Bayesian Variables Acceptance Sampling Plans: Quadratic Loss Function and Step Loss Function
Authors:	唐揆 Moskowitz, H.;Tang, Kwei
Contributors:	企管系
Keywords:	Bayes rule, Prior distribution, Quality costs
Date:	1992
Issue Date:	2016-08-24 17:23:49 (UTC+8)
Abstract:	In developing quality-control procedures, a step-loss function has been used implicitly or explicitly to describe consumer perceptions about product quality. A quadratic loss function has been suggested by Taguchi as an alternative to the step-loss function in measuring the loss due to imperfect product quality (cost of acceptance). In this article, Bayesian analyses of the known-standard-deviation acceptance-sampling problem are described for both the step and quadratic loss functions with three cost components—cost of inspection, cost of acceptance, and cost of rejection. A normal prior distribution is used for the lot mean. Efficient procedures for finding minimum expected cost procedures are given. For a particular example, comparisons are made of how optimal sampling plans and costs computed under the two cost structures change as the form of the prior distribution and misspecification of its mean and variance are varied. Sensitivity analyses for both cost functions show that the optimal sampling plan is robust with respect to the form of the prior distribution, as well as to misspecification of its mean and variance, if the tail specification reasonably approximates that of a normal distribution.
Relation:	Technometrics, 34(3), 340-347
Data Type:	article
DOI link:	http://dx.doi.org/10.1080/00401706.1992.10485283
DOI:	10.1080/00401706.1992.10485283
Appears in Collections:	[Department of Business Administation] Periodical Articles

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