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題名 Bayesian Variables Acceptance Sampling Plans: Quadratic Loss Function and Step Loss Function
作者 唐揆
Moskowitz, H.;Tang, Kwei
貢獻者 企管系
關鍵詞 Bayes rule, Prior distribution, Quality costs
日期 1992
上傳時間 24-Aug-2016 17:23:49 (UTC+8)
摘要 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.
關聯 Technometrics, 34(3), 340-347
資料類型 article
DOI http://dx.doi.org/10.1080/00401706.1992.10485283
dc.contributor 企管系
dc.creator (作者) 唐揆zh_TW
dc.creator (作者) Moskowitz, H.;Tang, Kwei
dc.date (日期) 1992
dc.date.accessioned 24-Aug-2016 17:23:49 (UTC+8)-
dc.date.available 24-Aug-2016 17:23:49 (UTC+8)-
dc.date.issued (上傳時間) 24-Aug-2016 17:23:49 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/100719-
dc.description.abstract (摘要) 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.
dc.format.extent 129 bytes-
dc.format.mimetype text/html-
dc.relation (關聯) Technometrics, 34(3), 340-347
dc.subject (關鍵詞) Bayes rule, Prior distribution, Quality costs
dc.title (題名) Bayesian Variables Acceptance Sampling Plans: Quadratic Loss Function and Step Loss Function
dc.type (資料類型) article
dc.identifier.doi (DOI) 10.1080/00401706.1992.10485283
dc.doi.uri (DOI) http://dx.doi.org/10.1080/00401706.1992.10485283