{"title":"共轭先验分布下过程平均的后验控制图","authors":"Sharada V. Bhat, Kailas D. Gokhale","doi":"10.1515/eqc-2014-0003","DOIUrl":null,"url":null,"abstract":"Abstract Control charts for the process average play an important role in process control. In the presence of prior information, using Bayesian approach, one can construct posterior control chart for process average (X̅ posterior control chart). The control limits of the proposed chart are derived under the assumption that the process average has a conjugate prior distribution. Both cases – variance is known and variance is unknown – are discussed. When the variance is unknown, the control limits are constructed using Unbiased Estimator (UE) and Maximum Likelihood Estimator (MLE) of the variance. The power and Average Run Length (ARL) of the proposed chart are obtained. The newly constructed X̅ posterior control chart is compared with a few other X̅ charts described in the literature.","PeriodicalId":360039,"journal":{"name":"Economic Quality Control","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Posterior Control Chart for Process Average under Conjugate Prior Distribution\",\"authors\":\"Sharada V. Bhat, Kailas D. Gokhale\",\"doi\":\"10.1515/eqc-2014-0003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract Control charts for the process average play an important role in process control. In the presence of prior information, using Bayesian approach, one can construct posterior control chart for process average (X̅ posterior control chart). The control limits of the proposed chart are derived under the assumption that the process average has a conjugate prior distribution. Both cases – variance is known and variance is unknown – are discussed. When the variance is unknown, the control limits are constructed using Unbiased Estimator (UE) and Maximum Likelihood Estimator (MLE) of the variance. The power and Average Run Length (ARL) of the proposed chart are obtained. The newly constructed X̅ posterior control chart is compared with a few other X̅ charts described in the literature.\",\"PeriodicalId\":360039,\"journal\":{\"name\":\"Economic Quality Control\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Economic Quality Control\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1515/eqc-2014-0003\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Economic Quality Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1515/eqc-2014-0003","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
摘要
摘要过程平均控制图在过程控制中起着重要的作用。在有先验信息的情况下,利用贝叶斯方法可以构造过程平均的后验控制图(X′s posterior control chart)。在过程平均具有共轭先验分布的假设下,推导了所提图表的控制极限。对方差已知和方差未知两种情况进行了讨论。当方差未知时,利用方差的无偏估计量(UE)和极大似然估计量(MLE)构造控制极限。得到了功率和平均运行长度(ARL)。将新构建的X′s后验控制图与文献中描述的其他几个X′s图进行比较。
Posterior Control Chart for Process Average under Conjugate Prior Distribution
Abstract Control charts for the process average play an important role in process control. In the presence of prior information, using Bayesian approach, one can construct posterior control chart for process average (X̅ posterior control chart). The control limits of the proposed chart are derived under the assumption that the process average has a conjugate prior distribution. Both cases – variance is known and variance is unknown – are discussed. When the variance is unknown, the control limits are constructed using Unbiased Estimator (UE) and Maximum Likelihood Estimator (MLE) of the variance. The power and Average Run Length (ARL) of the proposed chart are obtained. The newly constructed X̅ posterior control chart is compared with a few other X̅ charts described in the literature.