{"title":"An ARL-Unbiased Modified np-Chart for Autoregressive Binomial Counts","authors":"M. Morais, P. Wittenberg, Camila Jeppesen Cruz","doi":"10.1515/eqc-2022-0052","DOIUrl":null,"url":null,"abstract":"Abstract Independence between successive counts is not a sensible premise while dealing, for instance, with very high sampling rates. After assessing the impact of falsely assuming independent binomial counts in the performance of np-charts, such as the one with 3-σ control limits, we propose a modified np-chart for monitoring first-order autoregressive counts with binomial marginals. This simple chart has an in-control average run length (ARL) larger than any out-of-control ARL, i.e., it is ARL-unbiased. Moreover, the ARL-unbiased modified np-chart triggers a signal at sample t with probability one if the observed value of the control statistic is beyond the lower and upper control limits L and U. In addition to this, the chart emits a signal with probability γ L {\\gamma_{L}} (resp. γ U {\\gamma_{U}} ) if that observed value coincides with L (resp. U). This randomization allows us to set the control limits in such a way that the in-control ARL takes the desired value ARL 0 {\\operatorname{ARL}_{0}} , in contrast to traditional charts with discrete control statistics. Several illustrations of the ARL-unbiased modified np-chart are provided, using the statistical software R and resorting to real and simulated data.","PeriodicalId":37499,"journal":{"name":"Stochastics and Quality Control","volume":"52 1","pages":"11 - 24"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Stochastics and Quality Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1515/eqc-2022-0052","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Mathematics","Score":null,"Total":0}
引用次数: 0
Abstract
Abstract Independence between successive counts is not a sensible premise while dealing, for instance, with very high sampling rates. After assessing the impact of falsely assuming independent binomial counts in the performance of np-charts, such as the one with 3-σ control limits, we propose a modified np-chart for monitoring first-order autoregressive counts with binomial marginals. This simple chart has an in-control average run length (ARL) larger than any out-of-control ARL, i.e., it is ARL-unbiased. Moreover, the ARL-unbiased modified np-chart triggers a signal at sample t with probability one if the observed value of the control statistic is beyond the lower and upper control limits L and U. In addition to this, the chart emits a signal with probability γ L {\gamma_{L}} (resp. γ U {\gamma_{U}} ) if that observed value coincides with L (resp. U). This randomization allows us to set the control limits in such a way that the in-control ARL takes the desired value ARL 0 {\operatorname{ARL}_{0}} , in contrast to traditional charts with discrete control statistics. Several illustrations of the ARL-unbiased modified np-chart are provided, using the statistical software R and resorting to real and simulated data.
例如,在处理非常高的采样率时,连续计数之间的独立性不是一个明智的前提。在评估了错误假设独立二项计数对np图性能的影响后,例如具有3 σ控制极限的np图,我们提出了一种改进的np图,用于监测具有二项边缘的一阶自回归计数。这个简单的图表有一个可控的平均运行长度(ARL)大于任何失控的ARL,也就是说,它是ARL无偏的。此外,如果控制统计量的观测值超出控制下限L和上限u,则arl无偏修正np图在样本t处触发一个概率为1的信号,此外,图表发出一个概率为γ L {\gamma_{L}}的信号(resp。γ U {\gamma_{U}}),如果观测值与L (resp。这种随机化允许我们以这样一种方式设置控制限制,即控制中的ARL取期望值ARL 0 {\operatorname{ARL}_{0}},与具有离散控制统计的传统图表相反。利用统计软件R,结合真实数据和模拟数据,给出了arl无偏修正np图的几个例子。