Process Capability Cp Assessment for Auto-Correlated Data in the Presence of Measurement Errors

Pub Date : 2022-11-16 DOI:10.1142/s0218539322500103
M. Z. Anis, Kuntal Bera
{"title":"Process Capability Cp Assessment for Auto-Correlated Data in the Presence of Measurement Errors","authors":"M. Z. Anis, Kuntal Bera","doi":"10.1142/s0218539322500103","DOIUrl":null,"url":null,"abstract":"In this paper, we shall discuss some statistical properties of the estimator of [Formula: see text] when sample observations are autocorrelated and affected by measurement errors. The presence of autocorrelation in production units is very common in many industries like chemical, food processing, pharmaceutical, paper, and mineral. At the same time some amount of measurement error is invariably present in the sample observations due to inaccurate measurement process. In this paper, we discuss the case of a first-order stationary autoregressive process where measurement error follows a Gaussian distribution. The comparison of the statistical properties of the estimator in this case with the error-free case is the subject matter of this paper.","PeriodicalId":0,"journal":{"name":"","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1142/s0218539322500103","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

In this paper, we shall discuss some statistical properties of the estimator of [Formula: see text] when sample observations are autocorrelated and affected by measurement errors. The presence of autocorrelation in production units is very common in many industries like chemical, food processing, pharmaceutical, paper, and mineral. At the same time some amount of measurement error is invariably present in the sample observations due to inaccurate measurement process. In this paper, we discuss the case of a first-order stationary autoregressive process where measurement error follows a Gaussian distribution. The comparison of the statistical properties of the estimator in this case with the error-free case is the subject matter of this paper.
分享
查看原文
存在测量误差的自相关数据过程能力Cp评价
本文讨论了样本观测值自相关且受测量误差影响时[公式:见文]估计量的一些统计性质。在化工、食品加工、制药、造纸和矿物等许多行业中,生产单位中存在自相关现象是非常普遍的。同时,由于测量过程不准确,在样品观测中总是存在一定的测量误差。本文讨论了测量误差服从高斯分布的一阶平稳自回归过程。在这种情况下与无误差情况下估计量的统计性质的比较是本文的主题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信