针对新寿命分布的过程能力指数 $$S_{pmk}$$ 的推论

IF 3.1 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Kadir Karakaya
{"title":"针对新寿命分布的过程能力指数 $$S_{pmk}$$ 的推论","authors":"Kadir Karakaya","doi":"10.1007/s00500-024-09892-9","DOIUrl":null,"url":null,"abstract":"<p>In various applied disciplines, the modeling of continuous data often requires the use of flexible continuous distributions. Meeting this demand calls for the introduction of new continuous distributions that possess desirable characteristics. This paper introduces a new continuous distribution. Several estimators for estimating the unknown parameters of the new distribution are discussed and their efficiency is assessed through Monte Carlo simulations. Furthermore, the process capability index <span>\\(S_{pmk}\\)</span> is examined when the underlying distribution is the proposed distribution. The maximum likelihood estimation of the <span>\\(S_{pmk}\\)</span> is also studied. The asymptotic confidence interval is also constructed for <span>\\(S_{pmk}\\)</span>. The simulation results indicate that estimators for both the unknown parameters of the new distribution and the <span>\\(S_{pmk}\\)</span> provide reasonable results. Some practical analyses are also performed on both the new distribution and the <span>\\(S_{pmk}\\)</span>. The results of the conducted data analysis indicate that the new distribution yields effective outcomes in modeling lifetime data in the literature. Similarly, the data analyses performed for <span>\\(S_{pmk}\\)</span> illustrate that the new distribution can be utilized for process capability indices by quality controllers.</p>","PeriodicalId":22039,"journal":{"name":"Soft Computing","volume":"821 1","pages":""},"PeriodicalIF":3.1000,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Inference on process capability index $$S_{pmk}$$ for a new lifetime distribution\",\"authors\":\"Kadir Karakaya\",\"doi\":\"10.1007/s00500-024-09892-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>In various applied disciplines, the modeling of continuous data often requires the use of flexible continuous distributions. Meeting this demand calls for the introduction of new continuous distributions that possess desirable characteristics. This paper introduces a new continuous distribution. Several estimators for estimating the unknown parameters of the new distribution are discussed and their efficiency is assessed through Monte Carlo simulations. Furthermore, the process capability index <span>\\\\(S_{pmk}\\\\)</span> is examined when the underlying distribution is the proposed distribution. The maximum likelihood estimation of the <span>\\\\(S_{pmk}\\\\)</span> is also studied. The asymptotic confidence interval is also constructed for <span>\\\\(S_{pmk}\\\\)</span>. The simulation results indicate that estimators for both the unknown parameters of the new distribution and the <span>\\\\(S_{pmk}\\\\)</span> provide reasonable results. Some practical analyses are also performed on both the new distribution and the <span>\\\\(S_{pmk}\\\\)</span>. The results of the conducted data analysis indicate that the new distribution yields effective outcomes in modeling lifetime data in the literature. Similarly, the data analyses performed for <span>\\\\(S_{pmk}\\\\)</span> illustrate that the new distribution can be utilized for process capability indices by quality controllers.</p>\",\"PeriodicalId\":22039,\"journal\":{\"name\":\"Soft Computing\",\"volume\":\"821 1\",\"pages\":\"\"},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2024-07-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Soft Computing\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1007/s00500-024-09892-9\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Soft Computing","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1007/s00500-024-09892-9","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0

摘要

在各种应用学科中,连续数据建模往往需要使用灵活的连续分布。要满足这一需求,就需要引入具有理想特性的新连续分布。本文介绍了一种新的连续分布。本文讨论了几种用于估计新分布未知参数的估计器,并通过蒙特卡罗模拟评估了它们的效率。此外,本文还考察了当基础分布是所提出的分布时的过程能力指数 \(S_{pmk}\)。还研究了 \(S_{pmk}\)的最大似然估计。还构建了 \(S_{pmk}\)的渐近置信区间。模拟结果表明,新分布的未知参数和 \(S_{pmk}\)的估计值都提供了合理的结果。我们还对新分布和 (S_{pmk}\)进行了一些实际分析。数据分析的结果表明,新分布在对文献中的寿命数据建模时产生了有效的结果。同样,对 \(S_{pmk}\)进行的数据分析也表明,质量控制人员可以将新分布用于过程能力指数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Inference on process capability index $$S_{pmk}$$ for a new lifetime distribution

Inference on process capability index $$S_{pmk}$$ for a new lifetime distribution

In various applied disciplines, the modeling of continuous data often requires the use of flexible continuous distributions. Meeting this demand calls for the introduction of new continuous distributions that possess desirable characteristics. This paper introduces a new continuous distribution. Several estimators for estimating the unknown parameters of the new distribution are discussed and their efficiency is assessed through Monte Carlo simulations. Furthermore, the process capability index \(S_{pmk}\) is examined when the underlying distribution is the proposed distribution. The maximum likelihood estimation of the \(S_{pmk}\) is also studied. The asymptotic confidence interval is also constructed for \(S_{pmk}\). The simulation results indicate that estimators for both the unknown parameters of the new distribution and the \(S_{pmk}\) provide reasonable results. Some practical analyses are also performed on both the new distribution and the \(S_{pmk}\). The results of the conducted data analysis indicate that the new distribution yields effective outcomes in modeling lifetime data in the literature. Similarly, the data analyses performed for \(S_{pmk}\) illustrate that the new distribution can be utilized for process capability indices by quality controllers.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Soft Computing
Soft Computing 工程技术-计算机:跨学科应用
CiteScore
8.10
自引率
9.80%
发文量
927
审稿时长
7.3 months
期刊介绍: Soft Computing is dedicated to system solutions based on soft computing techniques. It provides rapid dissemination of important results in soft computing technologies, a fusion of research in evolutionary algorithms and genetic programming, neural science and neural net systems, fuzzy set theory and fuzzy systems, and chaos theory and chaotic systems. Soft Computing encourages the integration of soft computing techniques and tools into both everyday and advanced applications. By linking the ideas and techniques of soft computing with other disciplines, the journal serves as a unifying platform that fosters comparisons, extensions, and new applications. As a result, the journal is an international forum for all scientists and engineers engaged in research and development in this fast growing field.
×
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