A comparative study for parameter estimation of the Weibull distribution in a small sample size: An application to spring fatigue failure data

IF 1.3 4区 工程技术 Q4 ENGINEERING, INDUSTRIAL
Xiaoyu Yang, Liyang Xie, Yifeng Yang, Bingfeng Zhao, Yuan Li
{"title":"A comparative study for parameter estimation of the Weibull distribution in a small sample size: An application to spring fatigue failure data","authors":"Xiaoyu Yang, Liyang Xie, Yifeng Yang, Bingfeng Zhao, Yuan Li","doi":"10.1080/08982112.2022.2158745","DOIUrl":null,"url":null,"abstract":"Abstract The Weibull distribution is the most widely applied model in reliability analysis. The main objective of this paper is to present a simple method called the minimum discrepancy method that is applicable to both complete and censored data for the parameter estimation of the Weibull distribution and a detailed comparison in a small sample size of thirteen methods in terms of several criteria by a simulation study. Additionally, parameter estimation methods are applied to the spring fatigue failure data. By extensive simulations and comparisons, the generalized least square 1, the weighted least square 1, the weighted Maximum likelihood estimation and the minimum discrepancy method are recommended for parameter estimation with small samples.","PeriodicalId":20846,"journal":{"name":"Quality Engineering","volume":null,"pages":null},"PeriodicalIF":1.3000,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Quality Engineering","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1080/08982112.2022.2158745","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
引用次数: 1

Abstract

Abstract The Weibull distribution is the most widely applied model in reliability analysis. The main objective of this paper is to present a simple method called the minimum discrepancy method that is applicable to both complete and censored data for the parameter estimation of the Weibull distribution and a detailed comparison in a small sample size of thirteen methods in terms of several criteria by a simulation study. Additionally, parameter estimation methods are applied to the spring fatigue failure data. By extensive simulations and comparisons, the generalized least square 1, the weighted least square 1, the weighted Maximum likelihood estimation and the minimum discrepancy method are recommended for parameter estimation with small samples.
小样本威布尔分布参数估计的比较研究——应用于弹簧疲劳失效数据
摘要威布尔分布是可靠性分析中应用最广泛的模型。本文的主要目的是提出一种称为最小差异法的简单方法,该方法适用于威布尔分布参数估计的完整数据和截尾数据,并通过模拟研究在13种方法的小样本量中根据几个标准进行详细比较。此外,将参数估计方法应用于弹簧疲劳失效数据。通过大量的仿真和比较,推荐了广义最小二乘法、加权最小二乘法、最大似然估计法和最小方差法用于小样本参数估计。
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
来源期刊
Quality Engineering
Quality Engineering ENGINEERING, INDUSTRIAL-STATISTICS & PROBABILITY
CiteScore
3.90
自引率
10.00%
发文量
52
审稿时长
>12 weeks
期刊介绍: Quality Engineering aims to promote a rich exchange among the quality engineering community by publishing papers that describe new engineering methods ready for immediate industrial application or examples of techniques uniquely employed. You are invited to submit manuscripts and application experiences that explore: Experimental engineering design and analysis Measurement system analysis in engineering Engineering process modelling Product and process optimization in engineering Quality control and process monitoring in engineering Engineering regression Reliability in engineering Response surface methodology in engineering Robust engineering parameter design Six Sigma method enhancement in engineering Statistical engineering Engineering test and evaluation techniques.
×
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