Inference for the two-parameter exponential distribution with generalized order statistics

IF 1.4 3区 社会学 Q3 DEMOGRAPHY Mathematical Population Studies Pub Date : 2019-10-30 DOI:10.1080/08898480.2019.1681187
M. E. El-Adll
{"title":"Inference for the two-parameter exponential distribution with generalized order statistics","authors":"M. E. El-Adll","doi":"10.1080/08898480.2019.1681187","DOIUrl":null,"url":null,"abstract":"ABSTRACT Inferences about estimation and prediction of the two-parameter exponential distribution are based on generalized order statistics. Point and interval estimates are used for scale and location parameters. Unbiased point predictors and reconstructors are based upon pivotal quantities. The mean square error and Pitman’s measure help assess the closeness of estimators and predictors. Point estimators of scale and location parameters and point predictors of future observations are computed in the application of durations until remission of 20 leukemia patients and in the application until failure of air-conditioning systems.","PeriodicalId":49859,"journal":{"name":"Mathematical Population Studies","volume":null,"pages":null},"PeriodicalIF":1.4000,"publicationDate":"2019-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/08898480.2019.1681187","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mathematical Population Studies","FirstCategoryId":"90","ListUrlMain":"https://doi.org/10.1080/08898480.2019.1681187","RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"DEMOGRAPHY","Score":null,"Total":0}
引用次数: 10

Abstract

ABSTRACT Inferences about estimation and prediction of the two-parameter exponential distribution are based on generalized order statistics. Point and interval estimates are used for scale and location parameters. Unbiased point predictors and reconstructors are based upon pivotal quantities. The mean square error and Pitman’s measure help assess the closeness of estimators and predictors. Point estimators of scale and location parameters and point predictors of future observations are computed in the application of durations until remission of 20 leukemia patients and in the application until failure of air-conditioning systems.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
用广义阶统计量推断双参数指数分布
摘要基于广义阶统计量,推导了双参数指数分布的估计和预测。尺度和位置参数使用点和区间估计。无偏点预测器和重构器基于关键量。均方误差和皮特曼的测量方法有助于评估估计器和预测器的接近程度。尺度和位置参数的点估计量以及未来观察的点预测量在20例白血病患者缓解前的应用时间和在空调系统失效前的应用时间中进行计算。
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 去求助
来源期刊
Mathematical Population Studies
Mathematical Population Studies 数学-数学跨学科应用
CiteScore
3.20
自引率
11.10%
发文量
7
审稿时长
>12 weeks
期刊介绍: Mathematical Population Studies publishes carefully selected research papers in the mathematical and statistical study of populations. The journal is strongly interdisciplinary and invites contributions by mathematicians, demographers, (bio)statisticians, sociologists, economists, biologists, epidemiologists, actuaries, geographers, and others who are interested in the mathematical formulation of population-related questions. The scope covers both theoretical and empirical work. Manuscripts should be sent to Manuscript central for review. The editor-in-chief has final say on the suitability for publication.
期刊最新文献
Researching algorithm awareness: methodological approaches to investigate how people perceive, know, and interact with algorithms Detection of outliers in survey–weighted linear regression Fractional Lindley distribution generated by time scale theory, with application to discrete-time lifetime data Estimating the structure by age and sex of the US sexually active population Optimizing criterion for the upper limit of the signal response of brain neurons
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1