社论,特刊“稳健统计的进展”。

IF 0.7 Q3 STATISTICS & PROBABILITY Metron-International Journal of Statistics Pub Date : 2021-01-01 Epub Date: 2021-06-28 DOI:10.1007/s40300-021-00213-w
Marco Riani, Mia Hubert
{"title":"社论,特刊“稳健统计的进展”。","authors":"Marco Riani,&nbsp;Mia Hubert","doi":"10.1007/s40300-021-00213-w","DOIUrl":null,"url":null,"abstract":"<p><p>Starting with 2020 volume, the journal Metron has decided to celebrate the centenary since its foundation with three special issues. This volume is dedicated to robust statistics. A striking feature of most applied statistical analyses is the use of methods that are well known to be sensitive to outliers or to other departures from the postulated model. Robust statistical methods provide useful tools for reducing this sensitivity, through the detection of the outliers by first fitting the majority of the data and then by flagging deviant data points. The six papers in this issue cover a wide orientation in all fields of robustness. This editorial first provides some facts about the history and current state of robust statistics and then summarizes the contents of each paper.</p>","PeriodicalId":51716,"journal":{"name":"Metron-International Journal of Statistics","volume":"79 2","pages":"121-125"},"PeriodicalIF":0.7000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s40300-021-00213-w","citationCount":"1","resultStr":"{\"title\":\"Editorial, special issue on \\\"Advances in Robust Statistics\\\".\",\"authors\":\"Marco Riani,&nbsp;Mia Hubert\",\"doi\":\"10.1007/s40300-021-00213-w\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Starting with 2020 volume, the journal Metron has decided to celebrate the centenary since its foundation with three special issues. This volume is dedicated to robust statistics. A striking feature of most applied statistical analyses is the use of methods that are well known to be sensitive to outliers or to other departures from the postulated model. Robust statistical methods provide useful tools for reducing this sensitivity, through the detection of the outliers by first fitting the majority of the data and then by flagging deviant data points. The six papers in this issue cover a wide orientation in all fields of robustness. This editorial first provides some facts about the history and current state of robust statistics and then summarizes the contents of each paper.</p>\",\"PeriodicalId\":51716,\"journal\":{\"name\":\"Metron-International Journal of Statistics\",\"volume\":\"79 2\",\"pages\":\"121-125\"},\"PeriodicalIF\":0.7000,\"publicationDate\":\"2021-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1007/s40300-021-00213-w\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Metron-International Journal of Statistics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/s40300-021-00213-w\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2021/6/28 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q3\",\"JCRName\":\"STATISTICS & PROBABILITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Metron-International Journal of Statistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s40300-021-00213-w","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2021/6/28 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
引用次数: 1

摘要

从2020年开始,《地铁》杂志决定发行3期特刊,庆祝创刊100周年。本卷专门介绍稳健的统计数据。大多数应用的统计分析的一个显著特征是使用众所周知的对异常值或与假设模型的其他偏离敏感的方法。稳健的统计方法为降低这种敏感性提供了有用的工具,通过首先拟合大部分数据,然后通过标记异常数据点来检测异常值。本期的六篇论文涵盖了鲁棒性的所有领域。这篇社论首先提供了一些关于稳健统计的历史和现状的事实,然后总结了每篇论文的内容。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Editorial, special issue on "Advances in Robust Statistics".

Starting with 2020 volume, the journal Metron has decided to celebrate the centenary since its foundation with three special issues. This volume is dedicated to robust statistics. A striking feature of most applied statistical analyses is the use of methods that are well known to be sensitive to outliers or to other departures from the postulated model. Robust statistical methods provide useful tools for reducing this sensitivity, through the detection of the outliers by first fitting the majority of the data and then by flagging deviant data points. The six papers in this issue cover a wide orientation in all fields of robustness. This editorial first provides some facts about the history and current state of robust statistics and then summarizes the contents of each paper.

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
Metron-International Journal of Statistics
Metron-International Journal of Statistics STATISTICS & PROBABILITY-
CiteScore
1.60
自引率
0.00%
发文量
11
期刊介绍: METRON welcomes original articles on statistical methodology, statistical applications, or discussions of results achieved by statistical methods in different branches of science.
期刊最新文献
Imposing unsupervised constraints to the Benefit-of-the-Doubt (BoD) model Generalized regression estimators with concave penalties and a comparison to lasso type estimators Dynamic modelling of price expectations and judgments How the sampling variances affect the linear predictor of the Fay-Herriot model Evaluating the spatial heterogeneity of innovation drivers: a comparison between GWR and GWPR
×
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