Cox回归模型在铁路安全性能分析中的应用

H. Schabe, J. Braband
{"title":"Cox回归模型在铁路安全性能分析中的应用","authors":"H. Schabe, J. Braband","doi":"10.3850/978-981-18-2016-8_009-cd","DOIUrl":null,"url":null,"abstract":"The assessment of in-service safety performance is an important task, not only in railways. For example it is important to identify deviations early, in particular possible deterioration of safety performance, so that corrective actions can be applied early. On the other hand the assessment should be fair and objective and rely on sound and proven statistical methods. A popular means for this task is trend analysis. This paper defines a model for trend analysis and compares different approaches, e. g. classical and Bayes approaches, on real data. The examples show that in particular for small sample sizes, e. g. when railway operators shall be assessed, the Bayesian prior may influence the results significantly.","PeriodicalId":187633,"journal":{"name":"Proceedings of the 31st European Safety and Reliability Conference (ESREL 2021)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Application of the Cox Regression Model for Analysis of Railway Safety Performance\",\"authors\":\"H. Schabe, J. Braband\",\"doi\":\"10.3850/978-981-18-2016-8_009-cd\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The assessment of in-service safety performance is an important task, not only in railways. For example it is important to identify deviations early, in particular possible deterioration of safety performance, so that corrective actions can be applied early. On the other hand the assessment should be fair and objective and rely on sound and proven statistical methods. A popular means for this task is trend analysis. This paper defines a model for trend analysis and compares different approaches, e. g. classical and Bayes approaches, on real data. The examples show that in particular for small sample sizes, e. g. when railway operators shall be assessed, the Bayesian prior may influence the results significantly.\",\"PeriodicalId\":187633,\"journal\":{\"name\":\"Proceedings of the 31st European Safety and Reliability Conference (ESREL 2021)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 31st European Safety and Reliability Conference (ESREL 2021)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3850/978-981-18-2016-8_009-cd\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 31st European Safety and Reliability Conference (ESREL 2021)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3850/978-981-18-2016-8_009-cd","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

在役安全绩效评价是一项重要的工作,不仅在铁路领域如此。例如,及早发现偏差,特别是安全性能可能恶化的情况,以便及早采取纠正措施是很重要的。另一方面,评估应是公平和客观的,并依靠可靠和可靠的统计方法。执行此任务的常用方法是趋势分析。本文定义了一个趋势分析模型,并在实际数据上比较了不同的方法,如经典方法和贝叶斯方法。这些例子表明,特别是对于小样本量,例如当评估铁路运营商时,贝叶斯先验可能会显著影响结果。
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
Application of the Cox Regression Model for Analysis of Railway Safety Performance
The assessment of in-service safety performance is an important task, not only in railways. For example it is important to identify deviations early, in particular possible deterioration of safety performance, so that corrective actions can be applied early. On the other hand the assessment should be fair and objective and rely on sound and proven statistical methods. A popular means for this task is trend analysis. This paper defines a model for trend analysis and compares different approaches, e. g. classical and Bayes approaches, on real data. The examples show that in particular for small sample sizes, e. g. when railway operators shall be assessed, the Bayesian prior may influence the results significantly.
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
自引率
0.00%
发文量
0
期刊最新文献
How to Use Prescriptive Maintenance to Construct Robust Master Production Schedules Robust Sensor Fault Detection for Linear Parameter-Varying Systems using Interval Observer Knowledge-Based Approach for System Level Electromagnetic Safety Analysis A State-of-the-Art Review on IC EMC Reliability Empirical Analysis of Ship Anchor Drag Incidents for Cable Burial Risk Assessments
×
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