Cox回归模型在铁路安全性能分析中的应用

H. Schabe, J. Braband
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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。
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.
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