Quantifying the risk of extreme aviation accidents

被引：17

作者：

Das, Kumer Pial ^{[1
]}

Dey, Asim Kumer ^{[2
]}

机构：

[1] Lamar Univ, Beaumont, TX 77710 USA

[2] Univ Texas Dallas, Richardson, TX 75083 USA

来源：

PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS | 2016年 / 463卷

关键词：

Aviation accident; Extreme value model; Return level; Uncertainty; Bootstrap sampling; Monte Carlo simulation; GENERALIZED PARETO DISTRIBUTION; LARGE TERRORIST EVENTS; FUTURE PROBABILITIES; STATISTICS; PARAMETER;

D O I：

10.1016/j.physa.2016.07.023

中图分类号：

O4 [物理学];

学科分类号：

0702 ;

摘要：

Air travel is considered a safe means of transportation. But when aviation accidents do occur they often result in fatalities. Fortunately, the most extreme accidents occur rarely. However, 2014 was the deadliest year in the past decade causing 111 plane crashes, and among them worst four crashes cause 298, 239, 162 and 116 deaths. In this study, we want to assess the risk of the catastrophic aviation accidents by studying historical aviation accidents. Applying a generalized Pareto model we predict the maximum fatalities from an aviation accident in future. The fitted model is compared with some of its competitive models. The uncertainty in the inferences are quantified using simulated aviation accident series, generated by bootstrap resampling and Monte Carlo simulations. (C) 2016 Elsevier B.V. All rights reserved.

引用

页码：345 / 355

页数：11

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