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Activity Number: 493
Type: Contributed
Date/Time: Wednesday, August 3, 2016 : 8:30 AM to 10:20 AM
Sponsor: Section on Risk Analysis
Abstract #321010
Title: Analyzing fatal accidents in aviation using extreme value theory
Author(s): Kumer Das* and Asim Dey
Companies: Lamar University and The University of Texas at Dallas
Keywords: Extreme value model ; Generalized Pareto distribution ; Return Level ; Bootstrap sampling ; Monte Carlo simulation

Even though air travel is considered a safe means of transportation, 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, 116 deaths. In this study we want to assess the risk of the catastrophic aviation accident 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 simulation.

Authors who are presenting talks have a * after their name.

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