Analyzing fatal accidents in aviation using extreme value theory

• Activity Number: 493
• Type: Contributed
• Date/Time: Wednesday, August 3, 2016 : 8:30 AM to 10:20 AM
• Sponsor: Section on Risk Analysis
• 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

Abstract

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.