估计大型恐怖事件的历史和未来概率
Estimating the historical and future probabilities of large terrorist events
摘要：
在复杂的社会系统中，包括政治冲突、经济和社交网络，具有右偏分布的事件是普遍存在的，并且这些系统有时会产生非常大的事件。例如，9/11恐怖事件造成近3000人死亡，几乎是第二大事件的六倍。但是，考虑到现代恐怖主义的历史记录，这种巨大的生命损失在统计上是不可能的吗？由于经验分布上尾的大幅波动，准确估计这种事件的概率变得复杂。我们提出了一个通用的统计算法，使这样的估计，它结合了半参数模型的尾部行为和非参数引导。应用于全球恐怖事件数据库，我们估计自1968年以来观察到至少一个9/11规模或更大事件的全球历史概率为11- 35%。这些结果在经济发展的全球变化、国内与国际事件、所使用的武器类型以及截止到1998年的截断历史等条件下都是稳健的。然后，我们使用这个程序来对未来十年至少一个类似事件进行数据驱动的统计预测。
英文摘要：
Quantities with right-skewed distributions are ubiquitous in complex social systems, including political conflict, economics and social networks, and these systems sometimes produce extremely large events. For instance, the 9/11 terrorist events produced nearly 3000 fatalities, nearly six times more than the next largest event. But, was this enormous loss of life statistically unlikely given modern terrorism's historical record? Accurately estimating the probability of such an event is complicated by the large fluctuations in the empirical distribution's upper tail. We present a generic statistical algorithm for making such estimates, which combines semi-parametric models of tail behavior and a nonparametric bootstrap. Applied to a global database of terrorist events, we estimate the worldwide historical probability of observing at least one 9/11-sized or larger event since 1968 to be 11-35%. These results are robust to conditioning on global variations in economic development, domestic versus international events, the type of weapon used and a truncated history that stops at 1998. We then use this procedure to make a data-driven statistical forecast of at least one similar event over the next decade.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
