A predictive model of terrorist activity is developed by examining the daily
number of terrorist attacks in Indonesia from 1994 through 2007. The dynamic
model employs a shot noise process to explain the self-exciting nature of the
terrorist activities. This estimates the probability of future attacks as a
function of the times since the past attacks. In addition, the excess of
nonattack days coupled with the presence of multiple coordinated attacks on the
same day compelled the use of hurdle models to jointly model the probability of
an attack day and corresponding number of attacks. A power law distribution
with a shot noise driven parameter best modeled the number of attacks on an
attack day. Interpretation of the model parameters is discussed and predictive
performance of the models is evaluated.

通过研究 1994 年至 2007 年印度尼西亚的恐怖袭击次数，建立出具有自激性质的恐怖活动预测模型，使用 shot noise 过程估计未来袭击的概率，并采用障碍模型来共同建模攻击日的概率和相应的攻击次数，发现由于没有攻击日次数的过多而出现的非攻击日数的剩余，并发动协调攻击的存在，所以最合适的数学模型为具有 shot noise 驱动参数的幂律分布。讨论了模型参数的解释，并评估了这些模型的预测性能。