极端增量的前兆
Precursors of extreme increments
摘要：
我们调查的前兆和可预测性的极端增量的时间序列。我们所关注的事件是在连续的时间步长内的大增量。我们特别感兴趣的是了解预测的质量如何取决于选择前兆的策略、事件的大小和相关强度。我们研究了AR（1）过程中的极端增量的预测分析，并在风速记录和长期相关的ARMA数据的数值。我们通过接收器操作员特征（ROC曲线）评估预测的成功。此外，我们观察到的预测质量的增加，增加事件的大小和减少相关性在所有的例子。这两种效应都可以通过使用似然比作为平滑ROC曲线的汇总指标来理解。
英文摘要：
We investigate precursors and predictability of extreme increments in a time series. The events we are focusing on consist in large increments within successive time steps. We are especially interested in understanding how the quality of the predictions depends on the strategy to choose precursors, on the size of the event and on the correlation strength. We study the prediction of extreme increments analytically in an AR(1) process, and numerically in wind speed recordings and long-range correlated ARMA data. We evaluate the success of predictions via receiver operator characteristics (ROC-curves). Furthermore, we observe an increase of the quality of predictions with increasing event size and with decreasing correlation in all examples. Both effects can be understood by using the likelihood ratio as a summary index for smooth ROC-curves.
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