论文标题
定期变化时间序列的群集功能的估计：滑动块估计器
Estimation of cluster functionals for regularly varying time series: sliding blocks estimators
论文作者
论文摘要
群集指数描述了固定时间序列的极端行为。我们认为它们的滑动块估计器。使用现代的多变量理论，定期改变时间序列，我们在很容易验证的大型模型的条件下获得了中心限制定理。特别是，我们表明，在阈值框架上的峰值中，滑动和分离块估计器具有相同的限制差异。
Cluster indices describe extremal behaviour of stationary time series. We consider their sliding blocks estimators. Using a modern theory of multivariate, regularly varying time series, we obtain central limit theorems under conditions that can be easily verified for a large class of models. In particular, we show that in the Peak over Threshold framework, sliding and disjoint blocks estimators have the same limiting variance.
