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高维空间极值的空间尺度感知尾部依赖建模AI 解读

Extreme events over large spatial domains may exhibit highly heterogeneous tail dependence characteristics, yet most existing spatial extremes models yield only one dependence class over the entire spatial domain. To accurately characterize dependence in extreme events, we propose a mixture model that achieves flexible dependence properties and allows high-dimensional inference (∼600 spatial locations in our data example) for extremes of spatial processes. We modify the…

模型误设下的空间相依多重检验及极端气候归因应用AI 解读

The Weather Risk Attribution Forecast (WRAF) is a forecasting tool that uses output from global climate models to make simultaneous attribution statements about whether and how greenhouse gas emissions have contributed to extreme weather across the globe. However, in conducting a large number of simultaneous hypothesis tests, the WRAF is prone to identifying false “discoveries.” A common technique for addressing this multiple testing problem is to adjust the procedure in a…