New methods for modelling real-world extremes

该项目旨在开发新的理论和方法来分析和预测在真实世界过程中观察到的极值。许多现有技术受到方便的数学假设的限制，这些假设在实践中通常不成立：渐近水平的相关性、过程的平稳性，以及所观测的数据是感兴趣的过程的直接测量。因此，使用这些技术可能会产生不想要的结果。该项目的预期结果包括理论上合理的数据分析技术，这些技术可以准确地模拟现实世界中看到的极值。项目收益包括对国家在气候、森林火灾保险风险和异常检测方面的重要应用进行更现实的分析。

This project aims to develop new theory and methods for analysing and predicting extreme values observed in real-world processes. Many existing techniques are limited by convenient mathematical assumptions that commonly do not hold in practice: dependence at asymptotic levels, process stationarity, and that the observed data are direct measurements of the process of interest. As a result, using these techniques may produce undesirable results. Expected outcomes of this project include theoretically justified data analysis techniques that can accurately model extreme values seen in the real world. Project benefits include more realistic analyses of nationally important applications in climate, bushfire insurance risk, and anomaly detection.