当前位置: X-MOL 学术Extremes › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Editorial: EVA 2019 data competition on spatio-temporal prediction of Red Sea surface temperature extremes
Extremes ( IF 1.3 ) Pub Date : 2020-01-16 , DOI: 10.1007/s10687-019-00369-9
Raphaël Huser

Large, non-stationary spatio-temporal data are ubiquitous in modern statistical applications, and the modeling of spatio-temporal extremes is crucial for assessing risks in environmental sciences among others. While the modeling of extremes is challenging in itself, the prediction of rare events at unobserved spatial locations and time points is even more difficult. In this Editorial, we describe the data competition that was organized for the 11th international conference on Extreme-Value Analysis (EVA 2019), for which several teams modeled and predicted Red Sea surface temperature extremes over space and time. After introducing the dataset and the goal of the competition, we disclose the final ranking of the teams, and we finally discuss some interesting outcomes and future challenges.



中文翻译:

社论:关于红海表面温度极端时空预测的EVA 2019数据竞赛

在现代统计应用中,普遍存在大量的非平稳时空数据,而时空极端的建模对于评估环境科学等方面的风险至关重要。尽管极端现象本身具有挑战性,但要预测在未观察到的空间位置和时间点发生的稀有事件就更加困难。在本社论中,我们描述了为第11届极值分析国际会议(EVA 2019)组织的数据竞赛,几支团队为此建模和预测了时空上的红海地表极端温度。在介绍了数据集和比赛目标之后,我们公开了团队的最终排名,最后讨论了一些有趣的结果和未来的挑战。

更新日期:2020-04-21
down
wechat
bug