Welcome to the official GitHub repository for the KAUST Extreme Statistics (extSTAT) Research Group's submission to the Extreme Value Analysis (EVA) 2023 Conference Data Challenge, held at Bocconi University in Milan, Italy. This repository contains all the R code, data analyses, and additional resources used by team "Yalla" to secure first place in this prestigious international competition.
The EVA 2023 Data Challenge presented participants with a series of complex problems centred around the analysis of environmental extreme data. Organised by esteemed academics from the University of Bath, University College London, and Lancaster University, the challenge involved four sub-challenges that required innovative statistical approaches to model extreme quantiles and estimate tail probabilities in various dimensional settings.
Our team, comprising a dynamic group of researchers and Ph.D. students from KAUST, excelled in the competition by developing new methodologies that effectively addressed each sub-challenges. We achieved a second-place finish in two of the four sub-challenges and clinched the best performance in the final sub-challenge, leading to our overall win.
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subchallenge-c1/: Contains all the R code used for sub-challenge c1 of the competition. Similar directories are available for each of the four sub-challenges.
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Data/: Includes the simulated datasets provided during the competition and any additional data generated by our analyses.
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Figures/: All figures presented in reference [1] below.
Researchers and students can explore the repository to understand our approaches to solving extreme value problems, replicate our analyses, or build upon our methodologies for related research. Please cite this repository and relevant papers in the Reference section below if you use the materials in your research or publication.
[1] Jordan Richards, Noura Alotaibi, Daniela Cisneros, Yan Gong, Matheus B. Guerrero, Paolo Redondo, and Xuanjie Shao. Modern extreme value statistics for Utopian extremes. (2024+). arxiv:2311.11054.