This repo contains the source code for EVA 2023 Data Challenge.
For the detail, please refer to our paper: https://link.springer.com/article/10.1007/s10687-024-00497-x.
- Team Name: SHSmultiscale
- Final Ranking: 2nd place in the challenge
EVA 2023 Data Challenge consists of 4 sub-challenges, each of which deals with the problem of
- (C1) conditional extremal quantile prediction
- (C2) marginal extremal quantile prediction
- (C3) 3-dim joint probability prediction of exceedance events
- (C4) 50-dim joint probability prediction of exceedance events
To access more detailed information about the challenge, please refer to the "instructions" folder.
Kang, S., Kim, K., Kwon, Y., Park, S., Park, S., Shin, H.-Y., Kim, J. and Oh, H.-S. (2024+). Semiparametric approaches for the inference of univariate and multivariate extremes. Extremes.