This dataset contains the ESSD benchmark output data. Visit https://github.com/EUPP-benchmark/ESSD-benchmark for more information.

This dataset is provided as supplementary material with:

    ...: The EUPPBench postprocessing benchmark dataset v1.0, ...

Please cite this article if you use (a part of) this code for a publication.


Description of the methods used to get the ESSD benchmark output data
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 - ANET: NN post processing method using ensemble member encoders and dynamic attention
 	Repository: https://github.com/EUPP-benchmark/ESSD-ANET
 	
 - AR-EMOS: EMOS with heteroscedastic autoregressive error adjustments
 	Repository: https://github.com/EUPP-benchmark/ESSD-AR-EMOS
 	
 - ASRE: Accounting for systematic and representativeness errors
 	Repository: https://github.com/EUPP-benchmark/ESSD-ASRE
 	
 - DRN: Distributional regression network
 	Repository: https://github.com/EUPP-benchmark/ESSD-DRN
 	
 - DVQR: D-vine copula based postprocessing
 	Repository: https://github.com/EUPP-benchmark/ESSD-D-Vine-Copula
 	
 - EMOS: Ensemble model output statistics
 	Repository: https://github.com/EUPP-benchmark/ESSD-EMOS
 	
 - RC: Reliability Calibration
 	Repository: https://github.com/EUPP-benchmark/ESSD-reliability-calibration
 	
 - MBM: Member-By-Member postprocessing
 	Repository: https://github.com/EUPP-benchmark/ESSD-mbm