Erratum to 'Forecasting day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark' [Appl. Energy 293 (2021) 116983]

Jesus Lago, Grzegorz Marcjasz, Bart De Schutter and Rafał Weron

No WORMS/21/12, WORking papers in Management Science (WORMS) from Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology

Abstract: This Erratum corrects the error metrics of the LEAR models for the German (EPEX DE) market reported in Tables 2 and 3 of Lago et al. (2021) Applied Energy 293, 116983.

Keywords: Electricity price forecasting; Regression model; Deep learning; Open-access benchmark; Forecast evaluation; Best practices (search for similar items in EconPapers)
JEL-codes: C22 C32 C45 C51 C53 Q41 Q47 (search for similar items in EconPapers)
Pages: 2 pages
Date: 2021-07-08
New Economics Papers: this item is included in nep-ene, nep-for and nep-ore
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Citations: View citations in EconPapers (25)

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https://worms.pwr.edu.pl/RePEc/ahh/wpaper/WORMS_21_12.pdf Original version, 2021 (application/pdf)

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