ORD_33_103_R_Data: R notebook and data to replicate the results presented in Nitka and Weron (2023) Operations Research and Decisions 33(3), 105-118

Weronika Nitka and Rafał Weron

WORMS Software (WORking papers in Management Science Software) from Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology

Abstract: This R notebook can be used to replicate the results (including all figures and tables) presented in Nitka and Weron (2023, Operations Research and Decisions 33(3), 105-118, DOI 10.37190/ord230307). It contains implementations of naive and CRPS averaging methods for quantile probabilistic electricity price forecasts, as well as evaluation and visualization scripts. The main R Markdown notebook (ORD_Nitka_Weron_2023.Rmd) file includes all functions and scripts in executable code chunks. The preprocessed data file (NN_forecasts.RData) contains a list with a vector of the observed values of electricity prices, as well as probabilistic forecasts of Marcjasz et al. (2023, Energy Economics 125, 106843, DOI 10.1016/j.eneco.2023.106843) in the form of named matrices where each row contains 99 ordered quantile forecasts for one hourly data point from one model. The data can be read in base R language or in Python (e.g. using the rdata package). All library dependencies are described within the notebook. The notebook can be executed using R or opened with any text editor.

Language: R
Requires: R
Keywords: Electricity price forecasting; Day-ahead market; Distributional neural network; LASSO; Forecast averaging (search for similar items in EconPapers)
Date: 2023-12-13
References: Add references at CitEc
Citations:

Downloads: (external link)
https://worms.pwr.edu.pl/RePEc/ahh/wcodes/ORD_Nitka_Weron_2023.Rmd R notebook (Rmd) (text/plain)
https://worms.pwr.edu.pl/RePEc/ahh/wcodes/NN_forecasts.RData RData file (58 MB) (application/zip)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ahh:wcodes:wormsc2301

Access Statistics for this software item

More software in WORMS Software (WORking papers in Management Science Software) from Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology Contact information at EDIRC.
Bibliographic data for series maintained by Anna Kowalska-Pyzalska ().