| Day-ahead vs. Intraday—Forecasting the price spread to maximize economic benefits K Maciejowska, W Nitka, T Weron Energies 12 (4), 631, 2019 | 102 | 2019 |
| Enhancing load, wind and solar generation for day-ahead forecasting of electricity prices K Maciejowska, W Nitka, T Weron Energy Economics 99, 105273, 2021 | 45 | 2021 |
| Balancing generation from renewable energy sources: Profitability of an energy trader C Kath, W Nitka, T Serafin, T Weron, P Zaleski, R Weron Energies 13 (1), 205, 2020 | 30 | 2020 |
| Impact of solar activity on precipitation in the United States W Nitka, K Burnecki Physica A: Statistical Mechanics and its Applications 527, 121387, 2019 | 10 | 2019 |
| Prediction performance of Hidden Markov modelling for solar flares A Stanislavsky, W Nitka, M Małek, K Burnecki, J Janczura Journal of Atmospheric and Solar-Terrestrial Physics 208, 105407, 2020 | 8 | 2020 |
| Forecasting electricity prices: Autoregressive hybrid nearest neighbors (ARHNN) method W Nitka, T Serafin, D Sotiros International Conference on Computational Science, 312-325, 2021 | 7 | 2021 |
| Combining predictive distributions of electricity prices: Does minimizing the CRPS lead to optimal decisions in day-ahead bidding? W Nitka, R Weron arXiv preprint arXiv:2308.15443, 2023 | 4 | 2023 |
| Calibration window selection based on change-point detection for forecasting electricity prices J Nasiadka, W Nitka, R Weron International Conference on Computational Science, 278-284, 2022 | 4 | 2022 |
| 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 W Nitka, R Weron WORMS Software (WORking papers in Management Science Software), 2023 | | 2023 |
| Balancing RES generation: Profitability of an energy trader C Kath, W Nitka, T Serafin, T Weron, P law Zaleski, R l Weron HSC Research Reports, 2019 | | 2019 |
