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Online adaptive lasso estimation in vector autoregressive models for high dimensional wind power forecasting

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Cited by:

  1. Gaurav Kapoor & Nuttanan Wichitaksorn & Mengheng Li & Wenjun Zhang, 2025. "Forecasting Half-Hourly Electricity Prices Using a Mixed-Frequency Structural VAR Framework," Econometrics, MDPI, vol. 13(1), pages 1-26, January.
  2. Pierre Pinson & Liyang Han & Jalal Kazempour, 2022. "Regression markets and application to energy forecasting," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(3), pages 533-573, October.
  3. Berrisch, Jonathan & Ziel, Florian, 2024. "Multivariate probabilistic CRPS learning with an application to day-ahead electricity prices," International Journal of Forecasting, Elsevier, vol. 40(4), pages 1568-1586.
  4. Tesi Aliaj & Milos Ciganovic & Massimiliano Tancioni, 2023. "Nowcasting inflation with Lasso‐regularized vector autoregressions and mixed frequency data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(3), pages 464-480, April.
  5. Bingchun Liu & Shijie Zhao & Xiaogang Yu & Lei Zhang & Qingshan Wang, 2020. "A Novel Deep Learning Approach for Wind Power Forecasting Based on WD-LSTM Model," Energies, MDPI, vol. 13(18), pages 1-17, September.
  6. Billé, Anna Gloria & Gianfreda, Angelica & Del Grosso, Filippo & Ravazzolo, Francesco, 2023. "Forecasting electricity prices with expert, linear, and nonlinear models," International Journal of Forecasting, Elsevier, vol. 39(2), pages 570-586.
  7. Raja, Aitazaz Ali & Pinson, Pierre & Kazempour, Jalal & Grammatico, Sergio, 2024. "A market for trading forecasts: A wagering mechanism," International Journal of Forecasting, Elsevier, vol. 40(1), pages 142-159.
  8. Zhao, Yongning & Zhao, Yuan & Liao, Haohan & Pan, Shiji & Zheng, Yingying, 2025. "Interpreting LASSO regression model by feature space matching analysis for spatio-temporal correlation based wind power forecasting," Applied Energy, Elsevier, vol. 380(C).
  9. Jonathan Berrisch & Florian Ziel, 2023. "Multivariate Probabilistic CRPS Learning with an Application to Day-Ahead Electricity Prices," Papers 2303.10019, arXiv.org, revised Feb 2024.
  10. Camehl, Annika, 2023. "Penalized estimation of panel vector autoregressive models: A panel LASSO approach," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1185-1204.
  11. Simon Hirsch & Jonathan Berrisch & Florian Ziel, 2024. "Online Distributional Regression," Papers 2407.08750, arXiv.org, revised Aug 2024.
  12. Yang, Jinyu & Dong, Dayong & Liang, Chao, 2024. "Climate policy uncertainty and the U.S. economic cycle," Technological Forecasting and Social Change, Elsevier, vol. 202(C).
  13. Mo, Jixian & Gao, Ruobin & Fai Yuen, Kum & Bai, Xiwen, 2024. "Predictive analysis of sell-and-purchase shipping market: A PIMSE approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 185(C).
  14. Wen, Honglin & Pinson, Pierre & Gu, Jie & Jin, Zhijian, 2024. "Wind energy forecasting with missing values within a fully conditional specification framework," International Journal of Forecasting, Elsevier, vol. 40(1), pages 77-95.
  15. Dong, Yingchao & Zhang, Hongli & Wang, Cong & Zhou, Xiaojun, 2021. "A novel hybrid model based on Bernstein polynomial with mixture of Gaussians for wind power forecasting," Applied Energy, Elsevier, vol. 286(C).
  16. Tawn, R. & Browell, J., 2022. "A review of very short-term wind and solar power forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 153(C).
  17. Sommer, Benedikt & Pinson, Pierre & Messner, Jakob W. & Obst, David, 2021. "Online distributed learning in wind power forecasting," International Journal of Forecasting, Elsevier, vol. 37(1), pages 205-223.
  18. Simon Hirsch, 2025. "Online Multivariate Regularized Distributional Regression for High-dimensional Probabilistic Electricity Price Forecasting," Papers 2504.02518, arXiv.org.
  19. Ali Javaid & Umer Javaid & Muhammad Sajid & Muhammad Rashid & Emad Uddin & Yasar Ayaz & Adeel Waqas, 2022. "Forecasting Hydrogen Production from Wind Energy in a Suburban Environment Using Machine Learning," Energies, MDPI, vol. 15(23), pages 1-13, November.
  20. Jia, Yanyan & Fang, Yi & Jing, Zhongbo & Lin, Faqin, 2022. "Price connectedness and input–output linkages: Evidence from China," Economic Modelling, Elsevier, vol. 116(C).
  21. González-Sopeña, J.M. & Pakrashi, V. & Ghosh, B., 2021. "An overview of performance evaluation metrics for short-term statistical wind power forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
  22. Lu, Peng & Yang, Jianbin & Ye, Lin & Zhang, Ning & Wang, Yaqing & Di, Jingyi & Gao, Ze & Wang, Cheng & Liu, Mingyang, 2024. "A novel adaptively combined model based on induced ordered weighted averaging for wind power forecasting," Renewable Energy, Elsevier, vol. 226(C).
  23. Aitazaz Ali Raja & Pierre Pinson & Jalal Kazempour & Sergio Grammatico, 2022. "A Market for Trading Forecasts: A Wagering Mechanism," Papers 2205.02668, arXiv.org, revised Oct 2022.
  24. Wang, Da & Yang, Mao & Zhang, Wei & Ma, Chenglian & Su, Xin, 2025. "Short-term power prediction method of wind farm cluster based on deep spatiotemporal correlation mining," Applied Energy, Elsevier, vol. 380(C).
  25. Lv, Jiaqing & Zheng, Xiaodong & Pawlak, Mirosław & Mo, Weike & Miśkowicz, Marek, 2021. "Very short-term probabilistic wind power prediction using sparse machine learning and nonparametric density estimation algorithms," Renewable Energy, Elsevier, vol. 177(C), pages 181-192.
  26. Berrisch, Jonathan & Ziel, Florian, 2023. "CRPS learning," Journal of Econometrics, Elsevier, vol. 237(2).
  27. Rafati, Amir & Joorabian, Mahmood & Mashhour, Elaheh & Shaker, Hamid Reza, 2021. "High dimensional very short-term solar power forecasting based on a data-driven heuristic method," Energy, Elsevier, vol. 219(C).
  28. Spilger, Maike & Schneider, Dennis & Weber, Christoph, 2025. "Uncertainty characterization for generation adequacy assessments – Including an application to the recent European energy crisis," Energy Economics, Elsevier, vol. 144(C).
  29. Lagomarsino-Oneto, Daniele & Meanti, Giacomo & Pagliana, Nicolò & Verri, Alessandro & Mazzino, Andrea & Rosasco, Lorenzo & Seminara, Agnese, 2023. "Physics informed machine learning for wind speed prediction," Energy, Elsevier, vol. 268(C).
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