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Probabilistic forecasts of wind speed: ensemble model output statistics by using heteroscedastic censored regression

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Cited by:

  1. Manuel Gebetsberger & Jakob W. Messner & Georg J. Mayr & Achim Zeileis, 2016. "Tricks for improving non-homogeneous regression for probabilistic precipitation forecasts: Perfect predictions, heavy tails, and link functions," Working Papers 2016-28, Faculty of Economics and Statistics, Universität Innsbruck.
  2. Peter Tankov & Laura Tinsi, 2024. "Stochastic optimization with dynamic probabilistic forecasts," Annals of Operations Research, Springer, vol. 336(1), pages 711-747, May.
  3. Iversen, Emil B. & Morales, Juan M. & Møller, Jan K. & Madsen, Henrik, 2016. "Short-term probabilistic forecasting of wind speed using stochastic differential equations," International Journal of Forecasting, Elsevier, vol. 32(3), pages 981-990.
  4. Moritz N. Lang & Lisa Schlosser & Torsten Hothorn & Georg J. Mayr & Reto Stauffer & Achim Zeileis, 2020. "Circular regression trees and forests with an application to probabilistic wind direction forecasting," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(5), pages 1357-1374, November.
  5. Mayer, David G. & Chandra, Kerri A. & Burnett, Jolyon R., 2019. "Improved crop forecasts for the Australian macadamia industry from ensemble models," Agricultural Systems, Elsevier, vol. 173(C), pages 519-523.
  6. Manuel Gebetsberger & Jakob W. Messner & Georg J. Mayr & Achim Zeileis, 2017. "Estimation methods for non-homogeneous regression models: Minimum continuous ranked probability score vs. maximum likelihood," Working Papers 2017-23, Faculty of Economics and Statistics, Universität Innsbruck.
  7. Lei Zhang & Lun Xie & Qinkai Han & Zhiliang Wang & Chen Huang, 2020. "Probability Density Forecasting of Wind Speed Based on Quantile Regression and Kernel Density Estimation," Energies, MDPI, vol. 13(22), pages 1-24, November.
  8. Yan, Jie & Liu, Yongqian & Han, Shuang & Wang, Yimei & Feng, Shuanglei, 2015. "Reviews on uncertainty analysis of wind power forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1322-1330.
  9. Reto Stauffer & Jakob W. Messner & Georg J. Mayr & Nikolaus Umlauf & Achim Zeileis, 2016. "Ensemble Post-Processing of Daily Precipitation Sums over Complex Terrain Using Censored High-Resolution Standardized Anomalies," Working Papers 2016-21, Faculty of Economics and Statistics, Universität Innsbruck.
  10. Heinermann, Justin & Kramer, Oliver, 2016. "Machine learning ensembles for wind power prediction," Renewable Energy, Elsevier, vol. 89(C), pages 671-679.
  11. Baran, Sándor, 2014. "Probabilistic wind speed forecasting using Bayesian model averaging with truncated normal components," Computational Statistics & Data Analysis, Elsevier, vol. 75(C), pages 227-238.
  12. Jakob W. Messner & Georg J. Mayr & Daniel S. Wilks & Achim Zeileis, 2013. "Extending Extended Logistic Regression for Ensemble Post-Processing: Extended vs. Separate vs. Ordered vs. Censored," Working Papers 2013-32, Faculty of Economics and Statistics, Universität Innsbruck.
  13. Sándor Baran & Patrícia Szokol & Marianna Szabó, 2021. "Truncated generalized extreme value distribution‐based ensemble model output statistics model for calibration of wind speed ensemble forecasts," Environmetrics, John Wiley & Sons, Ltd., vol. 32(6), September.
  14. Chen, Shu-Hua & Yang, Shu-Chih & Chen, Chih-Ying & van Dam, C.P. & Cooperman, Aubryn & Shiu, Henry & MacDonald, Clinton & Zack, John, 2019. "Application of bias corrections to improve hub-height ensemble wind forecasts over the Tehachapi Wind Resource Area," Renewable Energy, Elsevier, vol. 140(C), pages 281-291.
  15. Thorey, J. & Chaussin, C. & Mallet, V., 2018. "Ensemble forecast of photovoltaic power with online CRPS learning," International Journal of Forecasting, Elsevier, vol. 34(4), pages 762-773.
  16. Mário Fernando De Sousa & Helton Saulo & Víctor Leiva & Paulo Scalco, 2018. "On Some Properties Of A New Asymmetry-Based Tobit Model," Anais do XLIV Encontro Nacional de Economia [Proceedings of the 44th Brazilian Economics Meeting] 129, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
  17. Pierre-Julien Trombe & Pierre Pinson & Henrik Madsen, 2012. "A General Probabilistic Forecasting Framework for Offshore Wind Power Fluctuations," Energies, MDPI, vol. 5(3), pages 1-37, March.
  18. Baran, Sándor & Lerch, Sebastian, 2018. "Combining predictive distributions for the statistical post-processing of ensemble forecasts," International Journal of Forecasting, Elsevier, vol. 34(3), pages 477-496.
  19. Zhao, Jing & Guo, Zhen-Hai & Su, Zhong-Yue & Zhao, Zhi-Yuan & Xiao, Xia & Liu, Feng, 2016. "An improved multi-step forecasting model based on WRF ensembles and creative fuzzy systems for wind speed," Applied Energy, Elsevier, vol. 162(C), pages 808-826.
  20. Marie Courbariaux & Pierre Barbillon & Luc Perreault & Éric Parent, 2019. "Post-processing Multiensemble Temperature and Precipitation Forecasts Through an Exchangeable Normal-Gamma Model and Its Tobit Extension," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 24(2), pages 309-345, June.
  21. Alonzo, Bastien & Tankov, Peter & Drobinski, Philippe & Plougonven, Riwal, 2020. "Probabilistic wind forecasting up to three months ahead using ensemble predictions for geopotential height," International Journal of Forecasting, Elsevier, vol. 36(2), pages 515-530.
  22. Jakob W. Messner & Georg J. Mayr & Achim Zeileis, 2016. "Non-homogeneous boosting for predictor selection in ensemble post-processing," Working Papers 2016-04, Faculty of Economics and Statistics, Universität Innsbruck.
  23. Peter Tankov & Laura Tinsi, 2021. "Decision making with dynamic probabilistic forecasts," Papers 2106.16047, arXiv.org.
  24. Sebastian Lerch & Sándor Baran, 2017. "Similarity-based semilocal estimation of post-processing models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(1), pages 29-51, January.
  25. Michaël Zamo & Liliane Bel & Olivier Mestre, 2021. "Sequential aggregation of probabilistic forecasts—Application to wind speed ensemble forecasts," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(1), pages 202-225, January.
  26. Jakob W. Messner & Achim Zeileis & Jochen Broecker & Georg J. Mayr, 2013. "Improved Probabilistic Wind Power Forecasts with an Inverse Power Curve Transformation and Censored Regression," Working Papers 2013-01, Faculty of Economics and Statistics, Universität Innsbruck.
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