Probabilistic wind speed forecasting using Bayesian model averaging with truncated normal components

DOI10.1016/j.csda.2014.02.013zbMath1506.62019arXiv1305.1184OpenAlexW1993642620MaRDI QIDQ1623494

Sándor Baran

Publication date: 23 November 2018

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1305.1184

zbMATH Keywords

ensemble calibrationtruncated normal distributioncontinuous ranked probability score

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Bayesian inference (62F15) Geostatistics (86A32)

Related Items (6)

Stochastic simulation of predictive space-time scenarios of wind speed using observations and physical model outputs ⋮ Semiparametric model averaging method for survival probability predictions of patients ⋮ Joint probabilistic forecasting of wind speed and temperature using Bayesian model averaging ⋮ Mixture EMOS model for calibrating ensemble forecasts of wind speed ⋮ Censored and shifted gamma distribution based EMOS model for probabilistic quantitative precipitation forecasting ⋮ Statistical Treatment of Inverse Problems Constrained by Differential Equations-Based Models with Stochastic Terms

Uses Software

• ensembleBMA
• MM5

Cites Work

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• Editorial: The 2nd special issue on advances in mixture models
• Improving mixture tree construction using better EM algorithms
• EM algorithms for multivariate Gaussian mixture models with truncated and censored data
• Ensemble forecasting
• Strictly Proper Scoring Rules, Prediction, and Estimation
• Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center

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