Results 21 to 30 of about 10,696 (267)
Recalibrating probabilistic forecasts of epidemics
PLOS Computational Biology, 2022 Distributional forecasts are important for a wide variety of applications, including forecasting epidemics. Often, forecasts are miscalibrated, or unreliable in assigning uncertainty to future events. We present a recalibration method that can be applied to a black-box forecaster given retrospective forecasts and observations, as well as an extension ...
Aaron Rumack +2 more
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Probabilistic Forecasts, Calibration and Sharpness [PDF]
Journal of the Royal Statistical Society Series B: Statistical Methodology, 2007 SummaryProbabilistic forecasts of continuous variables take the form of predictive densities or predictive cumulative distribution functions. We propose a diagnostic approach to the evaluation of predictive performance that is based on the paradigm of maximizing the sharpness of the predictive distributions subject to calibration. Calibration refers to
Gneiting, Tilmann +2 more
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A novel Bayesian ensembling model for wind power forecasting
Heliyon, 2022 Precise and robust wind power prediction can effectively alleviate the problem caused by the randomness and volatility of wind power. Ensemble learning can successfully improve forecasting precision and robustness, and quantify the uncertainty of the ...
Jingwei Tang +3 more
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Evaluating probabilistic population forecasts [PDF]
Economie et Statistique / Economics and Statistics, 2020 Abstract We demonstrate how a probabilistic population forecast can be evaluated, when observations for the predicted variables become available. Statisticians have developed various scoring rules for that purpose, but there are hardly any applications in population forecasting literature.
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Probabilistic short-term power load forecasting based on B-SCN
Energy Reports, 2022 Grid management and power dispatching rely on accurate short-term power load prediction. Different algorithms have been constantly developed and tested to improve forecast precision.
Yi Ning +5 more
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The Calibration of Probabilistic Economic Forecasts [PDF]
SSRN Electronic Journal, 2008 A probabilistic forecast is the estimated probability with which a future event will satisfy a specified criterion. One interesting feature of such forecasts is their calibration, or the match between predicted probabilities and actual outcome probabilities.
John Galbraith, Simon van Norden
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A probabilistic track model for tropical cyclone risk assessment using multitask learning
Frontiers in Energy Research, 2023 Tropical cyclone (TC) track forecasting is critical for wind risk assessment. This work proposes a novel probabilistic TC track forecasting model based on mixture density network (MDN) and multitask learning (MTL).
Zhou Jian, Xuan Liu, Tianyang Zhao
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Use and communication of probabilistic forecasts [PDF]
Statistical Analysis and Data Mining: The ASA Data Science Journal, 2016 Probabilistic forecasts are becoming more and more available. How should they be used and communicated? What are the obstacles to their use in practice? We review experience with five problems where probabilistic forecasting played an important role.
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Conditional Probabilistic Population Forecasting [PDF]
Institut für Demographie - VID, 2004 Summary Since policy‐makers often prefer to think in terms of alternative scenarios, the question has arisen as to whether it is possible to make conditional population forecasts in a probabilistic context. This paper shows that it is both possible and useful to make these forecasts. We do this with two different kinds of examples.
Sanderson, W.C. +3 more
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Denoising Diffusion Probabilistic Models for Probabilistic Energy Forecasting
2023 IEEE Belgrade PowerTech, 2023 Scenario-based probabilistic forecasts have become vital for decision-makers in handling intermittent renewable energies. This paper presents a recent promising deep learning generative approach called denoising diffusion probabilistic models. It is a class of latent variable models which have recently demonstrated impressive results in the computer ...
Esteban Hernandez Capel, Jonathan Dumas
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