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Comparison of non-homogeneous regression models for probabilistic wind speed forecasting [PDF]
Tellus: Series A, Dynamic Meteorology and Oceanography, 2013 In weather forecasting, non-homogeneous regression (NR) is used to statistically post-process forecast ensembles in order to obtain calibrated predictive distributions.
Sebastian Lerch +1 more
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Adaptive Significance Levels in Tests for Linear Regression Models: The e-Value and P-Value Cases
Entropy, 2022 The full Bayesian significance test (FBST) for precise hypotheses is a Bayesian alternative to the traditional significance tests based on p-values. The FBST is characterized by the e-value as an evidence index in favor of the null hypothesis (H).
Alejandra E. Patiño Hoyos +3 more
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A Central Limit Theorem for Predictive Distributions
Mathematics, 2021 Let S be a Borel subset of a Polish space and F the set of bounded Borel functions f:S→R. Let an(·)=P(Xn+1∈·∣X1,…,Xn) be the n-th predictive distribution corresponding to a sequence (Xn) of S-valued random variables.
Patrizia Berti +2 more
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Multi-Output Variational Gaussian Process for Daily Forecasting of Hydrological Resources
Engineering Proceedings, 2023 Water resource forecasting plays a crucial role in managing hydrological reservoirs, supporting operational decisions ranging from the economy to energy.
Julián David Pastrana-Cortés +4 more
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Meta-analysis Using Flexible Random-effects Distribution Models
Journal of Epidemiology, 2022 Background: In meta-analysis, the normal distribution assumption has been adopted in most systematic reviews of random-effects distribution models due to its computational and conceptual simplicity.
Hisashi Noma +4 more
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On Johnson’s “Sufficientness” Postulates for Feature-Sampling Models
Mathematics, 2021 In the 1920s, the English philosopher W.E. Johnson introduced a characterization of the symmetric Dirichlet prior distribution in terms of its predictive distribution. This is typically referred to as Johnson’s “sufficientness” postulate, and it has been
Federico Camerlenghi, Stefano Favaro
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Dataset of distribution transformers for predictive maintenance
Data in Brief, 2021 In electricity sector is possible to collect large quantities of data that contain information on relevant processes and events that occur in a given period.
Diego-A Bravo M +2 more
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A brief look into Bayesian statistics in cardiology data analysis
REC: Interventional Cardiology (English Ed.), 2022 Bayesian statistics assesses probabilistically all sources of uncertainty involved in a statistical study and uses Bayes’ theorem to sequentially update the information generated in the different phases of the study.
Carmen Armero +2 more
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Scientia Agricola, 2011 The animal breeding values forecasting at futures times is a relevant technological innovation in the field of Animal Science, since its enables a previous indication of animals that will be either kept by the producer for breeding purposes or discarded.
Fabyano Fonseca e Silva +6 more
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Dynamic items delivery network: prediction and clustering
Heliyon, 2021 Items delivery companies generally use a model to minimize delivery costs. From a mathematical perspective, the model is an objective function that involves constraints.
Mokhammad R. Yudhanegara +2 more
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