Probabilistic forecast reconciliation: properties, evaluation and score optimisation

DOI10.1016/j.ejor.2022.07.040OpenAlexW3080971905MaRDI QIDQ6106494

Puwasala Gamakumara, Anastasios Panagiotelis, Rob Hyndman, George Athanasopoulos

Publication date: 3 July 2023

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://figshare.com/articles/journal_contribution/Probabilistic_Forecast_Reconciliation_Properties_Evaluation_and_Score_Optimisation/21529341

zbMATH Keywords

forecastingstochastic gradient descentscoring ruleshierarchical time series

Mathematics Subject Classification ID

Operations research and management science (90Bxx)

Related Items (2)

Probabilistic Forecast Reconciliation under the Gaussian Framework ⋮ Efficient probabilistic reconciliation of forecasts for real-valued and count time series

Cites Work

• Optimal combination forecasts for hierarchical time series
• Forecasting with temporal hierarchies
• Elucidate structure in intermittent demand series
• Forecasting Swiss exports using Bayesian forecast reconciliation
• Assessing mortality inequality in the U.S.: what can be said about the future?
• Temporal hierarchies with autocorrelation for load forecasting
• Large-Scale Machine Learning with Stochastic Gradient Descent
• Boosting With theL₂Loss
• Quasi-Random Sampling for Multivariate Distributions via Generative Neural Networks
• Optimal Forecast Reconciliation for Hierarchical and Grouped Time Series Through Trace Minimization
• Strictly Proper Scoring Rules, Prediction, and Estimation
• Hierarchical Probabilistic Forecasting of Electricity Demand With Smart Meter Data

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