Elucidate structure in intermittent demand series

DOI10.1016/j.ejor.2020.05.046zbMath1487.90029OpenAlexW3032341964MaRDI QIDQ2028849

George Athanasopoulos, Nikolaos Kourentzes

Publication date: 3 June 2021

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

Full work available at URL: https://www.monash.edu/business/ebs/research/publications/ebs/wp27-2019.pdf

zbMATH Keywords

forecastingforecast combinationtemporal aggregationforecast reconciliationtemporal hierarchies

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Inventory, storage, reservoirs (90B05)

Related Items (3)

Probabilistic forecast reconciliation: properties, evaluation and score optimisation ⋮ Efficient probabilistic reconciliation of forecasts for real-valued and count time series ⋮ A new taxonomy for vector exponential smoothing and its application to seasonal time series

Uses Software

• R
• forecast
• Forecast
• expsmooth
• tsintermittent
• fpp2
• thief
• DeepAR

Cites Work

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• Optimal combination forecasts for hierarchical time series
• Forecasting with exponential smoothing. The state space approach
• A greedy aggregation-decomposition method for intermittent demand forecasting in fashion retailing
• Forecasting with temporal hierarchies
• Periodic control of intermittent demand items: theory and empirical analysis
• Model Selection and Multimodel Inference
• Demand forecasting by temporal aggregation
• Optimal Forecast Reconciliation for Hierarchical and Grouped Time Series Through Trace Minimization
• Strictly Proper Scoring Rules, Prediction, and Estimation
• On the categorization of demand patterns
• Forecasting and Stock Control for Intermittent Demands

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