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Research questionHow should forecasting-model selection adapt to demand patterns, available history, and forecast horizon?A single model-selection rule may choose inconsistently across demand patterns and forecasting conditions. The suitable selector can change with both the amount of historical data and how far ahead forecasts are required.
Business
Economics
Research Paper
Statistical Machine Learning
Latest papersRecent research connected to this question, newest first.Beyond a Universal Forecasting Selector: Demand-Conditioned Model Selection across Demand Patterns and HorizonsThe study compares five selection mechanisms across 24 optimized forecasting models, nine datasets, three training-testing partitions, and horizons from 1 to 12 cycles. It evaluates selector performance ex post using Global Relative Accuracy, statistical tests, and a best-attainable-model reference; the evidence indicates that selector suitability varies by demand configuration, data availability, and horizon.research paper · Sep 3, 2026
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