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When Does Pooling Pay? Credibility and Resolution under Forgetting in Intermittent-Demand Forecasting

Bai, Zong-Han et al.
arXiv (All) · Papers
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machine-learning
Forecasting many sparse series requires two choices: how much of each series' own past to retain, and how much to borrow from other series. We show that when one exponential recency operator is applied to item- and group-level statistics alike in a hierarchical empirical-Bayes hurdle model, the two
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