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fable.intermittent: benchmarking probabilistic forecasting methods for intermittent time series

Damato, Stefano et al.
arXiv (All) · Papers
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machine-learning
Intermittent time series are common in spare-parts demand and retail sales. Since the cost of forecast errors is typically asymmetric, decisions such as inventory control require the full predictive distribution rather than a point forecast. Many probabilistic forecasting methods have been proposed;
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