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Forecasting intermittent and sparse time series: A unified probabilistic framework via deep renewal processes
Intermittency are a common and challenging problem in demand forecasting. We introduce a new, unified framework for building probabilistic forecasting models for intermittent demand time series, which incorporates and allows to generalize existing methods in several directions. Our framework is base...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Public Library of Science
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8629246/ https://www.ncbi.nlm.nih.gov/pubmed/34843508 http://dx.doi.org/10.1371/journal.pone.0259764 |