A fast and scalable ensemble of global models with long memory and data partitioning for the M5 forecasting competition
Kasun Bandara, Hansika Hewamalage, Rakshitha Godahewa, Puwasala Gamakumara
| Year of publication: |
2022
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|---|---|
| Authors: | Bandara, Kasun ; Hewamalage, Hansika ; Godahewa, Rakshitha ; Gamakumara, Puwasala |
| Published in: |
International journal of forecasting. - Amsterdam [u.a.] : Elsevier, ISSN 0169-2070, ZDB-ID 283943-X. - Vol. 38.2022, 4, p. 1400-1404
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| Subject: | Global forecasting models | LightGBM models | M5 forecasting competition | Pooled Regression models | Sales demand forecasting | Prognoseverfahren | Forecasting model | Theorie | Theory | Zeitreihenanalyse | Time series analysis | Makroökonometrie | Macroeconometrics | Regressionsanalyse | Regression analysis | Prognose | Forecast |
| Type of publication: | Article |
|---|---|
| Type of publication (narrower categories): | Aufsatz in Zeitschrift ; Article in journal |
| Language: | English |
| Other identifiers: | 10.1016/j.ijforecast.2021.11.004 [DOI] |
| Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10014381097