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Forecasting model selection through out-of-sample rolling horizon weighted errors

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Forecasting model selection through out-of-sample rolling horizon weighted errors

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Poler Escoto, R.; Mula, J. (2011). Forecasting model selection through out-of-sample rolling horizon weighted errors. Expert Systems with Applications. 38(12):14778-14785. doi:10.1016/j.eswa.2011.05.072

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/51211

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Title: Forecasting model selection through out-of-sample rolling horizon weighted errors
Author:
UPV Unit: Universitat Politècnica de València. Centro de Investigación de Gestión e Ingeniería de la Producción - Centre d'Investigació de Gestió i Enginyeria de la Producció
Universitat Politècnica de València. Departamento de Organización de Empresas - Departament d'Organització d'Empreses
Issued date:
Abstract:
Demand forecasting is an essential process for any firm whether it is a supplier, manufacturer or retailer. A large number of research works about time series forecast techniques exists in the literature, and there are ...[+]
Subjects: Automatic forecasting , Error measures , Expert system , Forecasting model selection , Time series , Automatic selection , Complex problems , Demand forecast , Demand forecasting , Forecasting models , Rolling horizon , Selection criteria , Steel products , Time series forecasting , Time series forecasts , Expert systems , Forecasting
Copyrigths: Reserva de todos los derechos
Source:
Expert Systems with Applications. (issn: 0957-4174 )
DOI: 10.1016/j.eswa.2011.05.072
Publisher:
Elsevier
Publisher version: http://dx.doi.org/10.1016/10.1016/j.eswa.2011.05.072
Type: Artículo

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