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https://hdl.handle.net/11000/32298
Analysis of Weighting Strategies for Improving the Accuracy of Combined Forecasts
Título : Analysis of Weighting Strategies for Improving the Accuracy of Combined Forecasts |
Autor : Segura-Heras, José Vicente Bermúdez, José D. Corberan-Vallet, Ana Vercher, Enriqueta |
Editor : MDPI |
Departamento: Departamentos de la UMH::Estadística, Matemáticas e Informática |
Fecha de publicación: 2022-02-24 |
URI : https://hdl.handle.net/11000/32298 |
Resumen :
This paper deals with the weighted combination of forecasting methods using intelligent
strategies for achieving accurate forecasts. In an effort to improve forecasting accuracy, we develop
an algorithm that optimizes both the methods used in the combination and the weights assigned to
the individual forecasts, COmbEB. The performance of our procedure can be enhanced by analyzing
separately seasonal and non-seasonal time series. We study the relationships between prediction
errors in the validation set and those of ex-post forecasts for different planning horizons. This study
reveals the importance of setting the size of the validation set in a proper way. The performance of
the proposed strategy is compared with that of the best prediction strategy in the analysis of each of
the 100,000 series included in the M4 Competition.
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Palabras clave/Materias: forecasting time series methods forecasting combination M4 Competition |
Área de conocimiento : CDU: Ciencias puras y naturales: Matemáticas |
Tipo documento : application/pdf |
Derechos de acceso: info:eu-repo/semantics/openAccess |
DOI : https://doi.org/10.3390/math10050725 |
Aparece en las colecciones: Artículos Estadística, Matemáticas e Informática
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La licencia se describe como: Atribución-NonComercial-NoDerivada 4.0 Internacional.