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Analysis of Weighting Strategies for Improving the Accuracy of Combined Forecasts


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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.
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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