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Improving the forecasting performance of temporal hierarchies

Temporal hierarchies have been widely used during the past few years as they are capable to provide more accurate coherent forecasts at different planning horizons. However, they still display some limitations, being mainly subject to the forecasting methods used for generating the base forecasts an...

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Detalles Bibliográficos
Autores principales: Spiliotis, Evangelos, Petropoulos, Fotios, Assimakopoulos, Vassilios
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6776316/
https://www.ncbi.nlm.nih.gov/pubmed/31581211
http://dx.doi.org/10.1371/journal.pone.0223422
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author Spiliotis, Evangelos
Petropoulos, Fotios
Assimakopoulos, Vassilios
author_facet Spiliotis, Evangelos
Petropoulos, Fotios
Assimakopoulos, Vassilios
author_sort Spiliotis, Evangelos
collection PubMed
description Temporal hierarchies have been widely used during the past few years as they are capable to provide more accurate coherent forecasts at different planning horizons. However, they still display some limitations, being mainly subject to the forecasting methods used for generating the base forecasts and the particularities of the examined series. This paper deals with such limitations by considering three different strategies: (i) combining forecasts of multiple methods, (ii) applying bias adjustments and (iii) selectively implementing temporal hierarchies to avoid seasonal shrinkage. The proposed strategies can be applied either separately or simultaneously, being complements to the method considered for reconciling the base forecasts and completely independent from each other. Their effect is evaluated using the monthly series of the M and M3 competitions. The results are very promising, displaying lots of potential for improving the performance of temporal hierarchies, both in terms of accuracy and bias.
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spelling pubmed-67763162019-10-12 Improving the forecasting performance of temporal hierarchies Spiliotis, Evangelos Petropoulos, Fotios Assimakopoulos, Vassilios PLoS One Research Article Temporal hierarchies have been widely used during the past few years as they are capable to provide more accurate coherent forecasts at different planning horizons. However, they still display some limitations, being mainly subject to the forecasting methods used for generating the base forecasts and the particularities of the examined series. This paper deals with such limitations by considering three different strategies: (i) combining forecasts of multiple methods, (ii) applying bias adjustments and (iii) selectively implementing temporal hierarchies to avoid seasonal shrinkage. The proposed strategies can be applied either separately or simultaneously, being complements to the method considered for reconciling the base forecasts and completely independent from each other. Their effect is evaluated using the monthly series of the M and M3 competitions. The results are very promising, displaying lots of potential for improving the performance of temporal hierarchies, both in terms of accuracy and bias. Public Library of Science 2019-10-03 /pmc/articles/PMC6776316/ /pubmed/31581211 http://dx.doi.org/10.1371/journal.pone.0223422 Text en © 2019 Spiliotis et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Spiliotis, Evangelos
Petropoulos, Fotios
Assimakopoulos, Vassilios
Improving the forecasting performance of temporal hierarchies
title Improving the forecasting performance of temporal hierarchies
title_full Improving the forecasting performance of temporal hierarchies
title_fullStr Improving the forecasting performance of temporal hierarchies
title_full_unstemmed Improving the forecasting performance of temporal hierarchies
title_short Improving the forecasting performance of temporal hierarchies
title_sort improving the forecasting performance of temporal hierarchies
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6776316/
https://www.ncbi.nlm.nih.gov/pubmed/31581211
http://dx.doi.org/10.1371/journal.pone.0223422
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