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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2019
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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. |
format | Online Article Text |
id | pubmed-6776316 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT spiliotisevangelos improvingtheforecastingperformanceoftemporalhierarchies AT petropoulosfotios improvingtheforecastingperformanceoftemporalhierarchies AT assimakopoulosvassilios improvingtheforecastingperformanceoftemporalhierarchies |