New developments in the forecasting of monthly overnight stays in the North Region of Portugal

Detalhes bibliográficos
Autor(a) principal: Isabel Silva
Data de Publicação: 2020
Outros Autores: Hugo Alonso
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: https://hdl.handle.net/10216/127968
Resumo: The Tourism sector is of strategic importance to the North Region of Portugal and is growing. Forecasting monthly overnight stays in this region is, therefore, a relevant problem. In this paper, we analyze data more recent than those considered in previous studies and use them to develop and compare several forecasting models and methods. We conclude that the best results are achieved by models based on a non-parametric approach not considered so far for these data, the singular spectrum analysis. (c) 2020, (c) 2020 Informa UK Limited, trading as Taylor & Francis Group.
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spelling New developments in the forecasting of monthly overnight stays in the North Region of PortugalThe Tourism sector is of strategic importance to the North Region of Portugal and is growing. Forecasting monthly overnight stays in this region is, therefore, a relevant problem. In this paper, we analyze data more recent than those considered in previous studies and use them to develop and compare several forecasting models and methods. We conclude that the best results are achieved by models based on a non-parametric approach not considered so far for these data, the singular spectrum analysis. (c) 2020, (c) 2020 Informa UK Limited, trading as Taylor & Francis Group.20202020-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/10216/127968eng0266-476310.1080/02664763.2020.1795812Isabel SilvaHugo Alonsoinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-29T15:21:39Zoai:repositorio-aberto.up.pt:10216/127968Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T00:21:39.328224Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv New developments in the forecasting of monthly overnight stays in the North Region of Portugal
title New developments in the forecasting of monthly overnight stays in the North Region of Portugal
spellingShingle New developments in the forecasting of monthly overnight stays in the North Region of Portugal
Isabel Silva
title_short New developments in the forecasting of monthly overnight stays in the North Region of Portugal
title_full New developments in the forecasting of monthly overnight stays in the North Region of Portugal
title_fullStr New developments in the forecasting of monthly overnight stays in the North Region of Portugal
title_full_unstemmed New developments in the forecasting of monthly overnight stays in the North Region of Portugal
title_sort New developments in the forecasting of monthly overnight stays in the North Region of Portugal
author Isabel Silva
author_facet Isabel Silva
Hugo Alonso
author_role author
author2 Hugo Alonso
author2_role author
dc.contributor.author.fl_str_mv Isabel Silva
Hugo Alonso
description The Tourism sector is of strategic importance to the North Region of Portugal and is growing. Forecasting monthly overnight stays in this region is, therefore, a relevant problem. In this paper, we analyze data more recent than those considered in previous studies and use them to develop and compare several forecasting models and methods. We conclude that the best results are achieved by models based on a non-parametric approach not considered so far for these data, the singular spectrum analysis. (c) 2020, (c) 2020 Informa UK Limited, trading as Taylor & Francis Group.
publishDate 2020
dc.date.none.fl_str_mv 2020
2020-01-01T00:00:00Z
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dc.language.iso.fl_str_mv eng
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10.1080/02664763.2020.1795812
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