Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 2927-2940 |
| Number of pages | 14 |
| Journal | Journal of Applied Statistics |
| DOIs | |
| Publication status | Published - 2020 |
Bibliographical note
Publisher Copyright:© 2020, © 2020 Informa UK Limited, trading as Taylor & Francis Group.
Funding
This work was partially supported by the Center for Research and Development in Mathematics and Applications (CIDMA) through the Portuguese Foundation for Science and Technology (FCT–Fundação para a Ciência e a Tecnologia), references UIDB/04106/2020 and UIDP/04106/2020. he authors thank to the anonymous referees for their comments.
| Funders | Funder number |
|---|---|
| Fundação para a Ciência e a Tecnologia | UIDB/04106/2020, UIDP/04106/2020 |
| Center for Research and Development in Mathematics and Applications |
Keywords
- Forecasting
- neural networks
- overnight stays
- singular spectrum analysis
- time series
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