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Si us plau utilitzeu sempre aquest identificador per citar o enllaçar aquest document: https://hdl.handle.net/2445/101764
Modelling cross-dependencies between Spain's regional tourism markets with an extension of the Gaussian process regression model
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This study presents an extension of the Gaussian process regression model for multiple-input multiple-output forecasting. This approach allows modelling the cross-dependencies between a given set of input variables and generating a vectorial prediction. Making use of the existing correlations in international tourism demand to all seventeen regions of Spain, the performance of the proposed model is assessed in a multiple-step-ahead forecasting comparison. The results of the experiment in a multivariate setting show that the Gaussian process regression model significantly improves the forecasting accuracy of a multi-layer perceptron neural network used as a benchmark. The results reveal that incorporating the connections between different markets in the modelling process may prove very useful to refine predictions at a regional level.
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CLAVERÍA GONZÁLEZ, Óscar, MONTE MORENO, Enric, TORRA PORRAS, Salvador. Modelling cross-dependencies between Spain's regional tourism markets with an extension of the Gaussian process regression model. _Series-Journal Of The Spanish Economic Association_. 2016. Vol. 7, núm. 3, pàgs. 341-357. [consulta: 25 de febrer de 2026]. ISSN: 1869-4187. [Disponible a: https://hdl.handle.net/2445/101764]