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arXiv · 1805.00861

Modelling cross-dependencies between Spain's regional tourism markets with an extension of the Gaussian process regression model

Oscar Claveria·Enric Monte·Salvador Torra
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Abstract

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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Oscar Claveria, Enric Monte, Salvador Torra. 2018-05-02. Modelling cross-dependencies between Spain's regional tourism markets with an extension of the Gaussian process regression model. https://doi.org/10.1007/s13209-016-0144-7

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