Publication: Modelos de predicción para el sector turístico andaluz mediante métodos estadísticos avanzados
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Date
2021
Authors
Sánchez Sánchez, Francisca J. ; Sánchez Sánchez, Ana M.
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Publisher
Universidad de Murcia. Servicio de publicaciones
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DOI
https://doi.org/10.6018/turismo.492731
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info:eu-repo/semantics/article
Description
Abstract
En el trabajo se modeliza la serie temporal “turistas que visitan Andalucía”, variable que presenta una fuerte componente estacional. Se plantea y analiza la capacidad predictiva de tres modelos diferentes, aplicando distintas metodologías de modelización (Box-Jenkins, Holt-Winters y métodos combinados). Se comparan los resultados obtenidos de las predicciones con los valores reales de la serie de turismo, valorándose la buena capacidad predictiva de las tres metodologías empleadas. Se comprueba que el procedimiento clásico de Holt-Winters es el que ofrece mejores resultados predictivos.
In the work, the time series “tourists were visiting Andalusia” is modeled, a variable that has a strong seasonal component. The forecasting capacity of three different models is considered and analyzed, applying different modeling methodologies (Box-Jenkins, Holt-Winters and combined methods). The results obtained from the predictions are compared with the real values of the tourism series, assessing the good forecasting capacity of the three methodologies used. It is verified that the classic Holt-Winters procedure is theone that offers the best predictive results
In the work, the time series “tourists were visiting Andalusia” is modeled, a variable that has a strong seasonal component. The forecasting capacity of three different models is considered and analyzed, applying different modeling methodologies (Box-Jenkins, Holt-Winters and combined methods). The results obtained from the predictions are compared with the real values of the tourism series, assessing the good forecasting capacity of the three methodologies used. It is verified that the classic Holt-Winters procedure is theone that offers the best predictive results
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Citation
Cuadernos de Turismo, N.º 48 (2021)
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