Spatio-temporal clustering: Neighbourhoods based on median seasonal entropy

Abstract


In this research, a new uncertainty clustering method has been developed and applied to the spatial time series with seasonality. The new unsupervised grouping method is based on Neighbourhoods and Median Seasonal Entropy. This classification method aims to discover similar behaviours for a time series group and find a dissimilarity measure concerning a reference series r. The Neighbourhood’s Internal Verification Coefficient criterion makes it possible to measure intra-group similarity. This clustering criterion is flexible for spatial information. Our empirical approach allows us to measure accommodation decisions for tourists who visit Spain and decide to stay either in hotels or in tourist apartments. The results show the existence of dynamic seasonal patterns of behaviour. These insights support the decisions of economic agents. View Full-Text

Keywords: Spatial time series, Seasonal clustering, Entropy, Tourism economics, Neighbourhoods, Information theory






Si te suscribes...

  •  Te avisaremos de los nuevos Cursos, Talleres y Master Class que hagamos ONLINE.

  •  Tendrás acceso a ofertas y promociones puntuales.

  •  Si has estudiado Economía, ADE, Turismo. Recibirás ofertas de trabajo.

  •  Te mantendremos informado sobre novedades del sector de la Econometría.

  •  Te mandaremos tutoriales sobre herramientas de Econometría.

  • Facebook Classic
  • Twitter Classic
  • Google Classic