Recently, the Italian Statistical Agency Istat faced the problem of defining the new SLL (Local labour Systems) considering the data on commuting flows between municipalities collected in the last Italian Census (2011) by using a nonhierarchical agglomerative clustering procedure. We propose instead a model based clustering technique that directly accounts for network relations between municipalities and their position in geographical space. The model is based on latent and manifest geographical coordinates, a gaussian mixture distribution for the coordinates is considered and allows us to obtain a clustering of the municipalities based on the flows (having discounted for the population sizes). The model is estimated on commuting flows between municipalities in Friuli-Venezia Giulia region using the Bayesian approach. Results are compared with those recently presented by Istat.
A model for clustering a spatial network with application to local labour system identification
PAULI, FRANCESCO;TORELLI, Nicola;ZACCARIN, SUSANNA
2015-01-01
Abstract
Recently, the Italian Statistical Agency Istat faced the problem of defining the new SLL (Local labour Systems) considering the data on commuting flows between municipalities collected in the last Italian Census (2011) by using a nonhierarchical agglomerative clustering procedure. We propose instead a model based clustering technique that directly accounts for network relations between municipalities and their position in geographical space. The model is based on latent and manifest geographical coordinates, a gaussian mixture distribution for the coordinates is considered and allows us to obtain a clustering of the municipalities based on the flows (having discounted for the population sizes). The model is estimated on commuting flows between municipalities in Friuli-Venezia Giulia region using the Bayesian approach. Results are compared with those recently presented by Istat.File | Dimensione | Formato | |
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Torelli_A MODEL FOR CLUSTERING A SPATIAL NETWORK.pdf
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