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Copula-based fuzzy clustering of spatial time series.

Disegna, M., D'Urso, P. and Durante, F., 2017. Copula-based fuzzy clustering of spatial time series. Spatial Statistics, 21 (Part A August), 209-225.

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2017SPASTA_DDD_proof.pdf - Accepted Version
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DOI: 10.1016/j.spasta.2017.07.002


This paper contributes to the existing literature on the analysis of spatial time series presenting a new clustering algorithm called COFUST, i.e. COpula-based FUzzy clustering algorithm for Spatial Time series. The underlying idea of this algorithm is to perform a fuzzy Partitioning Around Medoids (PAM) clustering using copula-based approach to interpret comovements of time series. This generalisation allows both to extend usual clustering methods for time series based on Pearson’s correlation and to capture the uncertainty that arises assigning units to clusters. Furthermore, its flexibility permits to include directly in the algorithm the spatial information. Our approach is presented and discussed using both simulated and real data, highlighting its main advantages.

Item Type:Article
Uncontrolled Keywords:Copula; Fuzzy clustering; Partitioning around medoids; Spatial statistics; Time series; Tourism economics
Group:Bournemouth University Business School
ID Code:29518
Deposited By: Symplectic RT2
Deposited On:25 Jul 2017 12:01
Last Modified:14 Mar 2022 14:06


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