[HTML][HTML] Correlation-based hierarchical clustering of time series with spatial constraints
A Benevento, F Durante - Spatial Statistics, 2024 - Elsevier
Correlation-based hierarchical clustering methods for time series typically are based on a
suitable dissimilarity matrix derived from pairwise measures of association. Here, this …
suitable dissimilarity matrix derived from pairwise measures of association. Here, this …
Wasserstein dissimilarity for copula-based clustering of time series with spatial information
A Benevento, F Durante - Mathematics, 2023 - mdpi.com
The clustering of time series with geo-referenced data requires a suitable dissimilarity matrix
interpreting the comovements of the time series and taking into account the spatial …
interpreting the comovements of the time series and taking into account the spatial …
Traffic flows time series in a flood-prone area: modeling and clustering on extreme values with a spatial constraint
Time series of traffic flows, extracted from mobile phone origin–destination data, are
employed for monitoring people crowding and mobility in areas subject to flooding risk. By …
employed for monitoring people crowding and mobility in areas subject to flooding risk. By …
Tail-dependence clustering of time series with spatial constraints
We introduce a clustering method for time series based on tail dependence. Such a method
also considers spatial constraints by means of a suitable procedure merging temporal and …
also considers spatial constraints by means of a suitable procedure merging temporal and …
Dissimilarity-based clustering with soft proximity constraints
We provide a general framework for the definition of dissimilarity measures to cluster
dependent random variables. A copula-based pairwise dissimilarity measure that takes into …
dependent random variables. A copula-based pairwise dissimilarity measure that takes into …