We introduce a clustering method for time series based on tail dependence. Such a method considers spatial constraints by means of a suitable dissimilarity index that merges temporal and spatial dependence via extreme-value copulas. The proposed approach is applied to the study of rainfall extremes.
An approach to cluster time series extremes with spatial constraints / Benevento, Alessia; Durante, Fabrizio; Pappada', Roberta. - ELETTRONICO. - (2023), pp. 679-684. ( SEAS IN 2023 - Statistical Learning, Sustainability and Impact Evaluation Ancona 21-23 Giugno 2023).
An approach to cluster time series extremes with spatial constraints
Roberta Pappada'
2023-01-01
Abstract
We introduce a clustering method for time series based on tail dependence. Such a method considers spatial constraints by means of a suitable dissimilarity index that merges temporal and spatial dependence via extreme-value copulas. The proposed approach is applied to the study of rainfall extremes.File in questo prodotto:
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