Hierarchical Spatio-Temporal Change-Point Detection
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Show full item recordcomunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/7037
comunitat-uji-handle3:10234/8635
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INVESTIGACIONMetadata
Title
Hierarchical Spatio-Temporal Change-Point DetectionDate
2023Publisher
Taylor and FrancisISSN
0003-1305; 1537-2731Bibliographic citation
Mehdi Moradi, Ottmar Cronie, Unai Pérez-Goya & Jorge Mateu (2023) Hierarchical Spatio-Temporal Change-Point Detection, The American Statistician, DOI: 10.1080/00031305.2023.2191670Type
info:eu-repo/semantics/articlePublisher version
https://www.tandfonline.com/doi/full/10.1080/00031305.2023.2191670Version
info:eu-repo/semantics/publishedVersionSubject
Abstract
1 Introduction
2 Multivariate Change-Point Detection
3 Hierarchical Spatio-Temporal Change-Point Detection
4 Numerical Evaluation
5 Real Data Analyses
6 Discussion
Supplemental material
Acknowledgements
Refe ... [+]
1 Introduction
2 Multivariate Change-Point Detection
3 Hierarchical Spatio-Temporal Change-Point Detection
4 Numerical Evaluation
5 Real Data Analyses
6 Discussion
Supplemental material
Acknowledgements
References
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AbstractFormulae display:MathJax Logo?
Detecting change-points in multivariate settings is usually carried out by analyzing all marginals either independently, via univariate methods, or jointly, through multivariate approaches. The former discards any inherent dependencies between different marginals and the latter may suffer from domination/masking among different change-points of distinct marginals. As a remedy, we propose an approach which groups marginals with similar temporal behaviors, and then performs group-wise multivariate change-point detection. Our approach groups marginals based on hierarchical clustering using distances which adjust for inherent dependencies. Through a simulation study we show that our approach, by preventing domination/masking, significantly enhances the general performance of the employed multivariate change-point detection method. Finally, we apply our approach to two datasets: (i) Land Surface Temperature in Spain, during the years 2000–2021, and (ii) The WikiLeaks Afghan War Diary data. [-]
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The American Statistician, 2023Related data
https://figshare.com/articles/journal_contribution/Hierarchical_Spatio-Temporal_Change-Point_Detection/22587966Rights
© 2023 The Author(s). Published with license by Taylor & Francis Group, LLC.
info:eu-repo/semantics/openAccess
info:eu-repo/semantics/openAccess
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- MAT_Articles [765]