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Activity Number:
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2
- Phase Variation (Curve Registration) in Functional Data Analyzing
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Type:
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Invited
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Date/Time:
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Sunday, July 30, 2017 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Nonparametric Statistics
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Abstract #322317
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View Presentation
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Title:
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Clustering Misaligned Dependent Curves
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Author(s):
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Piercesare Secchi* and Konrad Abramowicz and Per Arnqvist and Sara Sj¨ostedt de Luna and Simone Vantini and Valeria Vitelli
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Companies:
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Politecnico di Milano and Umea University and Umea University and Umea University and Politecnico di Milano and University of Oslo
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Keywords:
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Functional data ;
Dependence ;
Misalignment
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Abstract:
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We introduce a novel functional clustering method, the Bagging Voronoi K-Mediod Aligment (BVKMA) algorithm, which simultaneously clusters and aligns spatially dependent curves. It is a nonparametric statistical method that does not rely on distributional or dependency structure assumptions. The method is motivated by and applied to varved (annually laminated) sediment data from lake Kassjoen in northern Sweden, aiming to infer on past environmental and climate changes. The resulting clusters and their time dynamics show great potential for seasonal climate interpretation, in particular for winter climate changes.
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Authors who are presenting talks have a * after their name.
