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Clustering misaligned dependent curves applied to varved lake sediment for climate reconstruction

  • Konrad Abramowicz
  • Per Arnqvist
  • Piercesare Secchi
  • Sara Sjöstedt de Luna
  • Simone VantiniEmail author
  • Valeria Vitelli
Original Paper

Abstract

In this paper we introduce a novel functional clustering method, the Bagging Voronoi K-Medoid 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 Kassjön 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.

Keywords

Functional data Clustering Dependence Misalignment Sediment data 

Notes

Acknowledgments

The authors would like to thank Christian Bigler for valuable comments and discussions. This work was supported by the Swedish Research Council, project D0520301.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.Department of Mathematics and Mathematical StatisticsUmeå UniversityUmeåSweden
  2. 2.MOX - Department of MathematicsPolitecnico di MilanoMilanItaly
  3. 3.Department of Biostatistics, Oslo Center for Biostatistics and EpidemiologyUniversity of OsloOsloNorway

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