Statistical properties of convex clustering

  • Kean Ming Tan
  • , Daniela Witten

Research output: Contribution to journalArticlepeer-review

69 Scopus citations

Abstract

In this manuscript, we study the statistical properties of convex clustering. We establish that convex clustering is closely related to single linkage hierarchical clustering and k-means clustering. In addition, we derive the range of the tuning parameter for convex clustering that yields a non-trivial solution. We also provide an unbiased estimator of the degrees of freedom, and provide a finite sample bound for the prediction error for convex clustering. We compare convex clustering to some traditional clustering methods in simulation studies.

Original languageEnglish (US)
Pages (from-to)2324-2347
Number of pages24
JournalElectronic Journal of Statistics
Volume9
Issue number2
DOIs
StatePublished - Aug 19 2015

Bibliographical note

Publisher Copyright:
© 2015, Institute of Mathematical Statistics. All rights reserved.

Keywords

  • Degrees of freedom
  • Fusion penalty
  • Hierarchical clustering
  • K-means
  • Prediction error
  • Single linkage

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