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A General Partition Cluster Algorithm

In: COMPSTAT 2004 — Proceedings in Computational Statistics

Author

Listed:
  • Daniel Peña

    (Universidad Carlos III de Madrid, Departamento de Estadística)

  • Julio Rodríguez

    (Universidad Politécnica de Madrid, Laboratorio de Estadística)

  • George C. Tiao

    (University of Chicago, Graduate School of Business)

Abstract

A new cluster algorithm based on the SAR procedure proposed by Peña and Tiao [9] is presented. The method splits the data into more homogeneous groups by putting together observations which have the same sensitivity to the deletion of extreme points in the sample. As the sample is always split by this method the second stage is to check if observations outside each group can be recombined one by one into the groups by using the distance implied by the model. The performance of this algorithm is compared to some well known cluster methods.

Suggested Citation

  • Daniel Peña & Julio Rodríguez & George C. Tiao, 2004. "A General Partition Cluster Algorithm," Springer Books, in: Jaromir Antoch (ed.), COMPSTAT 2004 — Proceedings in Computational Statistics, pages 371-379, Springer.
    • Handle: RePEc:spr:sprchp:978-3-7908-2656-2_30
    DOI: 10.1007/978-3-7908-2656-2_30
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