MIXTURE OF COPULAE BASED APPROACH FOR DEFINING THE SUBJECTS DISTANCE IN CLUSTER ANALYSIS

Andrea Bonanomi, Silvia Angela Osmetti, Marta Nai Ruscone

Risultato della ricerca: Contributo in libroContributo a convegno

Abstract

We define a new distance measure for ranking data by using a mixture of copula functions. This distance evaluates the dissimilarity between subjects expressing their preferences by rankings in order to segment them by hierarchical cluster analysis. The proposed distance builds upon the Spearman’s grade correlation coefficient on a transformation, operated by the copula function, of the rank denoting the leveloftheimportanceassignedbysubjectsunderclassificationtokobjects. Themixturesofcopulaeareaflexiblewaytomodeldifferenttypesofdependencestructuresin thedataandtoconsiderdifferentsituationsintheclassificationprocess. For example, by using mixtures of copulae with lower and upper tail dependence,we emphasize the agreement on extreme ranks, when extreme ranks are considered more important.
Lingua originaleEnglish
Titolo della pubblicazione ospiteCladag 2017 Book of Short Papers
Pagine1-4
Numero di pagine4
Stato di pubblicazionePubblicato - 2017
EventoCLADAG 2017 - Milano, Università di Milano Bicocca
Durata: 13 set 201715 set 2017

Convegno

ConvegnoCLADAG 2017
CittàMilano, Università di Milano Bicocca
Periodo13/9/1715/9/17

Keywords

  • copula
  • hierarchical cluster analysis
  • mixture of copulae
  • ranking data

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