Copula–based clustering methods

  • F. Marta L. Di Lascio
  • Fabrizio Durante
  • Roberta Pappadà
Conference paper

Abstract

We review some recent clustering methods based on copulas. Specifically, in the dissimilarity–based clustering framework, we describe and compare methods based on concordance or tail-dependence concept. An illustration is hence provided by using a time series dataset formed by the constituent data of the S&P 500 observed during the financial crisis of 2007-2008. Next, in the likelihood–based clustering framework, we present and discuss a clustering algorithm based on copula and called CoClust. Here, an application to the gene expression profiles of human tumour cell lines is provided to describe the methodology. Finally, a comparison between the two different approaches is performed through a case study on environmental data.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • F. Marta L. Di Lascio
    • 1
  • Fabrizio Durante
    • 2
  • Roberta Pappadà
    • 3
  1. 1.Faculty of Economics and ManagementFree University of Bozen-BolzanoBolzanoItaly
  2. 2.Dipartimento di Scienze dell’EconomiaUniversità del SalentoLecceItaly
  3. 3.Department of Economics, Business, Mathematics and Statistics “Bruno de Finetti”University of TriesteTriesteItaly

Personalised recommendations