Please use this identifier to cite or link to this item: http://arl.liuc.it/dspace/handle/2468/6717
Title: Dissimilarity measure for ranking data via copula
Authors: Osmetti, Silvia Angela
Bonanomi, Andrea
Nai Ruscone, Marta
Issue Date: 2019
Publisher: ECOSTA econometrics and statistics
Bibliographic citation: Osmetti Silvia Angela, Bonanomi Andrea, Nai Ruscone Marta (2019), Dissimilarity measure for ranking data via copula. In: CFE-CMStatistics 2019: 13th International Conference on Computational and Financial Econometrics (CFE 2019) and 12th International Conference of the ERCIM (European Research Consortium for Informatics and Mathematics) Working Group on Computational and Methodological Statistics (CMStatistics 2019), Senate House & Birkbeck University of London, UK, 14-16 December 2019: programme and abstracts. S.l.: ECOSTA econometrics and statistics, p. 46, article number E0804. ISBN 978-9963-2227-8-0.
Abstract: A new distance measure is defined for ranking data by using 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 Spearmans grade correlation coefficient on a transformation of the ranks denoting the levels of the importance assigned by subjects under classification to k objects. The copula is a flexible way to model different types of dependence structures in the data and to consider different situations in the classification process. For example, by using copulae with lower and upper tail dependence, we emphasize the agreement on extreme ranks, when they are considered more important.
URI: http://arl.liuc.it/dspace/handle/2468/6717
Journal/Book: CFE-CMStatistics 2019: 13th International Conference on Computational and Financial Econometrics (CFE 2019) and 12th International Conference of the ERCIM (European Research Consortium for Informatics and Mathematics) Working Group on Computational and Methodological Statistics (CMStatistics 2019), Senate House & Birkbeck University of London, UK, 14-16 December 2019: programme and abstracts
ISBN: 978-9963-2227-8-0
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