Copula-Based Non-Metric Unfolding on Augmented Data Matrix

Marta Nai Ruscone (), Daniel Fernández () and Antonio D’Ambrosio ()
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Marta Nai Ruscone: University of Genoa
Daniel Fernández: Universitat Politècnica de Catalunya, BarcelonaTech (UPC)
Antonio D’Ambrosio: University of Naples Federico II

Journal of Classification, 2024, vol. 41, issue 3, No 12, 678-697

Abstract: Abstract A multidimensional unfolding technique that is not prone to degenerate solutions and is based on multidimensional scaling of a complete data matrix is proposed. We adopt the strategy of augmenting the data matrix, trying to build a complete dissimilarity matrix, by using copula-based association measures among rankings (the individuals), and between rankings and objects (namely, a rank-order representation of the objects through tied rankings). The proposed technique leads to acceptable recovery of given preference structures.

Keywords: Copula; Multidimensional scaling; Unfolding (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s00357-024-09495-x

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