Biorder families, valued relations and preference modelling
Journal of Mathematical Psychology
Transitivity of fuzzy preference relations—an empirical study
Fuzzy Sets and Systems
General transitivity conditions for fuzzy reciprocal preference matrices
Fuzzy Sets and Systems - Special issue: Preference modelling and applications
Cycle-transitive comparison of independent random variables
Journal of Multivariate Analysis
An Introduction to Copulas (Springer Series in Statistics)
An Introduction to Copulas (Springer Series in Statistics)
On the transitivity of the comonotonic and countermonotonic comparison of random variables
Journal of Multivariate Analysis
On the transitivity of a parametric family of cardinality-based similarity measures
International Journal of Approximate Reasoning
Transitivity frameworks for reciprocal relations: cycle-transitivity versus FG-transitivity
Fuzzy Sets and Systems
Similarity relations and fuzzy orderings
Information Sciences: an International Journal
Kendall distribution functions and associative copulas
Fuzzy Sets and Systems
IEEE Transactions on Fuzzy Systems
Quasi-copulas and signed measures
Fuzzy Sets and Systems
On the cycle-transitivity of the mutual rank probability relation of a poset
Fuzzy Sets and Systems
An extension of stochastic dominance to fuzzy random variables
IPMU'10 Proceedings of the Computational intelligence for knowledge-based systems design, and 13th international conference on Information processing and management of uncertainty
On the ERA ranking representability of pairwise bipartite ranking functions
Artificial Intelligence
A study on the transitivity of probabilistic and fuzzy relations
Fuzzy Sets and Systems
The ordinal consistency of a fuzzy preference relation
Information Sciences: an International Journal
On a conjecture about the Frank copula family
Fuzzy Sets and Systems
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Given a collection of random variables, we build a probabilistic relation that, in the case of continuous random variables, expresses for each couple of random variables the probability that the first one takes a greater value than the second one. In order to compute this probability, the random variables are artificially coupled by means of a fixed commutative copula. The main result of this paper pertains to the transitivity of this probabilistic relation. Provided the commutative copula satisfies some additional condition, this transitivity can be described elegantly within the cycle-transitivity framework. It ranges between two known types of transitivity: T"L-transitivity and partial stochastic transitivity.