Biorder families, valued relations and preference modelling
Journal of Mathematical Psychology
Cycle-transitive comparison of independent random variables
Journal of Multivariate Analysis
Transitivity frameworks for reciprocal relations: cycle-transitivity versus FG-transitivity
Fuzzy Sets and Systems
On the cycle-transitive comparison of artificially coupled random variables
International Journal of Approximate Reasoning
IEEE Transactions on Fuzzy Systems
On the cycle-transitivity of the mutual rank probability relation of a poset
Fuzzy Sets and Systems
A transitivity analysis of bipartite rankings in pairwise multi-class classification
Information Sciences: an International Journal
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 quest for transitivity, a showcase of fuzzy relational calculus
WCCI'12 Proceedings of the 2012 World Congress conference on Advances in Computational Intelligence
On a conjecture about the Frank copula family
Fuzzy Sets and Systems
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A recently proposed method for the pairwise comparison of arbitrary independent random variables results in a probabilistic relation. When restricted to discrete random variables uniformly distributed on finite multisets of numbers, this probabilistic relation expresses the winning probabilities between pairs of hypothetical dice that carry these numbers and exhibits a particular type of transitivity called dice-transitivity. In case these multisets have equal cardinality, two alternative methods for statistically comparing the ordered lists of the numbers on the faces of the dice have been studied recently: the comonotonic method based upon the comparison of the numbers of the same rank when the lists are in increasing order, and the countermonotonic method, also based upon the comparison of only numbers of the same rank but with the lists in opposite order. In terms of the discrete random variables associated to these lists, these methods each turn out to be related to a particular copula that joins the marginal cumulative distribution functions into a bivariate cumulative distribution function. The transitivity of the generated probabilistic relation has been completely characterized. In this paper, the list comparison methods are generalized for the purpose of comparing arbitrary random variables. The transitivity properties derived in the case of discrete uniform random variables are shown to be generic. Additionally, it is shown that for a collection of normal random variables, both comparison methods lead to a probabilistic relation that is at least moderately stochastic transitive.