The mean value of a fuzzy number
Fuzzy Sets and Systems - Fuzzy Numbers
Fundamentals of Uncertainty Calculi with Applications to Fuzzy Inference
Fundamentals of Uncertainty Calculi with Applications to Fuzzy Inference
Uncertainty Models for Knowledge-Based Systems; A Unified Approach to the Measurement of Uncertainty
Uncertainty Models for Knowledge-Based Systems; A Unified Approach to the Measurement of Uncertainty
A random set characterization of possibility measures
Information Sciences—Informatics and Computer Science: An International Journal
Higher order models for fuzzy random variables
Fuzzy Sets and Systems
Nonspecificity for infinite random sets of indexable type
Fuzzy Sets and Systems
Some properties of a random set approximation to upper and lower distribution functions
International Journal of Approximate Reasoning
Pricing a contingent claim with random interval or fuzzy random payoff in one-period setting
Computers & Mathematics with Applications
Fuzzy Sets and Systems
Upper Probabilities Attainable by Distributions of Measurable Selections
ECSQARU '09 Proceedings of the 10th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Approximations of upper and lower probabilities by measurable selections
Information Sciences: an International Journal
On the variability of the concept of variance for fuzzy random variables
IEEE Transactions on Fuzzy Systems
Upper and lower probabilities induced by a fuzzy random variable
Fuzzy Sets and Systems
Upper and lower probabilities induced by a fuzzy random variable
Fuzzy Sets and Systems
Mark-recapture techniques in statistical tests for imprecise data
International Journal of Approximate Reasoning
Consonant random sets: structure and properties
ECSQARU'05 Proceedings of the 8th European conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Pricing and hedging in a single period market with random interval valued assets
International Journal of Approximate Reasoning
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Random intervals constitute one of the classes of random sets with a greater number of applications. In this paper, we regard them as the imprecise observation of a random variable, and study how to model the information about the probability distribution of this random variable. Two possible models are the probability distributions of the measurable selections and those bounded by the upper probability. We prove that, under some hypotheses, the closures of these two sets in the topology of the weak convergence coincide, improving results from the literature. Moreover, we provide examples showing that the two models are not equivalent in general, and give sufficient conditions for the equality between them. Finally, we comment on the relationship between random intervals and fuzzy numbers.