María Angeles Gil

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One of the most important aspects of the (statistical) analysis of imprecise data is the usage of a suitable distance on the family of all compact, convex fuzzy sets, which is not too hard to calculate and which reflects the intuitive meaning of fuzzy sets. On the basis of expressing the metric of Bertoluzza et al. (1995) in terms of the mid points and(More)
The use of the fuzzy scale ofmeasurement to describe an important number of observations from real-life attributes or variables is first explored. In contrast to other well-known scales (like nominal or ordinal), a wide class of statistical measures and techniques can be properly applied to analyze fuzzy data. This fact is connected with the possibility of(More)
Consider the class of the mappings from a Euclidean space to the unit interval [0,1] (that is, the class of the fuzzy sets of this space) which are upper semicontinuous, the closure of their supports is compact, and the inverse images of the singleton {1} are nonempty sets. When the metric d~, which generalizes the Hausdorff metric, is defined on the(More)
Testing methods are introduced in order to determine whether there is some ‘linear’ relationship between imprecise predictor and response variables in a regression analysis. The variables are assumed to be interval-valued. Within this context, the variables are formalized as compact convex random sets, and an interval arithmetic-based linear model is(More)
The fuzzy rating method has been introduced in psychometric studies as a tool, which allows the capture of and accurate reflection of the diversity, subjectivity, and imprecision inherent in human responses to many questionnaires. The lack of statistical techniques for in-depth analysis of these responses has been, for years, the appearance of an important(More)