The l&ar; -mean squared dispersion associated with a fuzzy random variable
Fuzzy Sets and Systems
On the formalization of fuzzy random variables
Information Sciences: an International Journal - Fuzzy random variables
Two-sample hypothesis tests of means of a fuzzy random variable
Information Sciences: an International Journal - Fuzzy random variables
Triangular fuzzification of random variables and power of distribution tests: Empirical discussion
Computational Statistics & Data Analysis
Editorial: Statistics for Functional Data
Computational Statistics & Data Analysis
Additive prediction and boosting for functional data
Computational Statistics & Data Analysis
Generalized profiling estimation for global and adaptive penalized spline smoothing
Computational Statistics & Data Analysis
Information Sciences: an International Journal
On the use of the bootstrap for estimating functions with functional data
Computational Statistics & Data Analysis
Bootstrap approach to the multi-sample test of means with imprecise data
Computational Statistics & Data Analysis
Computational Statistics & Data Analysis
Editorial: Special issue on fuzzy sets in statistics
Computational Statistics & Data Analysis
K-sample tests for equality of variances of random fuzzy sets
Computational Statistics & Data Analysis
Generalized Bayesian inference in a fuzzy context: From theory to a virtual reality application
Computational Statistics & Data Analysis
Information Sciences: an International Journal
A decomposition theorem for fuzzy set-valued random variables
Fuzzy Sets and Systems
A method based on shape-similarity for detecting similar opinions in group decision-making
Information Sciences: an International Journal
Bootstrap confidence sets for the Aumann mean of a random closed set
Computational Statistics & Data Analysis
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The use of the fuzzy scale of measurement 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 identifying the scale with a special subset of a functional Hilbert space. The identification can be used to develop methods for the statistical analysis of fuzzy data by considering techniques in functional data analysis and vice versa. In this respect, an approach to the FANOVA test is presented and analyzed, and it is later particularized to deal with fuzzy data. The proposed approaches are illustrated by means of a real-life case study.