Fuzzy Confidence Intervals for Mean of Fuzzy Random Variables

Dominated Convergence for Fuzzy Random Variables

SOME PROBABILISTIC INEQUALITIES FOR FUZZY RANDOM VARIABLES

In this paper, the concepts of positive dependence and linearlypositive quadrant dependence are introduced for fuzzy random variables. Also,an inequality is obtained for partial sums of linearly positive quadrant depen-dent fuzzy random variables. Moreover, a weak law of large numbers is estab-lished for linearly positive quadrant dependent fuzzy random variables. Weextend some well known inequ...

Confidence Regions for the Mean of a Fuzzy Random Variable

The aim of this paper is to extend the classical problem of confidence interval estimation for the mean of a random variable to the case of a fuzzy random variable. The key idea consists in considering a confidence region defined as a ball w.r.t. a given metric, which is centered in the sample mean and whose radius is determined via bootstrapping. The developed approach is illustrated both by m...

Computing the Mean Chance Distributions of Fuzzy Random Variables∗

Fuzzy random variable is a combination of fuzzy variable and random variable, and can characterize both fuzziness and randomness in the real world. The mean chance of a fuzzy random event is an important concept in fuzzy random optimization, just like the probability of a stochastic event in stochastic optimization and the credibility of a fuzzy event in fuzzy optimization. In fuzzy random prog...

Fuzzy Random Variables

Fuzziness is discussed in the context of multivalued lo&, and a corresponding view of fuzzy sets is given. Fuzzy random variables are introduced as random variables whose values are not real but fuzzy numbers, and subsequently redefined as a particular kind of fuzzy set. Expectations of fuzzy random variables, characteristic f~cti~ of fuzzy events, probabilities connected to fuzzy random variab...

Fuzzy Random Variables*

In practice we are often faced with random experiments whose outcomes are not numbers (or vectors in &I”) but are expressed in inexact linguistic terms. As an example, consider a group of individuals chosen at random who are questioned about the weather on a particular city on a particular winter day. Some possible answers would be “cold,” “more or less cold,” “very cold,” “ extremely cold,” an...