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What a Fuzzy Set Is and What It Is not? Read chapter Read first chapter

2018 | OriginalPaper | Chapter

Fuzzy Random Variables à la Kruse & Meyer and à la Puri & Ralescu: Key Differences and Coincidences

Author : María Ángeles Gil

Published in: Frontiers in Computational Intelligence

Publisher: Springer International Publishing

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Abstract

The concept of the so-called fuzzy random variables has been introduced in the literature aiming to model random mechanisms ‘producing’ fuzzy values. However, the best known approaches (namely, the one by Kwakernaak-Kruse and Meyer and the one by Féron-Puri and Ralescu) have been thought to deal with two different situations and, to a great extent, with two different probabilistic and statistical targets. This contribution highlights some of the most remarkable differences and coincidences between the two approaches.

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previous chapter What a Fuzzy Set Is and What It Is not?
next chapter Statistical Inference for Incomplete Ranking Data: A Comparison of Two Likelihood-Based Estimators
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Metadata
Title
Fuzzy Random Variables à la Kruse & Meyer and à la Puri & Ralescu: Key Differences and Coincidences
Author
María Ángeles Gil
Copyright Year
2018
Book
Frontiers in Computational Intelligence

Print ISBN: 978-3-319-67788-0

Electronic ISBN: 978-3-319-67789-7

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-67789-7_2

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