Abstract
The comparison of random variables can be made by means of stochastic orders such as expected utility or statistical preference. One possible model when the random variables are imprecisely observed is to consider fuzzy random variables, so that the images become fuzzy sets. This paper proposes two comparison methods for fuzzy random variables: one based on fuzzy rankings and another one that uses the extensions of stochastic orders to an imprecise framework. The particular case where the images of the fuzzy random variables are triangular fuzzy numbers is investigated.We illustrate our results by means of a decision making problem.
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Montes, I., Miranda, E., Montes, S. (2015). Stochastic Orders for Fuzzy Random Variables. In: Grzegorzewski, P., Gagolewski, M., Hryniewicz, O., Gil, M. (eds) Strengthening Links Between Data Analysis and Soft Computing. Advances in Intelligent Systems and Computing, vol 315. Springer, Cham. https://doi.org/10.1007/978-3-319-10765-3_3
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DOI: https://doi.org/10.1007/978-3-319-10765-3_3
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-10764-6
Online ISBN: 978-3-319-10765-3
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