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On a fuzzy discretization of continuous distributions with applications to risk models

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Abstract

The discretization of a continuous distribution is an important and challenging step in problems emerging from different fields, like, e.g., finance and insurance. The usual discretization methods come along with some information loss. With the purpose to capture more information by covering the entire support of the original distribution while keeping the discrete characteristic, in this paper, we propose a fuzzy alternative discretization method that—in terms of random variables—replaces a discretized random variable with a discrete triangular fuzzy random variable. As applications, we insert this discrete triangular fuzzy random variable in two classical risk models and study the results.

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Acknowledgements

The author is very grateful to the referee for the valuable comments that helped to significantly improve the paper.

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  1. Faculty of Mathematics and Computer Science, Ovidius University of Constanta, 124 Mamaia Blvd., 900527, Constanta, Romania

    Raluca Vernic

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  1. Raluca Vernic
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Correspondence to Raluca Vernic.

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Communicated by Leonardo Tomazeli Duarte.

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Vernic, R. On a fuzzy discretization of continuous distributions with applications to risk models. Comp. Appl. Math. 42, 61 (2023). https://doi.org/10.1007/s40314-023-02190-4

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  • DOI: https://doi.org/10.1007/s40314-023-02190-4

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