International Journal of applied mathematics and computer science

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Paper details

Number 2 - June 2024
Volume 34 - 2024

Bootstrapped tests for epistemic fuzzy data

Przemysław Grzegorzewski, Maciej Romaniuk

Epistemic bootstrap is a resampling algorithm that generates bootstrap real-valued samples based on some epistemic fuzzy data input. We apply this method as a universal basis for various statistical tests which can be then directly used for fuzzy random variables. Two classical goodness-of-fit tests are considered as an example to examine the suggested methodology for both synthetic and real data. The proposed approach is also compared with two other goodness-of-fit tests dedicated directly to fuzzy data.

bootstrap, fuzzy data, nonparametric statistics, simulation, statistical computing