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Paper details
Number 2 - June 2022
Volume 32 - 2022
Bootstrap methods for epistemic fuzzy data
Przemysław Grzegorzewski, Maciej Romaniuk
Abstract
Fuzzy numbers are often used for modeling imprecise perceptions of the real-valued observations. Such epistemic fuzzy
data may cause problems in statistical reasoning and data analysis. We propose a universal nonparametric technique, called
the epistemic bootstrap, which could be helpful when the existing methods do not work or do not give satisfactory results.
Besides the simple epistemic bootstrap, we develop its several refinements that aim to reduce the variance in statistical
inference. We also perform an extended simulation study to examine statistical properties of the approaches considered.
The discussion of the results is supplemented by some hints for practical use.
Keywords
bootstrap, estimation, fuzzy data, fuzzy numbers, hypotheses testing, resampling