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Bootstrap methods for epistemic fuzzy data

Grzegorzewski Przemyslaw, Romaniuk Maciej

International Journal of Applied Mathematics and Computer Science

2022

Vol. 32, no. 2

285--297

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.

Computing With Words and Life Data

Grzegorzewski P., Hryniewicz O

International Journal of Applied Mathematics and Computer Science

2002

Vol. 12, no 3

337-345

The problem of statistical inference on the mean lifetime in the presence of vague data is considered. Situations with fuzzy lifetimes and an imprecise number of failures are discussed.