Bootstrapped tests for epistemic fuzzy data

• Autorzy: Grzegorzewski Przemyslaw , Romaniuk Maciej

Identyfikatory

DOI

10.61822/amcs-2024-0020

• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

bootstrap; fuzzy data; nonparametric statistics; statistical computing

PL

metoda bootstrap; dane rozmyte; obliczenia statystyczne

• Wydawca: Oficyna Wydawnicza Uniwersytetu Zielonogórskiego
• Czasopismo: International Journal of Applied Mathematics and Computer Science
• Rocznik: 2024
• Tom: Vol. 34, no. 2
• Strony: 277--289
• Opis fizyczny: Bibliogr. 35 poz., tab., wykr.

Twórcy

autor

Grzegorzewski Przemyslaw

• Faculty of Mathematics and Information Science, Warsaw University of Technology, Koszykowa 75, 00-662 Warsaw, Poland

autor

Romaniuk Maciej

• Systems Research Institute, Polish Academy of Sciences, Newelska 6, 01-447 Warsaw, Poland

Bibliografia

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Uwagi

PL

Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).