Creator:

Grzegorzewski, Przemysław ; Romaniuk, Maciej

Contributor:

Korbicz, Józef (1951- ) - red. ; Uciński, Dariusz - red.

Title:

Bootstrapped tests for epistemic fuzzy data

Group publication title:

AMCS, volume 34 (2024)

Subject and Keywords:

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

Abstract:

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.

Publisher:

Zielona Góra: Uniwersytet Zielonogórski

Date:

2024

Resource Type:

artykuł

DOI:

10.61822/amcs-2024-0020

Pages:

277-289

Source:

AMCS, volume 34, number 2 (2024) ; click here to follow the link

Language:

eng

License CC BY 4.0:

click here to follow the link

Rights:

Biblioteka Uniwersytetu Zielonogórskiego