Creator:

Grzegorzewski, Przemysław ; Romaniuk, Maciej

Contributor:

Witczak, Marcin - ed. ; Stetter, Ralf - ed.

Title:

Bootstrap methods for epistemic fuzzy data

Subtitle:

.

Group publication title:

AMCS, volume 32 (2022)

Subject and Keywords:

bootstrap ; estimation ; fuzzy data ; fuzzy numbers ; hypotheses testing ; resampling

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.

Publisher:

Zielona Góra: Uniwersytet Zielonogórski

Date:

2022

Resource Type:

artykuł

DOI:

10.34768/amcs-2022-0021

Pages:

285-297

Source:

AMCS, volume 32, number 2 (2022) ; click here to follow the link

Language:

eng

License CC BY 4.0:

click here to follow the link

Rights:

Biblioteka Uniwersytetu Zielonogórskiego