International Journal of applied mathematics and computer science

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Paper details

Number 2 - June 2020
Volume 30 - 2020

Flexible resampling for fuzzy data

Przemyslaw Grzegorzewski, Olgierd Hryniewicz, Maciej Romaniuk

Abstract
In this paper, a new methodology for simulating bootstrap samples of fuzzy numbers is proposed. Unlike the classical bootstrap, it allows enriching a resampling scheme with values from outside the initial sample. Although a secondary sample may contain results beyond members of the primary set, they are generated smartly so that the crucial characteristics of the original observations remain invariant. Two methods for generating bootstrap samples preserving the representation (i.e., the value and the ambiguity or the expected value and the width) of fuzzy numbers belonging to the primary sample are suggested and numerically examined with respect to other approaches and various statistical properties.

Keywords
bootstrap, fuzzy data, fuzzy numbers, fuzzy sample, imprecise data, resampling

DOI
10.34768/amcs-2020-0022