International Journal of Applied Mathematics and Computer Science (Jun 2020)

Flexible resampling for fuzzy data

  • Grzegorzewski Przemyslaw,
  • Hryniewicz Olgierd,
  • Romaniuk Maciej

DOI
https://doi.org/10.34768/amcs-2020-0022
Journal volume & issue
Vol. 30, no. 2
pp. 281 – 297

Abstract

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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