Joint Proceedings of the 19th World Congress of the International Fuzzy Systems Association (IFSA), the 12th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT), and the 11th International Summer School on Aggregation Operators (AGOP)

Epistemic Bootstrap for Fuzzy Data

Authors
Przemysław Grzegorzewski, Maciej Romaniuk
Corresponding Author
Przemysław Grzegorzewski
Available Online 30 August 2021.
DOI
https://doi.org/10.2991/asum.k.210827.071How to use a DOI?
Keywords
Bootstrap, Estimation, Fuzzy data, Fuzzy numbers, Fuzzy EM, Hypotheses testing
Abstract

Fuzzy data applied for modeling imprecise observations cause many problems in statistical reasoning and data analysis. To handle better such observations a new bootstrap technique designed for epistemic fuzzy data is proposed. Our new method is conceptually simple and is not hard computationally. Some simulation results reported in the paper show that the proposed new type of the bootstrap may increase the effectiveness of statistical inferential procedures used so far. Although these results are rather preliminary, they indicate that the epistemic bootstrap might be useful in different fields which is a good prognostic for further research.

Copyright
© 2021, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Cite this article

TY  - CONF
AU  - Przemysław Grzegorzewski
AU  - Maciej Romaniuk
PY  - 2021
DA  - 2021/08/30
TI  - Epistemic Bootstrap for Fuzzy Data
BT  - Joint Proceedings of the 19th World Congress of the International Fuzzy Systems Association (IFSA), the 12th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT), and the 11th International Summer School on Aggregation Operators (AGOP)
PB  - Atlantis Press
SP  - 538
EP  - 545
SN  - 2589-6644
UR  - https://doi.org/10.2991/asum.k.210827.071
DO  - https://doi.org/10.2991/asum.k.210827.071
ID  - Grzegorzewski2021
ER  -