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Authors: Rédina Berkachy and Laurent Donzé

Affiliation: Applied Statistics and Modelling, Department of Informatics, Faculty of Management, Economics and Social Sciences, University of Fribourg, Boulevard de Pérolles 90, 1700 Fribourg, Switzerland

Keyword(s): Bootstrap Technique, Likelihood Ratio, Fuzzy Confidence Interval, Fuzzy Statistics, Fuzzy Hypotheses, Fuzzy Data.

Abstract: We propose a complete practical procedure to construct a fuzzy confidence interval by the likelihood method where the observations and the hypotheses are considered to be fuzzy. We use the bootstrap technique to estimate the distribution of the likelihood ratio. For this step of the process, we mainly expose two algorithms: the first one consists on simply randomly drawing the bootstrap samples, and the second one is based on drawing observations by preserving the location and dispersion measures of the primary data set. This is achieved in accordance with a new metric written as dθ? SGD. It is built on the basis of the known signed distance measure. We also provide a simulation study to measure the performance of both bootstrap algorithms and their influence on the constructed confidence intervals. We illustrate our method via a numerical application where we construct fuzzy confidence intervals by the traditional and the defended methods. The aim is to highlight important differenc es between them. (More)

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Paper citation in several formats:
Berkachy, R. and Donzé, L. (2020). Fuzzy Confidence Intervals by the Likelihood Ratio with Bootstrapped Distribution. In Proceedings of the 12th International Joint Conference on Computational Intelligence (IJCCI 2020) - FCTA; ISBN 978-989-758-475-6; ISSN 2184-3236, SciTePress, pages 231-242. DOI: 10.5220/0010023602310242

@conference{fcta20,
author={Rédina Berkachy. and Laurent Donzé.},
title={Fuzzy Confidence Intervals by the Likelihood Ratio with Bootstrapped Distribution},
booktitle={Proceedings of the 12th International Joint Conference on Computational Intelligence (IJCCI 2020) - FCTA},
year={2020},
pages={231-242},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010023602310242},
isbn={978-989-758-475-6},
issn={2184-3236},
}

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Computational Intelligence (IJCCI 2020) - FCTA
TI - Fuzzy Confidence Intervals by the Likelihood Ratio with Bootstrapped Distribution
SN - 978-989-758-475-6
IS - 2184-3236
AU - Berkachy, R.
AU - Donzé, L.
PY - 2020
SP - 231
EP - 242
DO - 10.5220/0010023602310242
PB - SciTePress

- Science and Technology Publications, Lda.
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