Modeling bivariate distributions with triangular fuzzy data and its application in hydrological studies: A copula-based approach

نویسندگان

1 Department of Statistics, Faculty of Mathematics and Computer, Shahid Bahonar University of Kerman, Kerman, Iran

2 عضو هییت علمی

3 Department of Statistics, Faculty of Mathematics ~and Computer Shahid Bahonar University of Kerman Kerman, Iran

doi
10.22111/ijfs.2026.51406.9082
چکیده

Fuzzy data analysis presents significant computational challenges due to its inherent ambiguity and uncertainty. Traditional statistical methods do not have the capability to effectively capture and model the uncertainty in fuzzy observations. A novel approach is proposed in this paper to model unknown bivariate densities using fuzzy observations and incorporating the dependency between variables. By employing this copula-based approach, we have effectivelymanaged the computational complexity associated with the analysis of fuzzy data. The proposed approach has been applied to model groundwater aquifers distribution.

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