Bivariate-Uniform Representations and Copula Approximations

In this paper, we present two different representations of the bivariate-uniform distribution and compare these to the Archimedean Copulas such as Clayton, Gumbel, and Frank. From this research, it is very clear that Gumbel Copula is a lot better than Frank and Clayton Copulas for approximating the Bivariate Uniform distribution.  

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Publication Details

Journal
International Journal of Statistics and Probability
Published
2025-06-28
DOI
https://doi.org/10.5539/ijsp.v14n2p21
Primary Topic
Neural Networks and Applications
Type
article
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article

Bivariate-Uniform Representations and Copula Approximations

A. Nanthakumar
International Journal of Statistics and Probability
Neural Networks and Applications
article

Bivariate-Uniform Representations and Copula Approximations

A. Nanthakumar
article en

Abstract

In this paper, we present two different representations of the bivariate-uniform distribution and compare these to the Archimedean Copulas such as Clayton, Gumbel, and Frank. From this research, it is very clear that Gumbel Copula is a lot better than Frank and Clayton Copulas for approximating the Bivariate Uniform distribution.  

International Journal of Statistics and ProbabilityVol. 14(2)
State University of New York at Oswego (US)
Openalex Percentile: Top 93%
Neural Networks and Applications
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Bivariate-Uniform Representations and Copula Approximations — A. Nanthakumar · International Journal of Statistics and Probability (2025) | TGRS Research Map | TGRS