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A Class of Copulas Derived from Residual Implications and Its Applications

DOI: 10.4236/ojs.2025.152008, PP. 129-149

Keywords: Copula, Residual Implication, Archimedean Copulas, Dependence Measures

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Abstract:

Copulas are multivariate distribution functions with uniform marginal distributions. In this paper, we study a class of copulas called radial copulas, which is derived from residual implications where the extensions of level curves intersect at a point. This class of radial copulas is a comprehensive and asymmetric extension of a class of Archimedean copulas. We derive analytical formulas for key concordance measures, including Spearman’s rho and Kendall’s tau, and demonstrate that these formulas cover the entire range of positive and negative correlations. Furthermore, we estimate the parameters of radial copulas and evaluate their performance through a simulation study under various dependence structures. Finally, using two datasets, we compare the performance of the class of radial copulas to that of several well-known copula models.

References

[1]  Sklar, A. (1959) Fonctions de répartition à n dimensions et leurs marges. Annales de lISUP, 8, 229-231.
https://hal.science/hal-04094463v1
[2]  Bouyé, E., Durrleman, V., Nikeghbali, A., Riboulet, G. and Roncalli, T. (2000) Copulas for Finance—A Reading Guide and Some Applications. SSRN Electronic Journal.
https://doi.org/10.2139/ssrn.1032533
[3]  Patton, A.J. (2012) A Review of Copula Models for Economic Time Series. Journal of Multivariate Analysis, 110, 4-18.
https://doi.org/10.1016/j.jmva.2012.02.021
[4]  Kumar, P. (2018) Copula Functions and Applications in Engineering. In: Deep, K., Jain, M. and Salhi, S., Eds., Logistics, Supply Chain and Financial Predictive Analytics, Springer, 195-209.
https://doi.org/10.1007/978-981-13-0872-7_15
[5]  Oppenheimer, M., Little, C.M. and Cooke, R.M. (2016) Expert Judgement and Uncertainty Quantification for Climate Change. Nature Climate Change, 6, 445-451.
https://doi.org/10.1038/nclimate2959
[6]  Baczyński, M. and Beliakov, G. and Sola, H. B. and Pradera, (2013) Advances in Fuzzy Implication Functions. Springer.
https://doi.org/10.1007/978-3-642-35677-3
[7]  Mas, M., Monserrat, M., Torrens, J. and Trillas, E. (2007) A Survey on Fuzzy Implication Functions. IEEE Transactions on Fuzzy Systems, 15, 1107-1121.
https://doi.org/10.1109/tfuzz.2007.896304
[8]  Bassan, B. and Spizzichino, F. (2005) Relations among Univariate Aging, Bivariate Aging and Dependence for Exchangeable Lifetimes. Journal of Multivariate Analysis, 93, 313-339.
https://doi.org/10.1016/j.jmva.2004.04.002
[9]  Demirli, K. and Baets, B.D. (1999) Basic Properties of Implicators in a Residual Framework, Tatra Mountains Mathematical Publications, 16, 31-46.
[10]  Zhang, X., Sheng, N. and Borzooei, R.A. (2023) Partial Residuated Implications Induced by Partial Triangular Norms and Partial Residuated Lattices. Axioms, 12, Article 63.
https://doi.org/10.3390/axioms12010063
[11]  Baczyński, M. and Jayaram, B. (2008) (S, N)-and R-Implications: A State-of-the-Art Survey. Fuzzy Sets and Systems, 159, 1836-1859.
https://doi.org/10.1016/j.fss.2007.11.015
[12]  Ouyang, Y. (2012) On Fuzzy Implications Determined by Aggregation Operators. Information Sciences, 193, 153-162.
https://doi.org/10.1016/j.ins.2012.01.001
[13]  Zhou, H. (2021) Characterizations of Fuzzy Implications Generated by Continuous Multiplicative Generators of t-norms. IEEE Transactions on Fuzzy Systems, 29, 2988-3002.
https://doi.org/10.1109/tfuzz.2020.3010616
[14]  Baczyński, M. (2004) Residual Implications Revisited. Notes on the Smets-Magrez Theorem. Fuzzy Sets and Systems, 145, 267-277.
https://doi.org/10.1016/s0165-0114(03)00245-8
[15]  Aguiló, I., Suñer, J. and Torrens, J. (2010) A Characterization of Residual Implications Derived from Left-Continuous Uninorms. Information Sciences, 180, 3992-4005.
https://doi.org/10.1016/j.ins.2010.06.023
[16]  Grzegorzewski, P. (2013) Probabilistic Implications. Fuzzy Sets and Systems, 226, 53-66.
https://doi.org/10.1016/j.fss.2013.01.003
[17]  Baczyński, M., Grzegorzewski, P., Mesiar, R., Helbin, P. and Niemyska, W. (2017) Fuzzy Implications Based on Semicopulas. Fuzzy Sets and Systems, 323, 138-151.
https://doi.org/10.1016/j.fss.2016.09.009
[18]  Massanet, S., Pradera, A., Ruiz-Aguilera, D. and Torrens, J. (2017) From Three to One: Equivalence and Characterization of Material Implications Derived from Co-Copulas, Probabilistic S-Implications and Survival S-Implications. Fuzzy Sets and Systems, 323, 103-116.
https://doi.org/10.1016/j.fss.2017.01.002
[19]  Durante, F., Klement, E.P., Mesiar, R. and Sempi, C. (2007) Conjunctors and Their Residual Implicators: Characterizations and Construction Methods. Mediterranean Journal of Mathematics, 4, 343-356.
https://doi.org/10.1007/s00009-007-0122-1
[20]  Ji, W. and Xie, J. (2023) Characterizations of Residual Implications Derived from Copulas. IEEE Transactions on Fuzzy Systems, 31, 1409-1415.
https://doi.org/10.1109/tfuzz.2022.3197902
[21]  Durante, F. and Sempi, C. (2005) Semicopulæ. Kybernetika, 41, 315-328.
[22]  Genest, C., Quesada Molina, J.J., Rodrı́guez Lallena, J.A. and Sempi, C. (1999) A Characterization of Quasi-Copulas. Journal of Multivariate Analysis, 69, 193-205.
https://doi.org/10.1006/jmva.1998.1809
[23]  Nelsen, R.B. (2006) An Introduction to Copulas. 2nd Edition, Springer.
https://doi.org/10.1007/0-387-28678-0
[24]  Tsukahara, H. (2005) Semiparametric Estimation in Copula Models. Canadian Journal of Statistics, 33, 357-375.
https://doi.org/10.1002/cjs.5540330304
[25]  Brahimi, B., Chebana, F. and Necir, A. (2014) Copula Representation of Bivariate L-Moments: A New Estimation Method for Multiparameter Two-Dimensional Copula Models. Statistics, 49, 497-521.
https://doi.org/10.1080/02331888.2014.932792
[26]  Hosking, J.R.M. (1990) L-Moments: Analysis and Estimation of Distributions Using Linear Combinations of Order Statistics. Journal of the Royal Statistical Society Series B: Statistical Methodology, 52, 105-124.
https://doi.org/10.1111/j.2517-6161.1990.tb01775.x
[27]  Chang, R.Y. and Wang, M.L. (1983) Shifted Legendre Direct Method for Variational Problems. Journal of Optimization Theory and Applications, 39, 299-307.
https://doi.org/10.1007/bf00934535
[28]  Serfling, R. and Xiao, P. (2007) A Contribution to Multivariate L-Moments: L-Comoment Matrices. Journal of Multivariate Analysis, 98, 1765-1781.
[29]  Chambers, J.M., Cleveland, W.S., Kleiner, B. and Tukey, P.A. (1983) Graphical Methods for Data Analysis. Taylor & Francis.
https://doi.org/10.1201/9781351072304
[30]  Genest, C., Rémillard, B. and Beaudoin, D. (2009) Goodness-of-Fit Tests for Copulas: A Review and a Power Study. Insurance: Mathematics and Economics, 44, 199-213.
https://doi.org/10.1016/j.insmatheco.2007.10.005
[31]  Ghosh, S., Bhuyan, P. and Finkelstein, M. (2022) On a Bivariate Copula for Modeling Negative Dependence: Application to New York Air Quality Data. Statistical Methods & Applications, 31, 1329-1353.
https://doi.org/10.1007/s10260-022-00636-3
[32]  El Ktaibi, F.E., Bentoumi, R., Sottocornola, N. and Mesfioui, M. (2022) Bivariate Copulas Based on Counter-Monotonic Shock Method. Risks, 10, Article 202.
https://doi.org/10.3390/risks10110202
[33]  Ashenfelter, O. and Krueger, A. (1994) Estimates of the Economic Return to Schooling from a New Sample of Twins. The American Economic Review, 84, 1157-1173.
https://doi.org/10.3386/W4143
[34]  Tang, C., Wang, D., El Barmi, H. and Tebbs, J.M. (2019) Testing for Positive Quadrant Dependence. The American Statistician, 75, 23-30.
https://doi.org/10.1080/00031305.2019.1607554
[35]  Najjari, V., Bacigál, T. and Bal, H. (2014) An Archimedean Copula Family with Hyperbolic Cotangent Generator. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 22, 761-768.
https://doi.org/10.1142/s0218488514500391
[36]  Esfahani, M., Amini, M., Mohtashami-Borzadaran, G.R. and Dolati, A. (2023) A New Copula-Based Bivariate Gompertz-Makeham Model and Its Application to COVID-19 Mortality Data. Iranian Journal of Fuzzy Systems, 20, 159-175.
https://doi.org/10.22111/ijfs.2023.7645

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