Various measures of dependence of a new asymmetric generalized Farlie–Gumbel–Morgenstern copulas

References

• Amblard, C., Girard, S. (2009). A new extension of bivariate FGM copulas. Metrika 70:1–17.
   Web of Science ®Google Scholar
• Amini, M., Jabbari, H., Mohtashami Borzadaran, G.R. (2011). Aspects of dependence in generalized Farlie-Gumbel-Morgenstern distributions. Commun. Stat. Simul. Comput. 40:1192–1205.
   Web of Science ®Google Scholar
• Bairamov, I., Kotz, S. (2002). Dependence structure and symmetry of Huang-Kotz FGM distributions and their extensions. Metrika 56:55–72.
   Web of Science ®Google Scholar
• Balakrishnan, N., Lai, C.D. (2009). Continuous Bivariate Distributions ( 2nd ed.). New York: Springer.
   Google Scholar
• Bayramoglu, K., Bairamov, I. (2014). Baker-Lin-Huang type bivariate distributions based on order statistics. Commun. Stat. Theory Methods 43:1992–2006.
   Google Scholar
• Bekrizadeh, H., Parham, G.A., Zadkarmi, M.R. (2012). The new generalization of Farlie-Gumbel-Morgenstern copulas. Appl. Math. Sci. 6:3527–3533.
   Google Scholar
• Dette, H., Siburg, K.F., Stoimenov, P.A. (2013). A copula-based non-parametric measure of regression dependence. Scand. J. Stat. 40:21–41.
   Web of Science ®Google Scholar
• Drouet Mari, D., Kotz, S. (2001). Correlation and Dependence.London: Imperial College Press.
   Google Scholar
• Farlie, D.J. G. (1960). The performance of some correlation coefficients for a general bivariate distribution. Biometrika 47:307–323.
   Web of Science ®Google Scholar
• Genest, C., Plante, J.F. (2003). On Blest’s measure of rank correlation. Can. J. Stat. 31:35–52.
   Web of Science ®Google Scholar
• Ghalibaf, M.B., Eghbal, N., Amini, M., Azarnoosh, H.A., Bozorgnia, A. (2010). Aspects of dependence in Cuadras-Auge family. Commun. Stat. Theory Methods 39:2094–2107.
   Web of Science ®Google Scholar
• Gumbel, E.J. (1958). Statistics of Extremes. New York, NY: Columbia University Press.
   Google Scholar
• Gumbel, E.J. (1960). Bivariate exponential distributions. J. Am. Stat. Assoc. 55:698–707.
   Web of Science ®Google Scholar
• Gupta, R.D., Kundu, D. (1999). Generalized exponential distributions. Aust. N. Z. J. Stat. 41:173–188.
   Web of Science ®Google Scholar
• Huang, J.S., Kotz, S. (1984). Correlation structure in iterated Farlie-Gumbel-Morgenstern distributions. Biometrika 71:633–636.
   Web of Science ®Google Scholar
• Huang, J.S., Kotz, S. (1999). Modifications of the Farlie-Gumbel-Morgenstern distributions. A tough hill to climb. Metrika 49:135–145.
   Web of Science ®Google Scholar
• Johnson, N.L., Kotz, S. (1975). On some generalized Farlie-Gumbel-Morgenstern distributions. Commun. Stat. Theory Methods 4:415–427.
   Web of Science ®Google Scholar
• Johnson, N.L., Kotz, S. (1977). On some generalized Farlie-Gumbel-Morgenstern distributions – II: Regression, correlation and further generalizations. Commun. Stat. Theory Methods 6:485–496.
   Web of Science ®Google Scholar
• Kim, J.M., Sungur, E.A., Choi, T., Heo, T.Y. (2011). Generalized bivariate copulas and their properties. Model Assist. Stat. Appl. 6:127–136.
   Google Scholar
• Kochar, S.C., Gupta, R.P. (1987). Competitors of the Kendall-tau test for testing independence against positive quadrant dependence. Biometrika 74:664–669.
   Web of Science ®Google Scholar
• Lai, C.D., Xie, M. (2000). A new family of positive quadrant dependence bivariate distributions. Stat. Probab. Lett. 46:359–366.
   Web of Science ®Google Scholar
• Lin, G.D. (1987). Relationships between two extensions of Farlie-Gumbel-Morgenstern distribution. Ann. Inst. Stat. Math. 39:129–140.
   Web of Science ®Google Scholar
• Morgenstern, D. (1956). Einfache Beispiele zweidimensionaler Verteilungen. Mitt. Math. Stat. 8:234–235.
   Google Scholar
• Nelsen, R.B. (2006). An Introduction to Copulas (2nd ed.). New York, NY: Springer.
   Google Scholar
• Sklar, A. (1959). Fonctions de répartition à n dimensions et leurs marges. Publ. Inst. Stat. Univ. Paris 8:229–231.
   Google Scholar
• Sungur, E.A. (2005). Some observations on copula regression function. Commun. Stat. Theory Methods 34:1967–1978.
   Web of Science ®Google Scholar
• Siburg, K.F., Stoimenov, P.A. (2010). A measure of mutual complete dependence. Metrika 71:239–251.
   Web of Science ®Google Scholar
• Vellaisamy, P., Pathak, A.K. (2014). Copulas and regression models. J. Indian Stat. Assoc. 52:113–134.
   Google Scholar