Copulas are functions that enable the construction of multivariate probability distributions by binding together univariate marginal distributions. Central to probability theory, they allow ...

MICHAEL FALK, SIMONE A. PADOAN, FLORIAN WISHECKEL, CONDITIONAL TAIL INDEPENDENCE IN ARCHIMEDEAN COPULA MODELS, Journal of Applied Probability, Vol. 56, No. 3 (SEPTEMBER 2019), pp. 858-869 ...

Principles of Copula Theory explores the state of the art on copulas and provides you with the foundation to use copulas in a variety of applications. Throughout the book, historical remarks and ...

Journal of Coastal Research, SPECIAL ISSUE NO. 103. Global Topics and New Trends in Coastal Research: Port, Coastal and Ocean Engineering (SUMMER 2020), pp. 839-842 (4 pages) In order to improve the ...

We propose a novel approach for the computation of the probability distribution of a counting variable linked to a particular kind of hierarchical multivariate copula function called a clusterized ...