Three semiparametric methods for estimating dependence parameters in copula models are compared, namely maximum pseudo-likelihood estimation and the two method-of-moment approaches based on the inversion of Spearman's rho and Kendall's tau. For each of these three asymptotically normal...

The agglomerative hierarchical clustering of continuous variables is studied in the framework of the likelihood linkage analysis method proposed by Lerman. The similarity between variables is defined from the process comparing the empirical copula with the independence copula in the spirit of...

The copula-based modeling of multivariate distributions with continuous margins is presented as a succession of rank-based tests: a multivariate test of randomness followed by a test of mutual independence and a series of goodness-of-fit tests. All the tests under consideration are based on the...

A decomposition of the independence empirical copula process into a finite number of asymptotically independent sub-processes was studied by Deheuvels. Starting from this decomposition, Genest and Rmillard recently investigated tests of independence among random variables based on Cramr-von...