This paper generalizes the locally optimal linear rank test based on copula from Shirahata (1974) resp. Guillén and Isabel (1998) and Genest et al. (2006) to p dimensions and introduces a new X2-type test for global independence (Nelsen test). The test is compared to similar nonparametric tests...

It is well known that the arithmetic mean of two possibly different copulas forms a copula, again. More general, we focus on the weighted power mean (WPM) of two arbitrary copulas which is not necessary a copula again, as different counterexamples reveal. However, various conditions regarding...

It is well known that the arithmetic mean of two possibly different copulas forms a copula, again. More general, we focus on the weighted power mean (WPM) of two arbitrary copulas which is not necessary a copula again, as different counterexamples reveal. However, various conditions regarding...

Nonparametric prediction of time series is a viable alternative to parametric prediction, since parametric prediction relies on the correct specification of the process, its order and the distribution of the innovations. Often these are not known and have to be estimated from the data. Another...

This paper introduces a copula based multivariate rank test for independence extending existing approaches from literature to p dimensions. Then, a multiparametric p-dimensional generalization of the FGM copula is provided that can model the behavior in each vertex of the p-dimensional unit cube...