Symmetry and dependence properties within a semiparametric family of bivariate copulas

symmetric generalized ruled submanifold of M is that R is locally mapped into itself by the geodesic reflection with respect to each ruling..

It is also expected that relaxing the assump- tions commonly applied to the vine copula in applications with high-dimensional dependency structures, such as independence between

Both plots are using monthly maximum of precipitation in Moscow and Kostroma to evaluate upper tail dependence coefficient using

The relation Eq.(49) is quite instructive in the zero range limit b → 0, for fixed non- zero scattering length a and atom numbers N σ : In this limit, the lattice filling factor

Johann Guilleminot and Christian Soize, On the statistical dependence for the components of random elasticity tensors exhibiting material symmetry properties, accepted for

We consider the estimation of the bivariate stable tail dependence function and propose a bias-corrected and robust estimator.. We establish its asymptotic behavior under

As in [25, Section 3.5] for the sine-G family, we focus our attention on a special member based on the inverse Weibull cdf for G(x), providing a new two parameter distribution

Then we use two real data sets set to compare TB, TW, TGa and TGz to TGE(transmuted generalized exponential distribution), TLE (Transmuted linear exponential distribution),