AbstractWe consider the multivariate Farlie–Gumbel–Morgenstern class of distributions and discuss their properties with respect to the extreme values. This class was used to consider dependence in multivariate distributions and their ordering. We show that the extreme values of these distributions behave as if no dependence would exist between its components
For an m-dimensional multivariate extreme value distribution there exist 2m−1 exponent measures whic...
In this paper, we explore tail dependence modelling in multivariate extreme value distributions. The...
Many problems which involve applications of extreme value theory show an essential multivariate natu...
We consider the multivariate Farlie-Gumbel-Morgenstern class of distributions and discuss their prop...
AbstractWe consider the multivariate Farlie–Gumbel–Morgenstern class of distributions and discuss th...
AbstractAny multivariate distribution can occur as the limit of extreme values in a sequence of inde...
The limit distributions of multivariate extreme values of stationary random sequences are associated...
Abstract. The set of dependent random variables with multivariate Farlie-Gumbel-Morgenstern (FGM) di...
The extremal coefficients are the natural dependence measures for multivariate extreme value distrib...
The extremal coefficients are the natural dependence measures for multivariate extreme value distrib...
Let H be the limiting distribution of a vector of maxima from a d-dimensional stationary sequence wi...
AbstractThe orthant tail dependence describes the relative deviation of upper- (or lower-) orthant t...
The set of the functions H, which are limiting distributions of linearly normalized maxima of n inde...
For an m-dimensional multivariate extreme value distribution there exist 2m−1 exponent measures whic...
AbstractA distributional mixing condition is introduced for stationary sequences of random vectors t...
For an m-dimensional multivariate extreme value distribution there exist 2m−1 exponent measures whic...
In this paper, we explore tail dependence modelling in multivariate extreme value distributions. The...
Many problems which involve applications of extreme value theory show an essential multivariate natu...
We consider the multivariate Farlie-Gumbel-Morgenstern class of distributions and discuss their prop...
AbstractWe consider the multivariate Farlie–Gumbel–Morgenstern class of distributions and discuss th...
AbstractAny multivariate distribution can occur as the limit of extreme values in a sequence of inde...
The limit distributions of multivariate extreme values of stationary random sequences are associated...
Abstract. The set of dependent random variables with multivariate Farlie-Gumbel-Morgenstern (FGM) di...
The extremal coefficients are the natural dependence measures for multivariate extreme value distrib...
The extremal coefficients are the natural dependence measures for multivariate extreme value distrib...
Let H be the limiting distribution of a vector of maxima from a d-dimensional stationary sequence wi...
AbstractThe orthant tail dependence describes the relative deviation of upper- (or lower-) orthant t...
The set of the functions H, which are limiting distributions of linearly normalized maxima of n inde...
For an m-dimensional multivariate extreme value distribution there exist 2m−1 exponent measures whic...
AbstractA distributional mixing condition is introduced for stationary sequences of random vectors t...
For an m-dimensional multivariate extreme value distribution there exist 2m−1 exponent measures whic...
In this paper, we explore tail dependence modelling in multivariate extreme value distributions. The...
Many problems which involve applications of extreme value theory show an essential multivariate natu...
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