The extremal coefficients are the natural dependence measures for multivariate extreme value distributions. For an m-variate distribution 2m distinct extremal coefficients of different orders exist; they are closely linked and therefore a complete set of 2m coefficients cannot take any arbitrary values. We give a full characterization of all the sets of extremal coefficients. To this end, we introduce a simple class of extreme value distributions that allows for a 1-1 mapping to the complete sets of extremal coefficients. We construct bounds that higher order extremal coefficients need to satisfy to be consistent with lower order extremal coefficients. These bounds are useful as lower order extremal coefficients are the most easily inferred...
Extreme value theory provides an asymptotically justified framework for estimation of exceedance pro...
Many problems which involve applications of extreme value theory show an essential multivariate natu...
Multivariate extreme value distributions arise as the limiting joint distribution of normalized comp...
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...
For an m-dimensional multivariate extreme value distribution there exist 2m−1 exponent measures whic...
For an m-dimensional multivariate extreme value distribution there exist 2m−1 exponent measures whic...
Tail dependence is an important issue to evaluate risk. The multivariate extreme values theory is th...
The multivariate extremal index function is a direction specific extension of the well-known univari...
Let H be the limiting distribution of a vector of maxima from a d-dimensional stationary sequence wi...
Extreme value modeling has been attracting the attention of researchers in diverse areas such as th...
AbstractThe orthant tail dependence describes the relative deviation of upper- (or lower-) orthant t...
AbstractIn this work, we introduce the s,k-extremal coefficients for studying the tail dependence be...
In this work, we introduce the s, k-extremal coefficients for studying the tail dependence between ...
AbstractWe consider the multivariate Farlie–Gumbel–Morgenstern class of distributions and discuss th...
Extreme value theory provides an asymptotically justified framework for estimation of exceedance pro...
Many problems which involve applications of extreme value theory show an essential multivariate natu...
Multivariate extreme value distributions arise as the limiting joint distribution of normalized comp...
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...
For an m-dimensional multivariate extreme value distribution there exist 2m−1 exponent measures whic...
For an m-dimensional multivariate extreme value distribution there exist 2m−1 exponent measures whic...
Tail dependence is an important issue to evaluate risk. The multivariate extreme values theory is th...
The multivariate extremal index function is a direction specific extension of the well-known univari...
Let H be the limiting distribution of a vector of maxima from a d-dimensional stationary sequence wi...
Extreme value modeling has been attracting the attention of researchers in diverse areas such as th...
AbstractThe orthant tail dependence describes the relative deviation of upper- (or lower-) orthant t...
AbstractIn this work, we introduce the s,k-extremal coefficients for studying the tail dependence be...
In this work, we introduce the s, k-extremal coefficients for studying the tail dependence between ...
AbstractWe consider the multivariate Farlie–Gumbel–Morgenstern class of distributions and discuss th...
Extreme value theory provides an asymptotically justified framework for estimation of exceedance pro...
Many problems which involve applications of extreme value theory show an essential multivariate natu...
Multivariate extreme value distributions arise as the limiting joint distribution of normalized comp...