Multivariate extreme models based on underlying skew-t and skew-normal distributions
We derive for the first time the limiting distribution of maxima of skew-t random vectors and we show that its limiting case, as the degree of freedom goes to infinity, is the skewed version of the well-known FlOsler-Reiss model. The advantage of the new families of models is that they are particularly flexible, allowing for both symmetric and asymmetric dependence structures and permitting the modelling of multivariate extremes with dimensions greater than two. (C) 2011 Elsevier Inc. All rights reserved.
Keywords: Extreme values ; Extreme copulas ; Max-stable distribution ; Pickands dependence function ; Skew-normal distribution ; Skew-t distribution ; Spatial extremes ; Tail dependence function ; Nonparametric-Estimation ; Dependence ; Independence ; Statistics ; Inference ; Copulas ; Values
Record created on 2011-12-16, modified on 2016-08-09