Generalized Logistic Model and Its Orthant Tail Dependence
نویسندگان
چکیده
The Multivariate Extreme Value distributions have shown their usefulness in environmental studies, financial and insurance mathematics. The Logistic or Gumbel–Hougaard distribution is one of the oldest multivariate extreme value models and it has been extended to asymmetric models. In this paper we introduce generalized logistic multivariate distributions. Our tools are mixtures of copulas and stable mixing variables, extending approaches in Tawn [14], Joe and Hu [6] and Fougères et al. [3]. The parametric family of multivariate extreme value distributions considered presents a flexible dependence structure and we compute for it the multivariate tail dependence coefficients considered in Li [7].
منابع مشابه
Generalized Logistic Models and its orthant tail dependence
Abstract: The Multivariate Extreme Value distributions have shown their usefulness in environmental studies, financial and insurance mathematics. The Logistic or Gumbel-Hougaard distribution is one of the oldest multivariate extreme value models and it has been extended to asymmetric models. In this paper we introduce generalized logistic multivariate distributions. Our tools are mixtures of co...
متن کاملOrthant tail dependence of multivariate extreme value distributions
AMS 2000 subject classifications: 62H20 62P05 Keywords: Tail dependence Heavy tails Copula Multivariate extreme value distribution Marshall–Olkin distribution Archimedean copula Contagion risk a b s t r a c t The orthant tail dependence describes the relative deviation of upper-(or lower-) orthant tail probabilities of a random vector from similar orthant tail probabilities of a subset of its c...
متن کاملTail Dependence of Multivariate Pareto Distributions
Various multivariate Pareto distributions are known to exhibit the heavy tail behaviors. This paper examines the tail dependence properties of a general class of multivariate Pareto distributions with the Pareto index and some common scale parameters. The multivariate tail dependence describes the amount of dependence in the upper-orthant tail or lower-orthant tail of a multivariate distributio...
متن کاملTraining L1-Regularized Models with Orthant-Wise Passive Descent Algorithms
The `1-regularized sparse model has been popular in machine learning society. The orthant-wise quasi-Newton (OWL-QN) method is a representative fast algorithm for training the model. However, the proof of the convergence has been pointed out to be incorrect by multiple sources, and up until now, its convergence has not been proved at all. In this paper, we propose a stochastic OWL-QN method for...
متن کاملDuality of the Multivariate Distributions of Marshall-Olkin Type and Tail Dependence
A dual class of the multivariate distributions of Marshall-Olkin type is introduced, and their copulas are presented and utilized to derive explicit expressions of the distributional tail dependencies, which describe the amount of dependence in the upperorthant tail or lower-orthant tail of a multivariate distribution and can be used in the study of dependence among extreme values. A sufficient...
متن کامل