AbstractA well-known result in extreme value theory indicates that componentwise taken sample maxima of random vectors are asymptotically independent under weak conditions. However, in important cases this independence is attained at a very slow rate so that the residual dependence structure plays a significant role.In the present article, we deduce limiting distributions of maxima under triangular schemes of random vectors. The residual dependence is expressed by a technical condition imposed on the spectral expansion of the underlying distribution
A bivariate random vector can exhibit either asymptotic independence or dependence between the large...
In the classical setting of bivariate extreme value theory, the procedures for estimating the probab...
AbstractThe set of the functions H, which are limiting distributions of linearly normalized maxima o...
AbstractA well-known result in extreme value theory indicates that componentwise taken sample maxima...
We analyse the asymptotic dependence structure of bivariate maxima in a triangular array of independ...
Let $\mathbf{X}(n) \in \mathbb{R}^d$ be a sequence of random vectors, where $n\in\mathbb{N}$ and $d ...
AbstractA distributional mixing condition is introduced for stationary sequences of random vectors t...
AbstractAny multivariate distribution can occur as the limit of extreme values in a sequence of inde...
In this paper, we study the asymptotic distribution of the maxima of suprema of dependent Gaussian p...
This paper explores the joint extreme-value behavior of discontinuous random variables. It is shown ...
summary:Due to globalization and relaxed market regulation, we have assisted to an increasing of ext...
Abstract. Models based on assumptions of multivariate regular variation and hidden regular variation...
In this paper we study the asymptotic behaviour of sample maxima of weighted Dirichlet triangular ar...
The study of multivariate extremes is dominated by multivariate regular variation, although it is we...
AbstractIn this paper, not only the weak convergence is considered, as in the ASCLT in Theorem 2.3 t...
A bivariate random vector can exhibit either asymptotic independence or dependence between the large...
In the classical setting of bivariate extreme value theory, the procedures for estimating the probab...
AbstractThe set of the functions H, which are limiting distributions of linearly normalized maxima o...
AbstractA well-known result in extreme value theory indicates that componentwise taken sample maxima...
We analyse the asymptotic dependence structure of bivariate maxima in a triangular array of independ...
Let $\mathbf{X}(n) \in \mathbb{R}^d$ be a sequence of random vectors, where $n\in\mathbb{N}$ and $d ...
AbstractA distributional mixing condition is introduced for stationary sequences of random vectors t...
AbstractAny multivariate distribution can occur as the limit of extreme values in a sequence of inde...
In this paper, we study the asymptotic distribution of the maxima of suprema of dependent Gaussian p...
This paper explores the joint extreme-value behavior of discontinuous random variables. It is shown ...
summary:Due to globalization and relaxed market regulation, we have assisted to an increasing of ext...
Abstract. Models based on assumptions of multivariate regular variation and hidden regular variation...
In this paper we study the asymptotic behaviour of sample maxima of weighted Dirichlet triangular ar...
The study of multivariate extremes is dominated by multivariate regular variation, although it is we...
AbstractIn this paper, not only the weak convergence is considered, as in the ASCLT in Theorem 2.3 t...
A bivariate random vector can exhibit either asymptotic independence or dependence between the large...
In the classical setting of bivariate extreme value theory, the procedures for estimating the probab...
AbstractThe set of the functions H, which are limiting distributions of linearly normalized maxima o...