Add to ORKGThis paper contains the results concerning the weak convergence of d-dimensional extreme order statistics in a Gaussian, equally correlated array. Three types of limit distributions are found and sufficient conditions for the existence of these distributions are given
AbstractIn this paper, not only the weak convergence is considered, as in the ASCLT in Theorem 2.3 t...
The aim of the present paper is to clarify the rôle of extreme order statistics in general statistic...
This paper proves weak convergence in D of the tail empirical process – the renormalized extreme tai...
In this paper, we study the limit distribution functions of the (lower-lower), (upper-upper) and (lo...
We investigate extreme value theory of a class of random sequences defined by the all-time suprema o...
Let be a d-dimensional array of independent standard Gaussian random variables. For a finite set def...
AbstractSuppose that {ξj} is a strictly stationary sequence which satisfies the strong mixing condit...
AbstractAny multivariate distribution can occur as the limit of extreme values in a sequence of inde...
We investigate extreme value theory of a class of random sequences defined by the all-time suprema o...
In this paper we show that the componentwise maxima of weakly dependent bivariate stationary Gaussia...
In this note an interesting fact is proved that, for any vector of bivariate extreme order statistic...
In this note an interesting fact is proved that, for any vector of bivariate extreme order statistic...
Let Xi,n, n ∈ N, 1 ≤ i ≤ n, be a triangular array of independent Rd-valued Gaussian random vectors w...
AbstractUnder weak regularity conditions of the covariance sequence, it is shown that the joint limi...
We establish sharp tail asymptotics for componentwise extreme values of bivariate Gaussian random ve...
AbstractIn this paper, not only the weak convergence is considered, as in the ASCLT in Theorem 2.3 t...
The aim of the present paper is to clarify the rôle of extreme order statistics in general statistic...
This paper proves weak convergence in D of the tail empirical process – the renormalized extreme tai...
In this paper, we study the limit distribution functions of the (lower-lower), (upper-upper) and (lo...
We investigate extreme value theory of a class of random sequences defined by the all-time suprema o...
Let be a d-dimensional array of independent standard Gaussian random variables. For a finite set def...
AbstractSuppose that {ξj} is a strictly stationary sequence which satisfies the strong mixing condit...
AbstractAny multivariate distribution can occur as the limit of extreme values in a sequence of inde...
We investigate extreme value theory of a class of random sequences defined by the all-time suprema o...
In this paper we show that the componentwise maxima of weakly dependent bivariate stationary Gaussia...
In this note an interesting fact is proved that, for any vector of bivariate extreme order statistic...
In this note an interesting fact is proved that, for any vector of bivariate extreme order statistic...
Let Xi,n, n ∈ N, 1 ≤ i ≤ n, be a triangular array of independent Rd-valued Gaussian random vectors w...
AbstractUnder weak regularity conditions of the covariance sequence, it is shown that the joint limi...
We establish sharp tail asymptotics for componentwise extreme values of bivariate Gaussian random ve...
AbstractIn this paper, not only the weak convergence is considered, as in the ASCLT in Theorem 2.3 t...
The aim of the present paper is to clarify the rôle of extreme order statistics in general statistic...
This paper proves weak convergence in D of the tail empirical process – the renormalized extreme tai...