AbstractLet {Xk, k⩾1} be a multivariate Gaussian sequence, and Mn be the partial maxima, taken componentwise, i.e. Mni=max{Xki,k⩽n}, for any i ⩽ p. We deal with the limiting behaviour of the distribution of Mn and show that, under certain conditions, this limit distribution is equal to the product of the marginal limit distributions of the Mni's or to the asymptotic product of the distributions of the Xk's
AbstractThe asymptotic distribution of the maximum Mn=max1⩽t⩽nξt in a stationary normal sequence ξ1,...
AbstractWe proved some almost sure limit theorems for standard strongly dependent Gaussian sequences...
AbstractA distributional mixing condition is introduced for stationary sequences of random vectors t...
AbstractIn this paper we study the asymptotic joint behavior of the maximum and the partial sum of a...
In this paper we study the asymptotic joint behavior of the maximum and the partial sum of a multiva...
AbstractUnder weak regularity conditions of the covariance sequence, it is shown that the joint limi...
AbstractIn this paper we study the asymptotic joint behavior of the maximum and the partial sum of a...
AbstractLet {Xn} be a stationary Gaussian sequence with E{X0} = 0, {X20} = 1 and E{X0Xn} = rn n Let ...
AbstractA distributional mixing condition is introduced for stationary sequences of random vectors t...
In this paper we show that the componentwise maxima of weakly dependent bivariate stationary Gaussia...
Let (Formula presented.) be a Gaussian random vector with a common correlation coefficient (Formula ...
This paper deals with a weak convergence of maximum vectors built on the base of stationary and norm...
AbstractLet (Xn) be a strictly stationary random sequence and Mn=max{X1,…,Xn}. Suppose that some of ...
AbstractLet {Xn,n≥1} be a strictly stationary sequence of random variables and Mn=max{X1,X2,…,Xn}. A...
AbstractAny multivariate distribution can occur as the limit of extreme values in a sequence of inde...
AbstractThe asymptotic distribution of the maximum Mn=max1⩽t⩽nξt in a stationary normal sequence ξ1,...
AbstractWe proved some almost sure limit theorems for standard strongly dependent Gaussian sequences...
AbstractA distributional mixing condition is introduced for stationary sequences of random vectors t...
AbstractIn this paper we study the asymptotic joint behavior of the maximum and the partial sum of a...
In this paper we study the asymptotic joint behavior of the maximum and the partial sum of a multiva...
AbstractUnder weak regularity conditions of the covariance sequence, it is shown that the joint limi...
AbstractIn this paper we study the asymptotic joint behavior of the maximum and the partial sum of a...
AbstractLet {Xn} be a stationary Gaussian sequence with E{X0} = 0, {X20} = 1 and E{X0Xn} = rn n Let ...
AbstractA distributional mixing condition is introduced for stationary sequences of random vectors t...
In this paper we show that the componentwise maxima of weakly dependent bivariate stationary Gaussia...
Let (Formula presented.) be a Gaussian random vector with a common correlation coefficient (Formula ...
This paper deals with a weak convergence of maximum vectors built on the base of stationary and norm...
AbstractLet (Xn) be a strictly stationary random sequence and Mn=max{X1,…,Xn}. Suppose that some of ...
AbstractLet {Xn,n≥1} be a strictly stationary sequence of random variables and Mn=max{X1,X2,…,Xn}. A...
AbstractAny multivariate distribution can occur as the limit of extreme values in a sequence of inde...
AbstractThe asymptotic distribution of the maximum Mn=max1⩽t⩽nξt in a stationary normal sequence ξ1,...
AbstractWe proved some almost sure limit theorems for standard strongly dependent Gaussian sequences...
AbstractA distributional mixing condition is introduced for stationary sequences of random vectors t...