The purpose of this research is to find the asymptotically exact expressions for the distribution function and for the probability that the absolute maximum of the sum of statistically independent homogeneous Gaussian and Rayleigh random processes with nondifferentiable covariance function will exceed the specified threshold. In this study, the applicability boundaries of the introduced theoretical formulas are also determined by means of statistical simulation. The recommendations are presented concerning the application of the obtained expressions depending on the observation interval length and the interrelation of Gaussian and Rayleigh components of the analyzed random process
Abstract. We study the tails of the distribution of the maximum of a stationary Gaussian process on ...
Let Xi,n, n ∈ N, 1 ≤ i ≤ n, be a triangular array of independent Rd-valued Gaussian random vectors w...
We define PSI-process — Poisson Stochastic Index process, as a continuous time random process which...
The purpose of this research is to find the asymptotically exact expressions for the distribution fu...
The purpose of this research is to find the asymptotically exact expressions for the distribution fu...
In this paper we are interested in the distribution of the maximum, or the maximum of the absolute v...
The exact distribution of extremes of a non-gaussian stationary discrete process is obtained and the...
AbstractThe exact distribution of extremes of a non-gaussian stationary discrete process is obtained...
This paper deals with the problem of obtaining methods to compute the distribution of the maximum of...
AbstractLet ξ(t) be a standard stationary Gaussian process with covariance function r(t), and η(t), ...
This paper uses the Rice method [18] to give bounds to the distribution of the maximum of a smooth...
The estimate of the initial moments in the distribution of an absolute maximum of a stationary Gauss...
It is well known, that under the condition LAN and some more regularity conditions, the process of l...
AbstractIt is well known, that under the condition LAN and some more regularity conditions, the proc...
We evaluate upper bounds for the maximal distributions of some Gaussian random fields, which arise i...
Abstract. We study the tails of the distribution of the maximum of a stationary Gaussian process on ...
Let Xi,n, n ∈ N, 1 ≤ i ≤ n, be a triangular array of independent Rd-valued Gaussian random vectors w...
We define PSI-process — Poisson Stochastic Index process, as a continuous time random process which...
The purpose of this research is to find the asymptotically exact expressions for the distribution fu...
The purpose of this research is to find the asymptotically exact expressions for the distribution fu...
In this paper we are interested in the distribution of the maximum, or the maximum of the absolute v...
The exact distribution of extremes of a non-gaussian stationary discrete process is obtained and the...
AbstractThe exact distribution of extremes of a non-gaussian stationary discrete process is obtained...
This paper deals with the problem of obtaining methods to compute the distribution of the maximum of...
AbstractLet ξ(t) be a standard stationary Gaussian process with covariance function r(t), and η(t), ...
This paper uses the Rice method [18] to give bounds to the distribution of the maximum of a smooth...
The estimate of the initial moments in the distribution of an absolute maximum of a stationary Gauss...
It is well known, that under the condition LAN and some more regularity conditions, the process of l...
AbstractIt is well known, that under the condition LAN and some more regularity conditions, the proc...
We evaluate upper bounds for the maximal distributions of some Gaussian random fields, which arise i...
Abstract. We study the tails of the distribution of the maximum of a stationary Gaussian process on ...
Let Xi,n, n ∈ N, 1 ≤ i ≤ n, be a triangular array of independent Rd-valued Gaussian random vectors w...
We define PSI-process — Poisson Stochastic Index process, as a continuous time random process which...