AbstractWe obtain the explicit Karhunen–Loeve decomposition of a Gaussian process generated as the limit of an empirical process based upon independent pairs of exponential random variables. The orthogonal eigenfunctions of the covariance kernel have simple expressions in terms of Jacobi polynomials. Statistical applications, in extreme value and reliability theory, include a Cramér–von Mises test of bivariate independence, whose null distribution and critical values are tabulated
In this paper we define conditional random fields in reproducing kernel Hilbert spaces and show conn...
AbstractIn this paper we investigate the tail behaviour of a random variable S which may be viewed a...
The aim of this thesis is to study and show, as described in the works of Nualart, that a sequence o...
AbstractWe obtain the explicit Karhunen–Loeve decomposition of a Gaussian process generated as the l...
In this paper, we consider weighted quadratic functionals of the multivariate uniform empirical proc...
AbstractIn the multivariate case, the empirical dependence function, defined as the empirical distri...
International audienceWe propose some construction of enhanced Gaussian processes using Karhunen-Loe...
A theorem is proved that allows to use approximations for construction of the Karhunen-Loeve model o...
Let (Xj)∞ j = 1 be a stationary, mean-zero Gaussian process with covariances r(k) = EXk + 1 X1 satis...
Li, WenboLeung, Yuk J.In this dissertation, we study the Karhunen-Lo??ve (KL) expansion and the exac...
The extremal coefficient function (ECF) of a max-stable process X on some index set T assigns to eac...
Abstract. We consider quadratic functionals of the multivariate uniform empirical process. Making us...
AbstractLet {Xi, i⩾0} be a sequence of independent identically distributed random variables with fin...
Let {Xi (t), t ≥ 0}, 1 ≤ i ≤ n be mutually independent centered Gaussian processes with almost surel...
AbstractLet X be a Gaussian rv with values in a separable Hilbert space H having a covariance operat...
In this paper we define conditional random fields in reproducing kernel Hilbert spaces and show conn...
AbstractIn this paper we investigate the tail behaviour of a random variable S which may be viewed a...
The aim of this thesis is to study and show, as described in the works of Nualart, that a sequence o...
AbstractWe obtain the explicit Karhunen–Loeve decomposition of a Gaussian process generated as the l...
In this paper, we consider weighted quadratic functionals of the multivariate uniform empirical proc...
AbstractIn the multivariate case, the empirical dependence function, defined as the empirical distri...
International audienceWe propose some construction of enhanced Gaussian processes using Karhunen-Loe...
A theorem is proved that allows to use approximations for construction of the Karhunen-Loeve model o...
Let (Xj)∞ j = 1 be a stationary, mean-zero Gaussian process with covariances r(k) = EXk + 1 X1 satis...
Li, WenboLeung, Yuk J.In this dissertation, we study the Karhunen-Lo??ve (KL) expansion and the exac...
The extremal coefficient function (ECF) of a max-stable process X on some index set T assigns to eac...
Abstract. We consider quadratic functionals of the multivariate uniform empirical process. Making us...
AbstractLet {Xi, i⩾0} be a sequence of independent identically distributed random variables with fin...
Let {Xi (t), t ≥ 0}, 1 ≤ i ≤ n be mutually independent centered Gaussian processes with almost surel...
AbstractLet X be a Gaussian rv with values in a separable Hilbert space H having a covariance operat...
In this paper we define conditional random fields in reproducing kernel Hilbert spaces and show conn...
AbstractIn this paper we investigate the tail behaviour of a random variable S which may be viewed a...
The aim of this thesis is to study and show, as described in the works of Nualart, that a sequence o...