Add to ORKGLet (X, Y) = (RU 1, RU 2) be a given bivariate scale mixture random vector, with R > 0 independent of the bivariate random vector (U 1, U 2). In this paper we derive exact asymptotic expansions of the joint survivor probability of (X, Y) assuming that R has distribution function in the Gumbel max-domain of attraction, and (U 1, U 2) has a specific local asymptotic behaviour around some absorbing point. We apply our results to investigate the asymptotic behaviour of joint conditional excess distribution and the asymptotic independence for two models of bivariate scale mixture distribution
A fundamental issue in applied multivariate extreme value (MEV) analysis is modelling dependence wit...
A bivariate competing risks problem is considered for a rather general class of survival models. The...
This paper exploits a stochastic representation of bivariate elliptical distributions in order to ob...
Let (X, Y) = (RU (1), RU (2)) be a given bivariate scale mixture random vector, with R > 0 indepe...
International audienceWe investigate conditions for the existence of the limiting conditional distri...
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...
The Ledford and Tawn model for the bivariate tail incorporates a coefficient, $\eta$, as a measure o...
Let (S 1,S 2) = (R cos(Θ), R sin(Θ)) be a bivariate random vector with associated random radius R wh...
AbstractA well-known result in extreme value theory indicates that componentwise taken sample maxima...
In this article we discuss the asymptotic behaviour of the componentwise maxima for a specific bivar...
32 pages, 5 figureInternational audienceLet $(X,Y)$ be a bivariate random vector. The estimation of ...
Let $ {\boldsymbol X} = A{\boldsymbol S} $ be an elliptical random vector with $ A \in \mathbb{R}^{{...
AbstractLet {Xn,n⩾1} be iid elliptical random vectors in Rd,d≥2 and let I,J be two non-empty disjoin...
We investigate the product Y1Y2 of two independent positive risks Y1 and Y2. If Y1 has distribution ...
A fundamental issue in applied multivariate extreme value (MEV) analysis is modelling dependence wit...
A bivariate competing risks problem is considered for a rather general class of survival models. The...
This paper exploits a stochastic representation of bivariate elliptical distributions in order to ob...
Let (X, Y) = (RU (1), RU (2)) be a given bivariate scale mixture random vector, with R > 0 indepe...
International audienceWe investigate conditions for the existence of the limiting conditional distri...
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...
The Ledford and Tawn model for the bivariate tail incorporates a coefficient, $\eta$, as a measure o...
Let (S 1,S 2) = (R cos(Θ), R sin(Θ)) be a bivariate random vector with associated random radius R wh...
AbstractA well-known result in extreme value theory indicates that componentwise taken sample maxima...
In this article we discuss the asymptotic behaviour of the componentwise maxima for a specific bivar...
32 pages, 5 figureInternational audienceLet $(X,Y)$ be a bivariate random vector. The estimation of ...
Let $ {\boldsymbol X} = A{\boldsymbol S} $ be an elliptical random vector with $ A \in \mathbb{R}^{{...
AbstractLet {Xn,n⩾1} be iid elliptical random vectors in Rd,d≥2 and let I,J be two non-empty disjoin...
We investigate the product Y1Y2 of two independent positive risks Y1 and Y2. If Y1 has distribution ...
A fundamental issue in applied multivariate extreme value (MEV) analysis is modelling dependence wit...
A bivariate competing risks problem is considered for a rather general class of survival models. The...
This paper exploits a stochastic representation of bivariate elliptical distributions in order to ob...