Abstract
This PhD thesis presents contributions to the modelling of multivariate extremevalues. We introduce a new tail model for multivariate distribution with Pareto margins. This model is inspired from the Wadsworth and Tawn (2013) one. A new non-standard multivariate regular variation with index equals to a function of two variables is thus introduced to generalize both modeling approaches proposedby Ramos and Ledford (2009) and Wadsworth and Tawn (2013), respectively. Building on this new approach we propose a new class of non-parametric models allowing multivariate extrapolation along trajectories covering the entire first positive quadrant. Similarly we consider parametric models built with a non-negative measure satisfying a constraint that generalizes the Ramos and Ledford (2009) one. These new models are flexible and valid in both situations of dependence or asymptotic independence.