International audienceA flexible multivariate threshold exceedances modeling is defined based on componentwise ratios between any two independent random vectors with exponential and Gamma marginal distributions. This construction allows flexibility in terms of extremal bivariate dependence. More precisely, asymptotic dependence and independence are possible, as well as hybrid situations. Two useful parametric model classes will be presented. Oneof the two, based on Gamma convolution models, will be illustrated through a simulation study. Good performance is shown for likelihood-based estimation of summaries of bivariate extremal dependence for several scenarii
Multivariate generalized Pareto distributions arise as the limit distributions of exceedances over m...
Extreme value theory is about the distributions of very large or very small values in a time series ...
Modelling excesses over a high threshold using the Pareto or generalized Pareto distribution (PD/GPD...
Generalized Pareto distributions with positive tail index arise from embedding a Gamma random variab...
Multivariate peaks over thresholds modelling based on generalized Pareto distributions has up to now...
The multivariate generalized Pareto distribution arises as the limit of a suitably normalized vector...
Statistical inference for extremes has been a subject of intensive research over the past couple of ...
textabstractWhen assessing the impact of extreme events, it is often not just a single component, bu...
This work considers various approaches for modelling multivariate extremal events. First we review t...
Inference over multivariate tails often requires a number of assumptions which may affect the assess...
A number of different dependence scenarios can arise in the theory of multivariate extremes, entaili...
Abstract: We propose a threshold model extending the generalized Pareto distribu-tion for exceedance...
In this thesis, we develop new models for covariate-varying tail dependence structures and propose n...
Statistical models with parsimonious dependence are useful for high-dimensional modelling as they of...
Extreme value theory is about the distributions of very large or very small values in a time series...
Multivariate generalized Pareto distributions arise as the limit distributions of exceedances over m...
Extreme value theory is about the distributions of very large or very small values in a time series ...
Modelling excesses over a high threshold using the Pareto or generalized Pareto distribution (PD/GPD...
Generalized Pareto distributions with positive tail index arise from embedding a Gamma random variab...
Multivariate peaks over thresholds modelling based on generalized Pareto distributions has up to now...
The multivariate generalized Pareto distribution arises as the limit of a suitably normalized vector...
Statistical inference for extremes has been a subject of intensive research over the past couple of ...
textabstractWhen assessing the impact of extreme events, it is often not just a single component, bu...
This work considers various approaches for modelling multivariate extremal events. First we review t...
Inference over multivariate tails often requires a number of assumptions which may affect the assess...
A number of different dependence scenarios can arise in the theory of multivariate extremes, entaili...
Abstract: We propose a threshold model extending the generalized Pareto distribu-tion for exceedance...
In this thesis, we develop new models for covariate-varying tail dependence structures and propose n...
Statistical models with parsimonious dependence are useful for high-dimensional modelling as they of...
Extreme value theory is about the distributions of very large or very small values in a time series...
Multivariate generalized Pareto distributions arise as the limit distributions of exceedances over m...
Extreme value theory is about the distributions of very large or very small values in a time series ...
Modelling excesses over a high threshold using the Pareto or generalized Pareto distribution (PD/GPD...