The aim of this paper is to provide models for spatial extremes in the case of stationarity. The spatial dependence at extreme levels of a stationary process is modeled using an extension of the theory of max-stable processes of de Haan and Pickands [Probab. Theory Related Fields 72 (1986) 477-492]. We propose three one-dimensional and three two-dimensional models. These models depend on just one parameter or a few parameters that measure the strength of tail dependence as a function of the distance between locations. We also propose two estimators for this parameter and prove consistency under domain of attraction conditions and asymptotic normality under appropriate extra conditions
The statistical theory of extremes is extended to independent multivariate observations that are non...
The areal modeling of the extremes of a natural process such as rainfall or temperature is important...
Max-stable processes allow the spatial dependence of extremes to be modelled and quantified, so they...
textabstractThe aim of this paper is to provide models for spatial extremes in the case of stationar...
• One common way to deal with extreme value analysis in spatial statistics is by using the max-stabl...
Max-stable processes play a fundamental role in modeling the spatial dependence of extremes because ...
Max-stable processes are natural models for spatial extremes because they provide suit-able asymptot...
Recently there has been a lot of effort to model extremes of spatially dependent data. These effort...
The classical modeling of spatial extremes relies on asymptotic models (i.e., max‐stable or r‐Pareto...
The analysis of spatial extremes requires the joint modeling of a spatial process at a large number ...
Currently available models for spatial extremes suffer either from inflexibility in the dependence s...
The conditional extremes framework allows for event-based stochastic modeling of dependent extremes,...
Max-stable processes are widely used to model spatial extremes. These processes exhibit asymptotic d...
Max-stable processes arise as the only possible nontrivial limits for maxima of affinely normalized ...
Extreme environmental phenomena such as major precipitation events manifestly exhibit spatial depend...
The statistical theory of extremes is extended to independent multivariate observations that are non...
The areal modeling of the extremes of a natural process such as rainfall or temperature is important...
Max-stable processes allow the spatial dependence of extremes to be modelled and quantified, so they...
textabstractThe aim of this paper is to provide models for spatial extremes in the case of stationar...
• One common way to deal with extreme value analysis in spatial statistics is by using the max-stabl...
Max-stable processes play a fundamental role in modeling the spatial dependence of extremes because ...
Max-stable processes are natural models for spatial extremes because they provide suit-able asymptot...
Recently there has been a lot of effort to model extremes of spatially dependent data. These effort...
The classical modeling of spatial extremes relies on asymptotic models (i.e., max‐stable or r‐Pareto...
The analysis of spatial extremes requires the joint modeling of a spatial process at a large number ...
Currently available models for spatial extremes suffer either from inflexibility in the dependence s...
The conditional extremes framework allows for event-based stochastic modeling of dependent extremes,...
Max-stable processes are widely used to model spatial extremes. These processes exhibit asymptotic d...
Max-stable processes arise as the only possible nontrivial limits for maxima of affinely normalized ...
Extreme environmental phenomena such as major precipitation events manifestly exhibit spatial depend...
The statistical theory of extremes is extended to independent multivariate observations that are non...
The areal modeling of the extremes of a natural process such as rainfall or temperature is important...
Max-stable processes allow the spatial dependence of extremes to be modelled and quantified, so they...