36 pagesInternational audienceThe goal of this paper is an exhaustive investigation of the link between the tail measure of a regularly varying time series and its spectral tail process, independently introduced in Owada and Samorodnitsky (2012) and Basrak and Segers (2009). Our main result is to prove in an abstract framework that there is a one to one correspondance between these two objets, and given one of them to show that it is always possible to build a time series of which it will be the tail measure or the spectral tail process. For non negative time series, we recover results explicitly or implicitly known in the theory of max-stable processes
We review spectral analysis and its application in inference for stationary processes. As can be see...
Modeling the dependence between consecutive observations in a time series plays a crucial role in ri...
AbstractMany qualitative properties of the spectral measure of a stationary Gaussian sequence are sp...
36 pagesInternational audienceThe goal of this paper is an exhaustive investigation of the link betw...
When aspatial process is recorded over time and the observation at a given time instant is viewed as...
To draw inference on serial extremal dependence within heavy-tailed Markov chains, Drees, Segers and...
AbstractThis paper is concerned with the estimation of the spectral measure of a stationary process....
The goal of this thesis is to treat the temporal tail dependence and the cross-sectional tail depend...
This paper is concerned with the estimation of the spectral measure of a stationary process. Empiric...
AbstractExtreme values of a stationary, multivariate time series may exhibit dependence across coord...
Extreme values of a stationary, multivariate time series may exhibit dependence across coordinates a...
We use tail dependence functions to study tail dependence for regularly varying (RV) time series. Fi...
Many interesting processes share the property of multivariate regular variation. This property is eq...
The aim of this paper is to take stock of the important recent contributions to spectral analysis, e...
To draw inference on serial extremal dependence within heavy-tailed Markov chains, Drees, Segers and...
We review spectral analysis and its application in inference for stationary processes. As can be see...
Modeling the dependence between consecutive observations in a time series plays a crucial role in ri...
AbstractMany qualitative properties of the spectral measure of a stationary Gaussian sequence are sp...
36 pagesInternational audienceThe goal of this paper is an exhaustive investigation of the link betw...
When aspatial process is recorded over time and the observation at a given time instant is viewed as...
To draw inference on serial extremal dependence within heavy-tailed Markov chains, Drees, Segers and...
AbstractThis paper is concerned with the estimation of the spectral measure of a stationary process....
The goal of this thesis is to treat the temporal tail dependence and the cross-sectional tail depend...
This paper is concerned with the estimation of the spectral measure of a stationary process. Empiric...
AbstractExtreme values of a stationary, multivariate time series may exhibit dependence across coord...
Extreme values of a stationary, multivariate time series may exhibit dependence across coordinates a...
We use tail dependence functions to study tail dependence for regularly varying (RV) time series. Fi...
Many interesting processes share the property of multivariate regular variation. This property is eq...
The aim of this paper is to take stock of the important recent contributions to spectral analysis, e...
To draw inference on serial extremal dependence within heavy-tailed Markov chains, Drees, Segers and...
We review spectral analysis and its application in inference for stationary processes. As can be see...
Modeling the dependence between consecutive observations in a time series plays a crucial role in ri...
AbstractMany qualitative properties of the spectral measure of a stationary Gaussian sequence are sp...