We prove that when the distribution of a stochastic process in C[0, 1] is in the domain of attraction of a max-stable process, then natural estimators for the extreme-value index (which is now a continuous function) and for the mean measure of the limiting Poisson process are consistent in the appropriate topologies. The ultimate goal, estimating probabilities of small (failure) sets, will be considered later
This dissertation consists of results in two distinct areas of probability theory. One is the extrem...
We study the extreme value distribution of stochastic processes modeled by superstatistics. Classica...
We consider discrete time dynamical systems and show the link between Hitting Time Statistics (the d...
We prove that when the distribution of a stochastic process in C[0, 1] is in the domain of attractio...
We prove that when the distribution of a stochastic process in C[0, 1] is in the domain of attractio...
We prove that when the distribution of a stochastic process in C[0, 1] is in the domain of attractio...
We prove that when the distribution of a stochastic process in C[0, 1] is in the domain of attractio...
Consider n i.i.d. random elements on C[0; 1].We show that under an appropriate strengthening of the ...
In the field of spatial extremes, stochastic processes with upper semicontinuous (usc) trajectories ...
The aim of the present paper is to clarify the rôle of extreme order statistics in general statistic...
We introduce some mathematical framework for extreme value theory in the space of continuous functio...
The aim of the present paper is to clarify the rôle of extreme order statistics in general statistic...
The aim of the present paper is to clarify the role of extreme order statistics in general statistic...
This paper constructs from the record values an estimator of the extreme-value index. It is proved t...
Title: Stochastical inference in the model of extreme events Author: Jan Dienstbier Department/Insti...
This dissertation consists of results in two distinct areas of probability theory. One is the extrem...
We study the extreme value distribution of stochastic processes modeled by superstatistics. Classica...
We consider discrete time dynamical systems and show the link between Hitting Time Statistics (the d...
We prove that when the distribution of a stochastic process in C[0, 1] is in the domain of attractio...
We prove that when the distribution of a stochastic process in C[0, 1] is in the domain of attractio...
We prove that when the distribution of a stochastic process in C[0, 1] is in the domain of attractio...
We prove that when the distribution of a stochastic process in C[0, 1] is in the domain of attractio...
Consider n i.i.d. random elements on C[0; 1].We show that under an appropriate strengthening of the ...
In the field of spatial extremes, stochastic processes with upper semicontinuous (usc) trajectories ...
The aim of the present paper is to clarify the rôle of extreme order statistics in general statistic...
We introduce some mathematical framework for extreme value theory in the space of continuous functio...
The aim of the present paper is to clarify the rôle of extreme order statistics in general statistic...
The aim of the present paper is to clarify the role of extreme order statistics in general statistic...
This paper constructs from the record values an estimator of the extreme-value index. It is proved t...
Title: Stochastical inference in the model of extreme events Author: Jan Dienstbier Department/Insti...
This dissertation consists of results in two distinct areas of probability theory. One is the extrem...
We study the extreme value distribution of stochastic processes modeled by superstatistics. Classica...
We consider discrete time dynamical systems and show the link between Hitting Time Statistics (the d...