Add to ORKGWe propose a consistent estimator for the exponential tail coefficient of a d.f., that is directly related to least squares estimators of Schultze and Steinebach [Statist. Decis. 14 (1996) 353]. We investigate here the weak asymptotic properties of this geometric-type estimator, showing in particular that, under general conditions, its distribution is asymptotically normal. The results are then applied to the related problem of estimating the adjustment coefficient in risk theory [Insur.: Math. Econ. 10 (1991) 37]. A simulation study is performed in order to illustrate the finite sample behaviour of the proposed estimator
Likelihood-based procedures are a common way to estimate tail depen- dence parameters. They are not ...
The problem of estimation of the heavy tail index is revisited from the point of view of truncated e...
AbstractWe determine the joint asymptotic normality of kernel and weighted least-squares estimators ...
Let Z1, Z2,... be i.i.d. random variables with tail behaviour P (Z1> z) = r(z)e−Rz, where r is a ...
The estimation of the tail index is a central topic in extreme value analysis. We consider a geometr...
We propose a class of weighted least squares estimators for the tail index of a distribution functio...
Z. Fabian and M. Stehlik (2009) investigate a new estimator of extreme value index of a distribution...
This dissertation has 4 chapters, in which we attempt to explore and analyze the structure of extrem...
In this paper we consider an autoregressive Pareto process which can be used as an alternative to h...
In this paper, and in the context of regularly varying tails, we analyse some variants of a maximum ...
We extend classical extreme value theory to non-identically distributed observations. When the tails...
Estimation of the tail index of stationary, fat-tailed return distributions is non-trivial since the...
In this work we discuss tail index estimation for heavy-tailed distributions with an emphasis on rob...
In extreme value statistics, the tail index is an important measure to gauge the heavy-tailed behavi...
Abstract: In this paper we shall consider a natural Generalized Jackknife estimator of the index of ...
Likelihood-based procedures are a common way to estimate tail depen- dence parameters. They are not ...
The problem of estimation of the heavy tail index is revisited from the point of view of truncated e...
AbstractWe determine the joint asymptotic normality of kernel and weighted least-squares estimators ...
Let Z1, Z2,... be i.i.d. random variables with tail behaviour P (Z1> z) = r(z)e−Rz, where r is a ...
The estimation of the tail index is a central topic in extreme value analysis. We consider a geometr...
We propose a class of weighted least squares estimators for the tail index of a distribution functio...
Z. Fabian and M. Stehlik (2009) investigate a new estimator of extreme value index of a distribution...
This dissertation has 4 chapters, in which we attempt to explore and analyze the structure of extrem...
In this paper we consider an autoregressive Pareto process which can be used as an alternative to h...
In this paper, and in the context of regularly varying tails, we analyse some variants of a maximum ...
We extend classical extreme value theory to non-identically distributed observations. When the tails...
Estimation of the tail index of stationary, fat-tailed return distributions is non-trivial since the...
In this work we discuss tail index estimation for heavy-tailed distributions with an emphasis on rob...
In extreme value statistics, the tail index is an important measure to gauge the heavy-tailed behavi...
Abstract: In this paper we shall consider a natural Generalized Jackknife estimator of the index of ...
Likelihood-based procedures are a common way to estimate tail depen- dence parameters. They are not ...
The problem of estimation of the heavy tail index is revisited from the point of view of truncated e...
AbstractWe determine the joint asymptotic normality of kernel and weighted least-squares estimators ...