Statistical issues arising in modelling univariate extremes of a random sample have been
successfully used in the most diverse fields, such as biometrics, finance, insurance and risk …

This review paper focuses on statistical issues arising in modeling univariate extremes of a
random sample. In the last three decades there has been a shift from the area of parametric …

The classical Hill estimator of a positive extreme value index (EVI) can be regarded as the
logarithm of the geometric mean, or equivalently the logarithm of the mean of order p= 0, of a …

Reduced-bias versions of a very simple generalization of the 'classical'Hill estimator of a
positive extreme value index (EVI) are put forward. The Hill estimator can be regarded as the …

The overarching aim of this open access book is to present self-contained theory and
algorithms for investigation and prediction of electric demand peaks. A cross-section of …

In the paper, we propose a new idea in the tail-index estimation. This idea allows us to
improve the asymptotic performance of the classical Hill estimator and other most popular …

A new class of estimators of the extreme value index is developed. It has a simple form and
is asymptotically very close to the maximum likelihood estimator for a wide class of heavy …

Heavy-tailed distributions are often encountered in economics, finance, biology,
telecommunications, geology, etc. The heaviness of a tail is measured by a tail index …

In this article, we are interested in the comparison, under a third-order framework, of classes
of second-order, reduced-bias tail index estimators, giving particular emphasis to minimum …

In the field of Statistics of Extremes, the most common assumption on any set of univariate
data is to consider them as a complete sample of either independent and identically …