activity
20112019
most citedOn the estimation of the extreme value index for randomly right-truncated data and application

1 citations · 1 across the 4 of their papers we have counts for

collaborators

7 papers

math.ST2019

Extreme value theory based confidence intervals for the parameters of a symmetric Lévy-stable distribution

Djamel Meraghni, Louiza Soltane

We exploit the asymptotic normality of the extreme value theory (EVT) based estimators of the parameters of a symmetric Lévy-stable distribution, to construct confidence intervals.…

math.ST2018

Tail empirical process and weighted extreme value index estimator for randomly right-censored data

Brahim Brahimi, Djamel Meraghni, Abdelhakim Necir +1

A tail empirical process for heavy-tailed and right-censored data is introduced and its Gaussian approximation is established. In this context, a (weighted) new Hill-type estimator…

math.ST2016

Statistical estimate of the proportional hazard premium of loss under random censoring

Louiza Soltane, Djamel Meraghni, Abdelhakim Necir

Many insurance premium principles are defined and various estimation procedures introduced in the literature. In this paper, we focus on the estimation of the excess-of-loss reinsu…

math.ST2015

Estimating the mean of a heavy-tailed distribution under random censoring

Louiza Soltane, Djamel Meraghni, Abdelhakim Necir

The central limit theorem introduced by Stute [The central limit theorem under random censorship. Ann. Statist. 1995; 23: 422-439] does not hold for some class of heavy-tailed dist…

math.ST2015

Tail product-limit process for truncated data with application to extreme value index estimation

Souad Benchaira, Djamel Meraghni, Abdelhakim Necir

A weighted Gaussian approximation to tail product-limit process for Pareto-like distributions of randomly right-truncated data is provided and a new consistent and asymptotically n…

math.ST20151 cited

On the estimation of the extreme value index for randomly right-truncated data and application

S. Benchaira, D. Meraghni, A. Necir

We introduce a consistent estimator of the extreme value index under random truncation based on a single sample fraction of top observations from truncated and truncation data. We…