2 citations · 3 across the 12 of their papers we have counts for
17 papers
Weighted and Truncated Tail Index Estimation under Random Censoring: A Unified Full-Range Framework
Abdelhakim Necir, Nour Elhouda Guesmia, Djamel Meraghni
Estimation of the extreme value index under right censoring is a fundamental problem in extreme value theory, with important applications in finance, insurance, and reliability. Cl…
Weighted Estimation of the Tail Index under Right Censorship: A Unified Approach Based on Kaplan-Meier and Nelson-Aalen Integrals
Abdelhakim Necir, Nour Elhouda Guesmia, Djamel Meraghni
Kaplan-Meier and Nelson-Aalen integral estimators to the tail index of right-censored Pareto-type data traditionally rely on the assumption that the proportion p of upper uncensore…
Robust and Smooth Estimation of the Extreme Tail Index via Weighted Minimum Density Power Divergence
Saida Mancer, Abdelhakim Necir, Djamel Meraghni
By introducing a weight function into the density power divergence, we develop a new class of robust and smooth estimators for the tail index of Pareto-type distributions, offering…
Robust Tail Index Estimation under Random Censoring via Minimum Density Power Divergence
Nour Elhouda Guesmia, Abdelhakim Necir, Djamel Meraghni
We propose a robust estimator for the tail index of Pareto-type distributions under random right-censoring, constructed within the minimum density power divergence (MDPD) framework…
Nelson-Aalen kernel estimator to the tail index of right censored Pareto-type data
Nour Elhouda Guesmia, Abdelhakim Necir, Djamel Meraghni
On the basis of Nelson-Aalen product-limit estimator of a randomly censored distribution function, we introduce a kernel estimator to the tail index of right-censored Pareto-like d…
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.…
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…
A Lynden-Bell integral estimator for the tail index of right-truncated data with a random threshold
Nawel Haouas, Abdelhakim Necir, Djamel Meraghni +1
By means of a Lynden-Bell integral with deterministic threshold, Worms and Worms [A Lynden-Bell integral estimator for extremes of randomly truncated data. Statist. Probab. Lett. 2…
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…
Kernel estimation of the tail index of a right-truncated Pareto-type distribution
Souad Benchaira, Djamel Meraghni, Abdelhakim Necir
In this paper, we define a kernel estimator for the tail index of a Pareto-type distribution under random right-truncation and establish its asymptotic normality. A simulation stud…
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…
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…
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…
Nelson-Aalen tail product-limit process and extreme value index estimation under random censorship
Brahim Brahimi, Djamel Meraghni, Abdelhakim Necir
On the basis of Nelson-Aalen nonparametric estimator of the cumulative distribution function, we provide a weak approximation to tail product-limit process for randomly right-censo…
Gaussian approximation to the extreme value index estimator of a heavy-tailed distribution under random censoring
Brahim Brahimi, Djamel Meraghni, Abdelhakim Necir
We make use of the empirical process theory to approximate the adapted Hill estimator, for censored data, in terms of Gaussian processes. Then, we derive its asymptotic normality,…
A Bias-reduced Estimator for the Mean of a Heavy-tailed Distribution with an Infinite Second Moment
Brahim Brahimi, Djamel Meraghni, Abdelhakim Necir +1
We use bias-reduced estimators of high quantiles, of heavy-tailed distributions, to introduce a new estimator of the mean in the case of infinite second moment. The asymptotic norm…
Distortion risk measures for sums of dependent losses
Brahim Brahimi, Djamel Meraghni, Abdelhakim Necir
We discuss two distinct approaches, for distorting risk measures of sums of dependent random variables, which preserve the property of coherence. The first, based on distorted expe…