3 citations · 9 across the 20 of their papers we have counts for
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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…
Kernel estimation for the tail index of a right-censored Pareto-type distribution
Abdelhakim Necir, Louiza Soltane
We introduce a kernel estimator, to the tail index of a right-censored Pareto-type distribution, that generalizes Worms's one (Worms and Worms, 2014)in terms of weight coefficients…