Zobrazeno 1 - 10
of 74
pro vyhledávání: '"Necir, Abdelhakim"'
Publikováno v:
Arab Journal of Mathematical Sciences, 2022, Vol. 30, Issue 2, pp. 171-196.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/AJMS-02-2022-0033
Autor:
Necir, Abdelhakim, Soltane, Louiza
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. Under some regularity conditions, the asymptotic normality of the pr
Externí odkaz:
http://arxiv.org/abs/2110.07459
It was shown that when one disposes of a parametric information of the truncation distribution, the semiparametric estimator of the distribution function for truncated data (Wang, 1989) is more efficient than the nonparametric one. On the basis of th
Externí odkaz:
http://arxiv.org/abs/2106.01004
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 for positive extreme value index is proposed and its consistency and
Externí odkaz:
http://arxiv.org/abs/1801.00572
Autor:
Necir, Abdelhakim
The well-known Koml\'os-Major-Tusn\'ady inequalities [Z. Wahrsch. Verw. Gebiete 32 (1975) 111-131; Z. Wahrsch. Verw. Gebiete 34 (1976) 33-58] provide sharp inequalities to partial sums of iid standard exponential random variables by a sequence of sta
Externí odkaz:
http://arxiv.org/abs/1709.00747
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. 2016; 109: 106-117] recently introduced an asymptotically normal estima
Externí odkaz:
http://arxiv.org/abs/1611.05147
In this paper, we propose an estimator of the second-order parameter of randomly right-truncated Pareto-type distributions data and establish its consistency and asymptotic normality. Moreover, we derive an asymptotically unbiased estimator of the ta
Externí odkaz:
http://arxiv.org/abs/1610.00094
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 reinsurance premium when the risks are randomly right-censored. The asymptot
Externí odkaz:
http://arxiv.org/abs/1602.02605
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 study shows that, compared to the estimators recently proposed by Gardes &
Externí odkaz:
http://arxiv.org/abs/1512.00425
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 distributions. In this paper, we make use of the extreme value theory to p
Externí odkaz:
http://arxiv.org/abs/1507.03178