Výsledky vyhledávání

Akademický článek

CLT for single functional index quantile regression under dependence structure

Autor: Kadiri Nadia, Rabhi Abbes, Khardani Salah, Akkal Fatima

Publikováno v: Acta Universitatis Sapientiae: Mathematica, Vol 13, Iss 1, Pp 45-77 (2021)

In this paper, we investigate the asymptotic properties of a nonparametric conditional quantile estimation in the single functional index model for dependent functional data and censored at random responses are observed. First of all, we establish as

Externí odkaz: https://doaj.org/article/65947721edd944a5a606cdae976fcaea

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Akademický článek

Strong uniform consistency rates of conditional quantile estimation in the single functional index model under random censorship

Autor: Kadiri Nadia, Rabhi Abbes, Bouchentouf Amina Angelika

Publikováno v: Dependence Modeling, Vol 6, Iss 1, Pp 197-227 (2018)

The main objective of this paper is to non-parametrically estimate the quantiles of a conditional distribution in the censorship model when the sample is considered as an -mixing sequence. First of all, a kernel type estimator for the conditional cum

Externí odkaz: https://doaj.org/article/6c80e2074193415fab4160ad0f0b97bb

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Akademický článek

Asymptotic normality of conditional distribution estimation in the single index model

Autor: Hamdaoui Diaa Eddine, Bouchentouf Amina Angelika, Rabhi Abbes, Guendouzi Toufik

Publikováno v: Acta Universitatis Sapientiae: Mathematica, Vol 9, Iss 1, Pp 162-175 (2017)

This paper deals with the estimation of conditional distribution function based on the single-index model. The asymptotic normality of the conditional distribution estimator is established. Moreover, as an application, the asymptotic (1 − γ) confi

Externí odkaz: https://doaj.org/article/e39e43479c8843d0b255cc201637eab7

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Akademický článek

Consistency rates and asymptotic normality of the high risk conditional for functional data

Autor: Rabhi Abbes, Keddani Latifa, Hammou Yassine

Publikováno v: Acta Universitatis Sapientiae: Mathematica, Vol 8, Iss 1, Pp 127-149 (2016)

The maximum of the conditional hazard function is a parameter of great importance in seismicity studies, because it constitutes the maximum risk of occurrence of an earthquake in a given interval of time. Using the kernel nonparametric estimates of t

Externí odkaz: https://doaj.org/article/3026ff5ee9dd471fa84e328cb5874c7b

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