A nonparametric estimation of the conditional ageing intensity function in censored data: A local linear approach-Reference-Cited by-同舟云学术

A nonparametric estimation of the conditional ageing intensity function in censored data: A local linear approach

Published:2021-04-01 Issue:2 Volume:71 Page:429-438
ISSN:1337-2211
Container-title:Mathematica Slovaca
language:en
Short-container-title:

Author:

Khardani Salah¹,Benkhaled Abdelkader²

Affiliation:

1. Laboratoire des Réseaux Intelligents et Nanotechnologie, Ecole Nationale des Sciences et, Technologies Avancáes Borj-Cédria , Borj-Cédria , Tunisia

2. Biology department, Faculty of Science, University of Mascara , Mascara , Algeria

Abstract

Abstract In this paper, we investigate the problem of the local linear estimation of the conditional ageing intensity function, when the variable of interest is subject to random right-censored. We establish under appropriate conditions the asymptotic normality of this estimator.

Publisher

Walter de Gruyter GmbH

Subject

General Mathematics

Link

https://www.degruyter.com/document/doi/10.1515/ms-2017-0479/pdf

Reference22 articles.

1. Bhattacharjee, S.—Nanda, A. K.—Misra, S. K.: Reliability analysis using ageing intensity function, Stat. Probab. Lett. 83(5) (2013), 1364–1371.

2. Bosq, D.: Nonparametric Statistics for Stochastic Processes: Estimation and Prediction, 2nd edition, New-York, Springer Verlag, 1999.

3. Bryson, M. C.—Siddiqui, M.: Some criteria for ageing, J. Amer. Statist. Assoc. 64 (1969), 1472–1483.

4. Bradley, R.: Introduction to Strong Mixing Conditions, Volumes 1–3, Kendrick Press, 2007.

5. Cai, Z.: Estimating a distribution function for censored time series data, J. Multivariate Anal. 78 (2001), 299–318.

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