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Article

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Title

Nonparametric estimation of aging intensity function forright-censored dependent data

Authors

[ 1 ] Instytut Automatyki i Robotyki, Wydział Automatyki, Robotyki i Elektrotechniki, Politechnika Poznańska | [ P ] employee

Scientific discipline (Law 2.0)

[2.2] Automation, electronics, electrical engineering and space technology

Year of publication

2024

Published in

Journal of Statistical Computation and Simulation

Journal year: 2024 | Journal volume: in press

Article type

scientific article

Publication language

english

Keywords
EN
  • aging intensity function
  • nonparametric densityestimation
  • α-mixing
  • meansquared error (MSE)
Abstract

EN Aging Intensity (AI) function is a quantitative measure of hazard function (hazard rate/failure rate), which is used for evaluating the aging behaviour of a component/system. Although variety of research are now available on various properties such as modelling and analysis of AI function; however, a detailed theoretical study on the estimation of the same has not been considered. Accordingly, in the present study, we propose two nonparametric estimators for aging intensity function based on right-censored dependent data scheme and study their properties. Asymptotic properties of the estimators are established under suitable regularity conditions. A simulation study and real data analysis have been carried out to illustrate the performance of the estimators.

Date of online publication

22.01.2024

DOI

10.1080/00949655.2024.2306472

URL

https://www.tandfonline.com/doi/full/10.1080/00949655.2024.2306472

Ministry points / journal

70

Impact Factor

1,2 [List 2022]

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