Estimating percentiles of time-to-failure distribution obtained from a Weibull accelerated degradation model

Ebrahem, Mohammed Al-Haj; Abedalqader, Mohammad

doi:10.47974/JSMS-1207

Open Access Research Article

Estimating percentiles of time-to-failure distribution obtained from a Weibull accelerated degradation model

^*Mohammed Al-Haj EbrahemCorresponding authormalhaj@yu.edu.joDepartment of Statistics Yarmouk UniversityIrbid, 21163, JordanView full profile → , Mohammad Abedalqader2017107012@ses.yu.edu.joDepartment of Statistics Yarmouk UniversityIrbid, 21163, JordanView full profile →

* Corresponding author · click or hover a name for details

pp. 79–87Vol. 28Issue 1January 2025DOI: 10.47974/JSMS-1207XML

Received:: 05 Dec 2022
Published Online:: 15 Jan 2025
Article type:: Research Article
Language:: EN
Article no.:: JSMS-1207
Pages:: 79–87

Abstract

We propose a nonparametric kernel estimation method to estimate the percentiles of the time-to-failure distribution under the usual use condition obtained from a Weibull accelerated degradation model. We discuss some of the well-known parametric methods that used to estimate the time-to-failure distribution and its percentile under the usual use condition including ordinary least square method and maximum likelihood method. The different exiting methods were compared with the kernel method through simulation by using the mean square error and the bootstrap confidence interval length. In general, when the distributional assumption is available, the maximum likelihood estimator performs better than the oher two estimators, while the kernel estimator performs better than the other two estimators when the distributional assumption is not available. Application to real data set was disscuced.

Keywords

Accelerated degradation model Kernel method Maximum likelihood Ordinary least squares Reliability Weibull distribution

Subject Classifications

62N0562G05

References

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