Statistical Inference For A Simple Step–Stress Model With Type–II Hybrid Censored Data From The Kumaraswamy Weibull Distribution

Journal of Data Science

article

R. E. Ibrahim¹  H. E. Semary¹ 

[1] Department of Statistics and Insurance, Faculty of Commerce Zagazig University

关键词: Accelerated testing;    Coverage probability;    Cumulative exposure model;    Kumaraswamy Weibull distribution;   

DOI  :  10.6339/JDS.202001_18(1).0007

学科分类：土木及结构工程学

来源: JDS

【 摘 要 】

In reliability and life-testing experiments, the researcher is often interested in the effects of extreme or varying stress factors on the lifetimes of experimental units. In this paper, a step-stress model is considered in which the life-testing experiment gets terminated either at a pre-fixed time (say, Tm+1) or at a random time ensuring at least a specified number of failures (Say, y out of n). Under this model in which the data obtained are Type-II hybrid censored, the Kumaraswamy Weibull distribution is used for the underlying lifetimes. The maximum Likelihood estimators (MLEs) of the parameters assuming a cumulative exposure model are derived. The confidence intervals of the parameters are also obtained. The hazard rate and reliability functions are estimated at usual conditions of stress. Monte Carlo simulation is carried out to investigate the precision of the maximum likelihood estimates. An application using real data is used to indicate the properties of the maximum likelihood estimators.

【 授权许可】

CC BY