Statistical Inference of Jointly Type-II Lifetime Samples under Weibull Competing Risks Models

Abstract

In this paper, we develop statistical inference of competing risks samples which are collected under a joint Type-II censoring scheme of products with Weibull lifetime distributions. These inferences are drawn from two independent fatal risks and come from two different lines of production with the same facility. The model parameters and the parameters of life (reliability and hazard rate functions) are estimated using maximum likelihood (ML), bootstrap and Bayes methods. Additionally, we constructed asymptotic ML confidence intervals, bootstrap confidence intervals and Bayes credible intervals. Furthermore, the theoretical results are assessed and compared through Monte Carlo simulations. Finally, one real data set is analyzed under the proposed model for illustrative purpose.

Keywords

• Bayes estimation
• bootstrap confidence intervals
• competing risks model
• joint Type-II censoring scheme
• maximum likelihood
• Weibull distribution