On competing risk model under step-stress stage life testing

Abstract

In this article, we consider the inference of a dependent competing risk model when the data are collected from a simple step-stress stage life testing experiment. We assume that there are two causes of failure and they are dependent causes. The dependency structure is explained through Marshall–Olkin bivariate Weibull distribution. The distribution under two stress levels is connected through Khamis Higgins model. We obtain the maximum likelihood estimates and the Bayes estimates of the model parameters. We also provide the asymptotic confidence intervals, symmetric credible intervals and the highest posterior density credible intervals of the model parameters. An optimality study has been done under different optimality criteria. An extensive simulation study and a data analysis have been performed for illustrative purpose.

Keywords:

• Dependent competing risk
• maximum likelihood estimates
• Bayes estimates
• confidence interval
• credible interval
• optimality

Disclosure statement

No potential conflict of interest was reported by the author(s).