On the Optimal Constant-Stress Acceleration Based on Competing Risks with Progressive Type-II Censoring for Lindley Distribution

In this study, We investigate competing risks and multiple levels constant-stress for accelerated life test using progressive type-II censoring. Assuming that the failure causes are independent and follow Lindley distribution. The optimization problem of the constant-stress for accelerated life test is investigated using two optimization criterions. Maximum likelihood estimate and the corresponding asymptotic confidence intervals are derived. Bayes estimate and credible confidence intervals are also obtained based on progressive type-II censoring. A real-world data examples are examined to illustrate the approaches employed in this study. Finally, simulation studies are executed to validate the estimates.