Abstract

This paper considers a step-stress accelerated dependent competing risks model under progressively Type-I censoring schemes. The dependence structure between competing risks is modeled by a general bivariate function, the cumulative exposure model is assumed and the accelerated model is described by the power rule model. The point and interval estimation of the model parameters and the reliability under normal usage level at mission time are obtained by using the maximum likelihood method and the asymptotic normal theory. We also consider the Bayesian estimators and the highest posterior density credible intervals based on conjugate priors, E-Bayesian, hierarchical Bayesian and empirical Bayesian methods. To illustrate the proposed methodology, the Marshall-Olkin bivariate exponential distribution is used to model the dependence structure between competing risks. A Monte Carlo simulation study and a real data analysis are presented to study the performance of different estimation methods.

摘要

本文考虑了渐进式 I 型审查方案下的阶跃压力加速依赖竞争风险模型。竞争风险之间的依赖结构由一般的双变量函数建模，累积暴露模型被假设，加速模型由幂规则模型描述。利用极大似然法和渐近正态理论，得到模型参数的点和区间估计以及任务时正常使用水平下的可靠性。我们还考虑了基于共轭先验、E-贝叶斯、分层贝叶斯和经验贝叶斯方法的贝叶斯估计量和最高后验密度可信区间。为了说明建议的方法，Marshall-Olkin 双变量指数分布用于模拟竞争风险之间的依赖结构。提出了蒙特卡罗模拟研究和真实数据分析来研究不同估计方法的性能。