ABSTRACT

Marshall–Olkin bivariate exponential distribution is used to statistically infer the adaptive type II progressive hybrid censored data under dependent competition risk model. For complex censored data with only partial failure reasons observed, maximum likelihood estimation and approximate confidence interval based on Fisher information are established. At the same time, Bayesian estimation is performed under the highly flexible Gamma–Dirichlet prior distribution and the highest posterior density interval using Gibbs sampling and Metropolis–Hastings algorithm is obtained. Then the performance of two methods is compared through several indexes. In addition, the Monte Carlo method is used for data simulation of multiple sets of variables to give experimental suggestions. Finally, a practical example is given to illustrate the operability and applicability of the proposed algorithm to efficiently carry out reliability test.

摘要

Marshall-Olkin 双变量指数分布用于统计推断依赖竞争风险模型下的自适应 II 型渐进混合删失数据。对于仅观察到部分失效原因的复杂删失数据，建立基于Fisher信息的最大似然估计和近似置信区间。同时在高度灵活的Gamma-Dirichlet先验分布下进行贝叶斯估计，利用Gibbs采样和Metropolis-Hastings算法得到最高后验密度区间。然后通过几个指标比较两种方法的性能。此外，蒙特卡罗方法用于多组变量的数据模拟，给出实验建议。最后，